The Women's Health Initiative Randomized Trials and Clinical Practice: A Review.

Importance: Approximately 55 million people in the US and approximately 1.1 billion people worldwide are postmenopausal women. To inform clinical practice about the health effects of menopausal hormone therapy, calcium plus vitamin D supplementation, and a low-fat dietary pattern, the Women's Health Initiative (WHI) enrolled 161 808 postmenopausal US women (N = 68 132 in the clinical trials) aged 50 to 79 years at baseline from 1993 to 1998, and followed them up for up to 20 years. Observations: The WHI clinical trial results do not support hormone therapy with oral conjugated equine estrogens plus medroxyprogesterone acetate for postmenopausal women or conjugated equine estrogens alone for those with prior hysterectomy to prevent cardiovascular disease, dementia, or other chronic diseases. However, hormone therapy is effective for treating moderate to severe vasomotor and other menopausal symptoms. These benefits of hormone therapy in early menopause, combined with lower rates of adverse effects of hormone therapy in early compared with later menopause, support initiation of hormone therapy before age 60 years for women without contraindications to hormone therapy who have bothersome menopausal symptoms. The WHI results do not support routinely recommending calcium plus vitamin D supplementation for fracture prevention in all postmenopausal women. However, calcium and vitamin D are appropriate for women who do not meet national guidelines for recommended intakes of these nutrients through diet. A low-fat dietary pattern with increased fruit, vegetable, and grain consumption did not prevent the primary outcomes of breast or colorectal cancer but was associated with lower rates of the secondary outcome of breast cancer mortality during long-term follow-up. Conclusions and Relevance: For postmenopausal women, the WHI randomized clinical trials do not support menopausal hormone therapy to prevent cardiovascular disease or other chronic diseases. Menopausal hormone therapy is appropriate to treat bothersome vasomotor symptoms among women in early menopause, without contraindications, who are interested in taking hormone therapy. The WHI evidence does not support routine supplementation with calcium plus vitamin D for menopausal women to prevent fractures or a low-fat diet with increased fruits, vegetables, and grains to prevent breast or colorectal cancer. A potential role of a low-fat dietary pattern in reducing breast cancer mortality, a secondary outcome, warrants further study.

Long-Term Effect of Randomization to Calcium and Vitamin D Supplementation on Health in Older Women : Postintervention Follow-up of a Randomized Clinical Trial.

BACKGROUND: Although calcium and vitamin D (CaD) supplementation may affect chronic disease in older women, evidence of long-term effects on health outcomes is limited. OBJECTIVE: To evaluate long-term health outcomes among postmenopausal women in the Women's Health Initiative CaD trial. DESIGN: Post hoc analysis of long-term postintervention follow-up of the 7-year randomized intervention trial of CaD. (ClinicalTrials.gov: NCT00000611). SETTING: A multicenter (n = 40) trial across the United States. PARTICIPANTS: 36 282 postmenopausal women with no history of breast or colorectal cancer. INTERVENTION: Random 1:1 assignment to 1000 mg of calcium carbonate (400 mg of elemental calcium) with 400 IU of vitamin D3 daily or placebo. MEASUREMENTS: Incidence of colorectal, invasive breast, and total cancer; disease-specific and all-cause mortality; total cardiovascular disease (CVD); and hip fracture by randomization assignment (through December 2020). Analyses were stratified on personal supplement use. RESULTS: For women randomly assigned to CaD versus placebo, a 7% reduction in cancer mortality was observed after a median cumulative follow-up of 22.3 years (1817 vs. 1943 deaths; hazard ratio [HR], 0.93 [95% CI, 0.87 to 0.99]), along with a 6% increase in CVD mortality (2621 vs. 2420 deaths; HR, 1.06 [CI, 1.01 to 1.12]). There was no overall effect on other measures, including all-cause mortality (7834 vs. 7748 deaths; HR, 1.00 [CI, 0.97 to 1.03]). Estimates for cancer incidence varied widely when stratified by whether participants reported supplement use before randomization, whereas estimates on mortality did not vary, except for CVD mortality. LIMITATION: Hip fracture and CVD outcomes were available on only a subset of participants, and effects of calcium versus vitamin D versus joint supplementation could not be disentangled. CONCLUSION: Calcium and vitamin D supplements seemed to reduce cancer mortality and increase CVD mortality after more than 20 years of follow-up among postmenopausal women, with no effect on all-cause mortality. PRIMARY FUNDING SOURCE: National Heart, Lung, and Blood Institute of the National Institutes of Health.

Biomarker-assessed total energy intake and its cohort study association with all-cause mortality in postmenopausal females.

BACKGROUND: The association of total energy intake (EI) with all-cause mortality is uncertain as are the dependencies of this association on age and weight change history. OBJECTIVES: To identify an EI biomarker suitable for use in epidemiologic association studies and to study EI associations with total mortality in a Women's Health Initiative (WHI) cohort of postmenopausal United States females (1993-present). METHODS: EI biomarkers were developed based on doubly labeled water (DLW) total energy expenditure (TEE) and weight variation during the 2-wk DLW protocol period using the energy balance method in an embedded feeding study (n = 153). This along with 2 earlier WHI nutrition biomarker studies having TEE assessments (n = 1131 total), with 14.6 y (median) follow-up, constituted a prospective cohort for the study of EI and all-cause mortality. RESULTS: An empirical biomarker for log(EI) was developed that had a correlation of 0.73 with log(feeding study-consumed EI). The overall association between EI and mortality was nonsignificant. The association, however, depended on age (P = 0.009), with lower EI associated with lower mortality at younger ages, and also on preceding weight change history (P = 0.03). Among participants with stable or increasing weight, mortality hazard ratios (95% confidence intervals [CIs]) for a 12% lower EI were 0.66 (95% CI: 0.51, 0.87) at age 60, 0.84 (95% CI: 0.72, 0.98) at age 70, and 1.06 (95% CI: 0.87, 1.29) at age 80. Corresponding values for participants having preceding weight loss were 0.83 (95% CI: 0.61, 1.12) at age 60, 1.05 (95% CI: 0.87, 1.26) at age 70, and 1.33 (95% CI: 1.08, 1.63) at age 80. A previously considered EI biomarker, using a theoretical model for variation in body fat and fat-free mass components over time, gave similar results following rescaling. CONCLUSIONS: Lower EI is associated with lower all-cause mortality among younger postmenopausal females with stable or increasing weight and with higher mortality among older females with weight loss. This study was registered with clinicaltrials.gov as NCT00000611.

Measuring diet by metabolomics: a 14-d controlled feeding study of weighed food intake.

BACKGROUND: Metabolomics has the potential to enhance dietary assessment by revealing objective measures of many aspects of human food intake. Although metabolomics studies indicate that hundreds of metabolites are associated with dietary intake, correlations have been modest (e.g., r < 0.50), and few have been evaluated in controlled feeding studies. OBJECTIVES: The aim of this study was to evaluate associations between metabolites and weighed food and beverage intake in a controlled feeding study of habitual diet. METHODS: Healthy postmenopausal females from the Women's Health Initiative (N = 153) were provided with a customized 2-wk controlled diet designed to emulate their usual diet. Metabolites were measured by liquid chromatography tandem mass spectrometry in end-of-study 24-h urine and fasting serum samples (1293 urine metabolites; 1113 serum metabolites). We calculated partial Pearson correlations between these metabolites and intake of 65 food groups, beverages, and supplements during the feeding study. The threshold for significance was Bonferroni-adjusted to account for multiple testing (5.94 × 10-07 for urine metabolites; 6.91 × 10-07 for serum metabolites). RESULTS: Significant diet-metabolite correlations were identified for 23 distinct foods, beverages, and supplements (171 distinct metabolites). Among foods, strong metabolite correlations (r ≥ 0.60) were evident for citrus (highest r = 0.80), dairy (r = 0.65), and broccoli (r = 0.63). Among beverages and supplements, strong correlations were evident for coffee (r = 0.86), alcohol (r = 0.69), multivitamins (r = 0.69), and vitamin E supplements (r = 0.65). Moderate correlations (r = 0.50-0.60) were also observed for avocado, fish, garlic, grains, onion, poultry, and black tea. Correlations were specific; each metabolite correlated with one food, beverage, or supplement, except for metabolites correlated with juice or multivitamins. CONCLUSIONS: Metabolite levels had moderate to strong correlations with weighed intake of habitually consumed foods, beverages, and supplements. These findings exceed in magnitude those previously observed in population studies and exemplify the strong potential of metabolomics to contribute to nutrition research. The Women's Health Initiative is registered at clinicaltrials.gov as NCT00000611.

Diet and Chronic Disease Research in the Women's Health Initiative.

The Women's Health Initiative (WHI) has been a major contributor to diet and chronic disease research among postmenopausal US women over its 30+ year history (1993 to present). The WHI program included full-scale randomized trials of a low-fat dietary pattern high in fruits, vegetables, and grains, and of calcium and vitamin D supplementation, each with designated primary and secondary chronic disease outcomes. The history of these trials will be briefly reviewed here, along with principal findings that included evidence for breast cancer-related benefits for each of the 2 interventions. In recent years, WHI investigators have developed an active research program in nutritional biomarker development and in the application of these biomarkers in WHI cohorts, among various other nutritional epidemiology uses of WHI observational study resources. The intake biomarker work, which primarily relies on blood and urine metabolomics profiles, lends support to the low-fat dietary pattern trial results, and supports chronic disease benefits of higher carbohydrate diets more generally, especially through the fiber component of carbohydrate.

Regression calibration utilizing biomarkers developed from high-dimensional metabolites.

Addressing systematic measurement errors in self-reported data is a critical challenge in association studies of dietary intake and chronic disease risk. The regression calibration method has been utilized for error correction when an objectively measured biomarker is available; however, biomarkers for only a few dietary components have been developed. This paper proposes to use high-dimensional objective measurements to construct biomarkers for many more dietary components and to estimate the diet disease associations. It also discusses the challenges in variance estimation in high-dimensional regression methods and presents a variety of techniques to address this issue, including cross-validation, degrees-of-freedom corrected estimators, and refitted cross-validation (RCV). Extensive simulation is performed to study the finite sample performance of the proposed estimators. The proposed method is applied to the Women's Health Initiative cohort data to examine the associations between the sodium/potassium intake ratio and the total cardiovascular disease.

Metabolomics-Based Biomarker for Dietary Fat and Associations with Chronic Disease Risk in Postmenopausal Women.

BACKGROUND: The Women's Health Initiative (WHI) randomized, controlled Dietary Modification (DM) trial of a low-fat dietary pattern suggested intervention benefits related to breast cancer, coronary heart disease (CHD), and diabetes. Here, we use WHI observational data for further insight into the chronic disease implications of adopting this type of low-fat dietary pattern. OBJECTIVES: We aimed to use our earlier work on metabolomics-based biomarkers of carbohydrate and protein to develop a fat intake biomarker by subtraction, to use the resulting biomarker to develop calibration equations that adjusts self-reported fat intake for measurement error, and to study associations of biomarker-calibrated fat intake with chronic disease risk in WHI cohorts. Corresponding studies for specific fatty acids will follow separately. METHODS: Prospective disease association results are presented using WHI cohorts of postmenopausal women, aged 50-79 y when enrolled at 40 United States clinical centers. Biomarker equations were developed using an embedded human feeding study (n = 153). Calibration equations were developed using a WHI nutritional biomarker study (n = 436). Calibrated intakes were associated with cancer, cardiovascular diseases, and diabetes incidence in WHI cohorts (n = 81,954) over an approximate 20-y follow-up period. RESULTS: A biomarker for fat density was developed by subtracting protein, carbohydrate, and alcohol densities from one. A calibration equation was developed for fat density. Hazard ratios (95% confidence intervals) for 20% higher fat density were 1.16 (1.06, 1.27) for breast cancer, 1.13 (1.02, 1.26) for CHD, and 1.19 (1.13, 1.26) for diabetes, in substantial agreement with findings from the DM trial. With control for additional dietary variables, especially fiber, fat density was no longer associated with CHD, with hazard ratio (95% confidence interval) of 1.00 (0.88, 1.13), whereas that for breast cancer was 1.11 (1.00, 1.24). CONCLUSIONS: WHI observational data support prior DM trial findings of low-fat dietary pattern benefits in this population of postmenopausal United States women. TRIAL REGISTRATION NUMBER: This study is registered with clinicaltrials.gov identifier: NCT00000611.

Metabolomics Biomarkers for Fatty Acid Intake and Biomarker-Calibrated Fatty Acid Associations with Chronic Disease Risk in Postmenopausal Women.

BACKGROUND: A substantial observational literature relating specific fatty acid classes to chronic disease risk may be limited by its reliance on self-reported dietary data. OBJECTIVES: We aimed to develop biomarkers for saturated (SFA), monounsaturated (MUFA), and polyunsaturated (PUFA) fatty acid densities, and to study their associations with cardiovascular disease (CVD), cancer, and type 2 diabetes (T2D) in Women's Health Initiative (WHI) cohorts. METHODS: Biomarker equations were based primarily on serum and urine metabolomics profiles from an embedded WHI human feeding study (n = 153). Calibration equations were based on biomarker values in a WHI nutritional biomarker study (n = 436). Calibrated intakes were assessed in relation to disease incidence in larger WHI cohorts (n = 81,894). Participants were postmenopausal women, aged 50-79 when enrolled at 40 United States Clinical Centers (1993-1998), with a follow-up period of ∼20 y. RESULTS: Biomarker equations meeting criteria were developed for SFA, MUFA, and PUFA densities. That for SFA density depended somewhat weakly on metabolite profiles. On the basis of our metabolomics platforms, biomarkers were insensitive to trans fatty acid intake. Calibration equations meeting criteria were developed for SFA and PUFA density, but not for MUFA density. With or without biomarker calibration, SFA density was associated positively with risk of CVD, cancer, and T2D, but with small hazard ratios, and CVD associations were not statistically significant after controlling for other dietary variables, including trans fatty acid and fiber intake. Following this same control, PUFA density was not significantly associated with CVD risk, but there were positive associations for some cancers and T2D, with or without biomarker calibration. CONCLUSIONS: Higher SFA and PUFA diets were associated with null or somewhat higher risk for clinical outcomes considered in this population of postmenopausal United States women. Further research is needed to develop even stronger biomarkers for these fatty acid densities and their major components. This study is registered with clinicaltrials.gov identifier: NCT00000611.

Demographic, Health and Lifestyle Factors Associated with the Metabolome in Older Women.

Demographic and clinical factors influence the metabolome. The discovery and validation of disease biomarkers are often challenged by potential confounding effects from such factors. To address this challenge, we investigated the magnitude of the correlation between serum and urine metabolites and demographic and clinical parameters in a well-characterized observational cohort of 444 post-menopausal women participating in the Women's Health Initiative (WHI). Using LC-MS and lipidomics, we measured 157 aqueous metabolites and 756 lipid species across 13 lipid classes in serum, along with 195 metabolites detected by GC-MS and NMR in urine and evaluated their correlations with 29 potential disease risk factors, including demographic, dietary and lifestyle factors, and medication use. After controlling for multiple testing (FDR < 0.01), we found that log-transformed metabolites were mainly associated with age, BMI, alcohol intake, race, sample storage time (urine only), and dietary supplement use. Statistically significant correlations were in the absolute range of 0.2-0.6, with the majority falling below 0.4. Incorporation of important potential confounding factors in metabolite and disease association analyses may lead to improved statistical power as well as reduced false discovery rates in a variety of data analysis settings.

Total energy expenditure as assessed by doubly labeled water and all-cause mortality in a cohort of postmenopausal women.

BACKGROUND: The association of TEE with all-cause mortality is uncertain, as is the dependence of this association on age. OBJECTIVES: To examine the association between TEE and all-cause mortality, and its age interaction, in a Women's Health Initiative (WHI) cohort of postmenopausal United States women (1992-present). METHODS: A cohort of 1131 WHI participants having DLW TEE assessment of ∼10.0 y (median) following WHI enrollment with ∼13.7 y (median) of subsequent follow-up, was used to study the EE associations with all-cause mortality. To enhance the comparability of TEE and total EI, key analyses excluded participants having >5% weight change between WHI enrollment and DLW assessment. The influence of participant age on mortality associations was examined, as was the ability of concurrent and earlier weight and height measurements to explain the results. RESULTS: There were 308 deaths following the TEE assessment through 2021. TEE was unrelated to overall mortality (P = 0.83) in this cohort of generally healthy, older (mean 71 y at TEE assessment) United States women. However, this potential association varied with age (P = 0.003). Higher TEE was associated with a higher mortality rate at the age of 60 y and a lower mortality rate at the age of 80 y. Within the weight-stable subset (532 participants, 129 deaths), TEE was weakly positively related to overall mortality (P = 0.08). This association also varied with age (P = 0.03), with mortality HRs (95% CIs) for a 20% increment in TEE of 2.33 (1.24, 4.36) at the age of 60 y, 1.49 (1.10, 2.02) at 70 y of age, and 0.96 (0.66, 1.38) at 80 y of age. This pattern remained, although was somewhat attenuated, following control for baseline weight and weight changes between WHI enrollment and TEE assessment. CONCLUSIONS: Higher EE is associated with higher all-cause mortality among younger postmenopausal women, only partially explained by weight and weight change. This study is registered with clinicaltrials.gov identifier: NCT00000611.

Enhancing Capacity for Food and Nutrient Intake Assessment in Population Sciences Research.

Nutrition influences health throughout the life course. Good nutrition increases the probability of good pregnancy outcomes, proper childhood development, and healthy aging, and it lowers the probability of developing common diet-related chronic diseases, including obesity, cardiovascular disease, cancer, and type 2 diabetes. Despite the importance of diet and health, studying these exposures is among the most challenging in population sciences research. US and global food supplies are complex; eating patterns have shifted such that half of meals are eaten away from home, and there are thousands of food ingredients with myriad combinations. These complexities make dietary assessment and links to health challenging both for population sciences research and for public health policy and practice. Furthermore, most studies evaluating nutrition and health usually rely on self-report instruments prone to random and systematic measurement error. Scientific advances involve developing nutritional biomarkers and then applying these biomarkers as stand-alone nutritional exposures or for calibrating self-reports using specialized statistics.

Associations of Biomarker-Calibrated Healthy Eating Index-2010 Scores with Chronic Disease Risk and Their Dependency on Energy Intake and Body Mass Index in Postmenopausal Women.

BACKGROUND: Prior studies examined associations between the Healthy Eating Index (HEI) and chronic disease risk based on self-reported diet without measurement error correction. OBJECTIVE: Our objective was to test associations between biomarker calibration of the food-frequency questionnaire (FFQ)-derived HEI-2010 with incident cardiovascular disease (CVD), cancer, and type 2 diabetes (T2D) among Women's Health Initiative (WHI) participants. METHODS: Data were derived from WHI postmenopausal women (n = 100,374) aged 50-79 y at enrollment (1993-1998) at 40 US clinical centers, linked to nutritional biomarker substudies and outcomes over subsequent decades of follow-up. Baseline or year 1 FFQ-derived HEI-2010 scores were calibrated with nutritional biomarkers and participant characteristics (e.g., BMI) for systematic measurement error correction. Calibrated data were then used in HR models examining associations with incidence of CVD (total, subtypes, mortality), cancer (total, subtypes, mortality), and T2D in WHI participants with approximately 2 decades of follow-up. Models were multivariable-adjusted with further adjustment for BMI and doubly labeled water (DLW)-calibrated energy. RESULTS: Multivariable-adjusted HRs modeled a 20% increment in HEI-2010 score in relation to outcomes. HRs were modest using uncalibrated HEI-2010 scores (HRs = 0.91-1.09). Using biomarker-calibrated HEI-2010, 20% increments in scores yielded multivariable-adjusted HRs (95% CIs) of 0.75 (0.60, 0.93) for coronary heart disease; 0.75 (0.61, 0.91) for myocardial infarction; 0.96 (0.92, 1.01) for stroke; 0.88 (0.75, 1.02) for CVD mortality; 0.81 (0.70, 0.94) for colorectal cancer; 0.81 (0.74, 0.88) for breast cancer; 0.79 (0.73, 0.87) for cancer mortality; and 0.45 (0.36-0.55) for T2D. Except for cancer mortality and T2D incidence, results became null when adjusted for DLW-calibrated energy intake and BMI. CONCLUSIONS: Biomarker calibration of FFQ-derived HEI-2010 was associated with lower CVD and cancer incidence and mortality and lower T2D incidence in postmenopausal women. Attenuation after adjustment with BMI and DLW-calibrated energy suggests that energy intake and/or obesity are strong drivers of diet-related chronic disease risk in postmenopausal women. The Women's Health Initiative is registered at clinicaltrials.gov at NCT00000611.

Constitutional BRCA1 Methylation and Risk of Incident Triple-Negative Breast Cancer and High-grade Serous Ovarian Cancer.

Importance: About 25% of all triple-negative breast cancers (TNBCs) and 10% to 20% of high-grade serous ovarian cancers (HGSOCs) harbor BRCA1 promoter methylation. While constitutional BRCA1 promoter methylation has been observed in normal tissues of some individuals, the potential role of normal tissue methylation as a risk factor for incident TNBC or HGSOC is unknown. Objective: To assess the potential association between white blood cell BRCA1 promoter methylation and subsequent risk of incident TNBC and HGSOC. Design, Setting, and Participants: This case-control study included women who were participating in the Women's Health Initiative study who had not received a diagnosis of either breast or ovarian cancer before study entrance. A total of 637 women developing incident TNBC and 511 women developing incident HGSOC were matched with cancer-free controls (1841 and 2982, respectively) in a nested case-control design. Cancers were confirmed after central medical record review. Blood samples, which were collected at entry, were analyzed for BRCA1 promoter methylation by massive parallel sequencing. The study was performed in the Mohn Cancer Research Laboratory (Bergen, Norway) between 2019 and 2022. Main Outcomes and Measures: Associations between BRCA1 methylation and incident TNBC and incident HGSOC were analyzed by Cox proportional hazards regression. Results: Of 2478 cases and controls in the TNBC group and 3493 cases and controls in the HGSOC group, respectively, 7 (0.3%) and 3 (0.1%) were American Indian or Alaska Native, 46 (1.9%) and 30 (0.9%) were Asian, 1 (0.04%) and 1 (0.03%) was Native Hawaiian or Pacific Islander, 326 (13.2%) and 125 (3.6%) were Black or African, 56 (2.3%) and 116 (3.3%) were Hispanic, 2046 (82.6%) and 3257 (93.2%) were White, and 35 (1.4%) and 35 (1.0%) were multiracial. Median (range) age at entry was 62 (50-79) years, with a median interval to diagnosis of 9 (TNBC) and 10 (HGSOC) years. Methylated BRCA1 alleles were present in 194 controls (5.5%). Methylation was associated with risk of incident TNBC (12.4% methylated; HR, 2.35; 95% CI, 1.70-3.23; P < .001) and incident HGSOC (9.4% methylated; HR, 1.93; 95% CI, 1.36-2.73; P < .001). Restricting analyses to individuals with more than 5 years between sampling and cancer diagnosis yielded similar results (TNBC: HR, 2.52; 95% CI, 1.75-3.63; P < .001; HGSOC: HR, 1.82; 95% CI, 1.22-2.72; P = .003). Across individuals, methylation was not haplotype-specific, arguing against an underlying cis-acting factor. Within individuals, BRCA1 methylation was observed on the same allele, indicating clonal expansion from a single methylation event. There was no association found between BRCA1 methylation and germline pathogenic variant status. Conclusions and Relevance: The results of this case-control suggest that constitutional normal tissue BRCA1 promoter methylation is significantly associated with risk of incident TNBC and HGSOC, with potential implications for prediction of these cancers. These findings warrant further research to determine if constitutional methylation of tumor suppressor genes are pancancer risk factors.

Human total, basal and activity energy expenditures are independent of ambient environmental temperature.

Lower ambient temperature (Ta) requires greater energy expenditure to sustain body temperature. However, effects of Ta on human energetics may be buffered by environmental modification and behavioral compensation. We used the IAEA DLW database for adults in the USA (n = 3213) to determine the effect of Ta (-10 to +30°C) on TEE, basal (BEE) and activity energy expenditure (AEE) and physical activity level (PAL). There were no significant relationships (p > 0.05) between maximum, minimum and average Ta and TEE, BEE, AEE and PAL. After adjustment for fat-free mass, fat mass and age, statistically significant (p < 0.01) relationships between TEE, BEE and Ta emerged in females but the effect sizes were not biologically meaningful. Temperatures inside buildings are regulated at 18-25°C independent of latitude. Hence, adults in the US modify their environments to keep TEE constant across a wide range of external ambient temperatures.

Contributions of the Women's Health Initiative to Cardiovascular Research: JACC State-of-the-Art Review.

The WHI (Women's Health Initiative) enrolled 161,808 racially and ethnically diverse postmenopausal women, ages 50-79 years, from 1993 to 1998 at 40 clinical centers across the United States. In its clinical trial component, WHI evaluated 3 randomized interventions (menopausal hormone therapy; diet modification; and calcium/vitamin D supplementation) for the primary prevention of major chronic diseases, including cardiovascular disease, in older women. In the WHI observational study, numerous clinical, behavioral, and social factors have been evaluated as predictors of incident chronic disease and mortality. Although the original interventions have been completed, the WHI data and biomarker resources continue to be leveraged and expanded through ancillary studies to yield novel insights regarding cardiovascular disease prevention and healthy aging in women.

Criteria for Acceptable Dietary Intake Biomarkers.

Dietary intake biomarkers that can be written as actual intake, plus 'error' that is independent of actual intake and confounding factors can substitute for actual intake in disease association analyses. Also, such biomarkers can be used to develop calibration equations using self-reported diet and participant measures, and biomarker-calibrated intakes can be calculated in larger cohorts for use in disease association analyses. Criteria for biomarkers, and for biomarker-calibrated intakes, arise by working back from properties needed for valid disease association analyses. Accordingly, arguments for a potential biomarker are strengthened if error components are small relative to actual intakes, and important sources of reduced sensitivity or specificity are not apparent. Feeding study biomarker development can then involve regression of actual intake on putative biomarkers, with regression R2 values playing a role in biomarker evaluation. In comparison, 'predictive' biomarker status, as argued in this issue by Freedman and colleagues for 24-hour urinary sucrose plus fructose as biomarker for total sugars, involves regression of potential biomarker on actual intake and other variables, with parameter stability across populations and limited within-person variability as criteria. The choice of criteria for biomarkers and for biomarker-calibrated intakes, is discussed here, in the context of total sugars intake. See related article by Freedman et al., p. 1227.

On the targets of inference with multivariate failure time data.

There are several different topics that can be addressed with multivariate failure time regression data. Data analysis methods are needed that are suited to each such topic. Specifically, marginal hazard rate models are well suited to the analysis of exposures or treatments in relation to individual failure time outcomes, when failure time dependencies are themselves of little or no interest. On the other hand semiparametric copula models are well suited to analyses where interest focuses primarily on the magnitude of dependencies between failure times. These models overlap with frailty models, that seem best suited to exploring the details of failure time clustering. Recently proposed multivariate marginal hazard methods, on the other hand, are well suited to the exploration of exposures or treatments in relation to single, pairwise, and higher dimensional hazard rates. Here these methods will be briefly described, and the final method will be illustrated using the Women's Health Initiative hormone therapy trial data.

Biomarker-Calibrated Red and Combined Red and Processed Meat Intakes with Chronic Disease Risk in a Cohort of Postmenopausal Women.

BACKGROUND: The associations of red and processed meat with chronic disease risk remain to be clarified, in part because of measurement error in self-reported diet. OBJECTIVES: We sought to develop metabolomics-based biomarkers for red and processed meat, and to evaluate associations of biomarker-calibrated meat intake with chronic disease risk among postmenopausal women. METHODS: Study participants were women who were members of the Women's Health Initiative (WHI) study cohorts. These participants were postmenopausal women aged 50-79 y when enrolled during 1993-1998 at 40 US clinical centers with embedded human feeding and nutrition biomarker studies. Literature reports of metabolomics correlates of meat consumption were used to develop meat intake biomarkers from serum and 24-h urine metabolites in a 153-participant feeding study (2010-2014). Resulting biomarkers were used in a 450-participant biomarker study (2007-2009) to develop linear regression calibration equations that adjust FFQ intakes for random and systematic measurement error. Biomarker-calibrated meat intakes were associated with cardiovascular disease, cancer, and diabetes incidence among 81,954 WHI participants (1993-2020). RESULTS: Biomarkers and calibration equations meeting prespecified criteria were developed for consumption of red meat and red plus processed meat combined, but not for processed meat consumption. Following control for nondietary confounding factors, hazard ratios were calculated for a 40% increment above the red meat median intake for coronary artery disease (HR: 1.10; 95% CI: 1.07, 1.14), heart failure (HR: 1.26; 95% CI: 1.20, 1.33), breast cancer (HR: 1.10; 95% CI: 1.07, 1.13) for, total invasive cancer (HR: 1.07; 95% CI: 1.05, 1.09), and diabetes (HR: 1.37; 95% CI: 1.34, 1.39). HRs for red plus processed meat intake were similar. HRs were close to the null, and mostly nonsignificant following additional control for dietary potential confounding factors, including calibrated total energy consumption. CONCLUSIONS: A relatively high-meat dietary pattern is associated with somewhat higher chronic disease risks. These elevations appear to be largely attributable to the dietary pattern, rather than to consumption of red or processed meat per se.

Assessing the validity of plasma phospholipid fatty acids as biomarkers of dairy fat intake using data from a randomized controlled intervention trial.

BACKGROUND: Plasma phospholipid pentadecanoic acid (C15:0), heptadecanoic acid (C17:0), and trans-palmitoleic acid (trans-C16:1n-7) are correlates of dairy fat intake. However, their relative concentrations may be influenced by other endogenous factors, such as liver fat content, and their validity as biomarkers of dairy fat intake has yet to be established. OBJECTIVES: We investigated whether liver fat content modifies relations between concentrations of C15:0, C17:0, and trans-C16:1n-7 (alone and in combination with iso-C17:0) and known dairy fat intake in the context of a randomized controlled intervention study. We further examined the proportion of dairy fat intake explained by these fatty acids on their own and when considering liver fat content. METHODS: We used data from a 12-wk intervention trial in which participants (n = 62) consumed diets limited in dairy (0.3 g/d of dairy fat), rich in low-fat dairy (8.7 g/d of dairy fat), or rich in full-fat dairy (28.5 g/d of dairy fat). We used linear regression models to examine relations between relative fatty acid concentrations and grams per day of dairy fat intake, liver fat percentage, and their interaction. RESULTS: Only trans-C16:1n-7 in isolation (ß: 0.0004 ± 0.0002, P = 0.03) and combined with iso-C17:0 (ß: 0.002 ± 0.0005, P < 0.0001) were consistently positively associated with dairy fat intake regardless of liver fat content. Trans-C16:1n-7 combined with iso-C17:0 also explained the greatest proportion of variation (35.4%) in dairy fat intake. C15:0 and C17:0 were not associated with dairy fat intake after adjusting for liver fat and were predicted to be higher in relation to increased dairy fat intake only among individuals with elevated liver fat. CONCLUSIONS: The potential for liver fat to affect relative plasma phospholipid concentrations of C15:0 and C17:0 raises questions about their validity as biomarkers of dairy fat intake. Of the fatty acid measures tested, trans-C16:1n-7 combined with iso-C17:0, especially with adjustment of liver fat, age, and sex, may provide the most robust estimate of dairy fat consumption.