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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., (Copyright © 2023 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.)

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., (Copyright © 2023 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.)

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., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Society for Nutrition.)

Background: We recently developed protein and carbohydrate intake biomarkers using metabolomics profiles in serum and urine, and used them to correct self-reported dietary data for measurement error. Biomarker-calibrated carbohydrate density was inversely associated with chronic disease risk, whereas protein density associations were mixed., Objectives: To elucidate and extend this earlier work through biomarker development for protein and carbohydrate components, including animal protein and fiber., Methods: Prospective disease association analyses were undertaken in Women's Health Initiative (WHI) cohorts of postmenopausal US women, aged 50-79 y when enrolled at 40 US clinical centers. Biomarkers were developed using an embedded human feeding study (n = 153). Calibration equations for protein and carbohydrate components were developed using a WHI nutritional biomarker study (n = 436). Calibrated intakes were associated with chronic disease incidence in WHI cohorts (n = 81,954) over a 20-y (median) follow-up period, using HR regression methods., Results: Previously reported elevations in cardiovascular disease (CVD) with higher-protein diets tended to be explained by animal protein density. For example, for coronary heart disease a 20% increment in animal protein density had an HR of 1.20 (95% CI: 1.02, 1.42) relative to the HR for total protein density. In comparison, cancer and diabetes risk showed little association with animal protein density beyond that attributable to total protein density. Inverse carbohydrate density associations with total CVD were mostly attributable to fiber density, with a 20% increment HR factor of 0.89 (95% CI: 0.83, 0.94). Cancer risk showed little association with fiber density, whereas diabetes risk had a 20% increment HR of 0.93 (95% CI: 0.88, 0.98) relative to the HRs for total carbohydrate density., Conclusions: In a population of postmenopausal US women, CVD risk was associated with high-animal-protein and low-fiber diets, cancer risk was associated with low-carbohydrate diets, and diabetes risk was associated with low-fiber/low-carbohydrate diets., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Society for Nutrition.)

Background: Maternal nutrition during pregnancy and lactation has profound effects on the development and lifelong health of the child. Long-chain PUFAs are particularly important for myelination and the development of vision during the perinatal period., Objectives: We conducted a systematic review to examine the relationship between supplementation with omega-3 fatty acids during pregnancy and/or lactation and neurodevelopment in children, to inform the Scientific Report of the 2020 Dietary Guidelines Advisory Committee., Methods: We identified articles on omega-3 fatty acid supplementation in pregnant and lactating women that included measures of neurodevelopment in their children (0-18 y) by searching PubMed, CENTRAL, Embase, and CINAHL Plus. After dual screening articles for inclusion, we qualitatively synthesized and graded the strength of evidence using pre-established criteria for assessing risk of bias, consistency, directness, precision, and generalizability., Results: We included 33 articles from 15 randomized controlled trials (RCTs) and 1 prospective cohort study. Of the 8 RCTs that delivered omega-3 fatty acid dietary supplements during pregnancy alone (200-2200 mg/d DHA and 0-1100 mg/d EPA for approximately 20 wk), 5 studies reported ≥1 finding that supplementation improved measures of cognitive development in the infant or child by 6%-11% (P < 0.05), but all 8 studies also reported ≥1 nonsignificant (P > 0.05) result. There was inconsistent or insufficient evidence for other outcomes (language, social-emotional, physical, motor, or visual development; academic performance; risks of attention deficit disorder, attention-deficit/hyperactivity disorder, autism spectrum disorder, anxiety, or depression) and for supplementation during lactation or both pregnancy and lactation. Populations with a lower socioeconomic status and adolescents were underrepresented and studies lacked racial and ethnic diversity., Conclusions: Limited evidence suggests that omega-3 fatty acid supplementation during pregnancy may result in favorable cognitive development in the child. There was insufficient evidence to evaluate the effects of omega-3 fatty acid supplementation during pregnancy and/or lactation on other developmental outcomes., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.)

Background: Multiple methods of correcting nutrient intake for misreported energy intake have been proposed but have not been extensively compared. The availability of the Women's Health Initiative (WHI) data set, which includes several objective recovery biomarkers, offers an opportunity to compare these corrections with respect to protein intake., Objective: We compared 5 energy-correction methods for self-reported dietary protein against urinary nitrogen-derived protein intake., Methods: As part of the WHI Nutritional Biomarkers Study (NBS) 544 participants (50- to 80-y-old women) completed a FFQ and biomarker assessments using doubly labeled water (DLW) for total energy expenditure (TEE) and 24-h urinary nitrogen. Correction methods evaluated were as follows: 1) DLW-TEE; 2) the Institute of Medicine's (IOM's) estimated energy requirement (EER) TEE prediction equation based on sex, height, weight, and age; 3) published NBS total energy TEE prediction (WHI-NBS-TEE) using age, BMI, race, and income; 4) reported protein versus reported energy linear regression-based residual method; and 5) a Goldberg cutoff to exclude subjects reporting energy intakes <1.35 times their basal metabolic rate. Efficacy was evaluated using correlations obtained by regressing corrected protein against biomarker protein (6.25 × urinary nitrogen/0.81)., Results: Unadjusted self-reported protein intake from the FFQ (mean = 66.7 g) correlated weakly (r = 0.31) with biomarker protein (mean = 74.9 g). DLW-TEE-corrected self-reported protein intake (mean = 90.7 g) had the strongest correlation with biomarker protein (r = 0.47). Other energy corrections yielded lower, but still significant correlations: EER, r = 0.44 (mean = 92.1 g); WHI-NBS-TEE, r = 0.37 (mean = 90.4 g); Goldberg cutoff, r = 0.36 (mean = 88.4 g); and residual method, r = 0.35 (mean = 66.7 g)., Conclusions: Our data indicate that proportional correction of reported protein intake using a measure of energy requirement from DLW-TEE or IOM-EER performed modestly better than other methods in this cohort. These energy adjustments, however, yielded corrected protein exceeding the biomarker protein, indicating that energy adjustment alone does not eliminate all self-reported protein reporting bias., (Copyright © The Author(s) 2020.)

Background: The preferred macronutrient dietary composition, and the health consequences of dietary fat reduction specifically, have been debated for decades. Here we provide a comprehensive overview of long-term health outcomes in the Women's Health Initiative Dietary Modification (DM) trial., Objective: The DM trial aimed to examine whether a low-fat dietary pattern would reduce the risk of invasive breast cancer, colorectal cancer, and, secondarily, coronary heart disease (CHD), with various other health outcomes also considered., Methods: The DM trial is a randomized controlled trial conducted at 40 centers in the US, among 48,835 postmenopausal women aged 50-79 y with baseline intake of ≥32% energy from fat. Participants were randomly assigned to a low-fat dietary pattern intervention group or to a usual-diet comparison group, during 1993-1998. Intervention goals were to reduce fat intake from ∼35% to 20% of total energy, in conjunction with increasing vegetables and fruit to 5 servings/d and grains to 6 servings/d., Results: Over an 8.5-y (median) intervention period, intervention and comparison group differences included lower fat by 8-10%, and higher carbohydrate by 8-10%, of total energy, in conjunction with higher consumption of vegetables, fruit, and grains. Time-to-outcome analyses did not show significant differences between intervention and comparison groups for invasive breast cancer, colorectal cancer, or CHD, either over the intervention period or over longer-term cumulative follow-up. Additional analyses showed significant intervention group benefits related to breast cancer, CHD, and diabetes, without adverse effects. Over a 19.6-y (median) follow-up period, HRs (95% CIs) were 0.84 (0.74, 0.96) for breast cancer followed by death, and 0.87 (0.77, 0.98) for diabetes requiring insulin., Conclusions: Reduction in dietary fat with corresponding increase in vegetables, fruit, and grains led to benefits related to breast cancer, CHD, and diabetes, without adverse effects, among healthy postmenopausal US women., This trial was registered at clinicaltrials.gov as NCT00000611., (Copyright © American Society for Nutrition 2019.)

Coronary heart disease (CHD) is the leading cause of death in women. A nested case-control study tested whether dietary patterns predicted CHD events among 1224 participants in the Women's Health Initiative-Observational Study (WHI-OS) with centrally confirmed CHD, fatal or nonfatal myocardial infarct compared to 1224 WHI-OS controls matched for age, enrollment date, race/ethnicity, and absence of CHD at baseline or follow-up. The first six principal components explained >75% of variation in dietary intakes and K-mean analysis based on these six components produced three clusters. Diet cluster 1 was rich in carbohydrate, vegetable protein, fiber, dietary vitamin K, folate, carotenoids, α-linolenic acid [18:3(n-3)], linoleic acid [18:2(n-6)], and supplemental calcium and vitamin D. Diet cluster 2 was rich in total and animal protein, arachidonic acid [20:4(n-6)], DHA [22:6(n-3)], vitamin D, and calcium. Diet cluster 3 was rich in energy, total fat, and trans fatty acids (all P < 0.01). Conditional logistic regression analysis demonstrated diet cluster 1 was associated with lower CHD risk than diet cluster 2 (reference group) adjusted for smoking, education, and physical activity [OR = 0.79 (95% CI = 0.64, 0.99); P = 0.038]. This difference was not significant after adjustment for BMI and systolic blood pressure. Diet cluster 3 was associated with higher CHD risk than diet cluster 2 [OR = 1.28 (95% CI = 1.04, 1.57); P = 0.019], but this difference did not remain significant after adjustment for smoking, education, and physical activity. Within this WHI-OS cohort, distinct dietary patterns may be associated with subsequent CHD outcomes.

Consumption of foods with a high glycemic index (GI) or glycemic load (GL) is hypothesized to contribute to insulin resistance, which is associated with increased risk of diabetes mellitus, obesity, cardiovascular disease, and some cancers. However, dietary assessment of GI and GL is difficult because values are not included in standard food composition databases. Our objective was to develop a database of GI and GL values that could be integrated into an existing dietary database used for the analysis of FFQ. Food GI values were obtained from published human experimental studies or imputed from foods with a similar carbohydrate and fiber content. We then applied the values to the Women's Health Initiative (WHI) FFQ database and tested the output in a random sample of previously completed WHI FFQs. Of the 122 FFQ line items (disaggregated into 350 foods), 83% had sufficient carbohydrate (>5 g/serving) for receipt of GI and GL values. The foods on the FFQ food list with the highest GL were fried breads, potatoes, pastries, pasta, and soft drinks. The fiber content of foods had very little influence on calculated GI or GL estimates. The augmentation of this FFQ database with GI and GL values will enable etiologic investigations of GI and GL with numerous disease outcomes in the WHI and other epidemiologic studies that utilize this FFQ.