Dietary Fiber Intake and Risk of Advanced and Aggressive Forms of Prostate Cancer: A Pooled Analysis of 15 Prospective Cohort Studies.

BACKGROUND: Evidence of an association between dietary fiber intake and risk of advanced and aggressive forms of prostate cancer (PC) and PC mortality is limited. OBJECTIVE: To examine associations between intakes of dietary fiber overall and by food source and risk of advanced and aggressive forms of PC. DESIGN: Pooled analysis of the primary data in 15 cohorts in three continents. Baseline dietary fiber intake was assessed using a validated food frequency questionnaire or diet history in each study. PARTICIPANTS/SETTING: 842,149 men were followed for up to 9-22 years between 1985-2009 across studies. MAIN OUTCOME MEASURES: The primary outcome measures were advanced (stage T4, N1, or M1 or PC mortality), advanced restricted (excluded men with missing stage and those with localized PC who died of PC), high grade (Gleason score ≥8 or poorly differentiated/undifferentiated) PC, and PC mortality. STATISTICAL ANALYSIS: Study-specific multivariable hazard ratios (MVHR) were calculated using Cox proportional hazards regression and pooled using random effects models. RESULTS: Intake of dietary fiber overall, from fruits, and from vegetables was not associated with risk of advanced (n=4,863), advanced restricted (n=2,978), or high-grade PC (n=9,673) or PC mortality (n=3,097). Dietary fiber intake from grains was inversely associated with advanced PC (MVHR comparing the highest vs. lowest quintile=0.84, 95% confidence interval [CI] 0.76-0.93), advanced restricted PC (MVHR=0.85, 95%CI 0.74-0.97), and PC mortality (MVHR=0.78, 95%CI 0.68-0.89); statistically significant trends were noted for each of these associations (p≤0.03), while a null association was observed for high grade PC for the same comparison (MVHR=1.00, 95%CI 0.93-1.07). The comparable results were 1.06 (95%CI 1.01-1.10, p-value, test for trend=0.002) for localized (n=35,199) and 1.05 (95%CI 0.99-1.11, , p-value, test for trend=0.04) for low/intermediate grade (n=34,366) PC. CONCLUSIONS: Weak nonsignificant associations were observed between total dietary fiber intake and risk of advanced forms of PC, high grade PC, and PC mortality. High dietary fiber intake from grains was associated with a modestly lower risk of advanced forms of PC and PC mortality.

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.

The Use of Three-Dimensional Images and Food Descriptions from a Smartphone Device Is Feasible and Accurate for Dietary Assessment.

Technology-assisted dietary assessment has the potential to improve the accuracy of self-reported dietary intake. This study evaluates MealScan3D (MS3D), a mobile device-based food recording system, which uses three-dimensional images to obtain food volumes and an application to capture algorithm-driven food intake data. Participants (n = 179) were randomly assigned and trained to record three meals using either MS3D or a written food record (WFR). Generous amounts of standardized meals were provided, and participants self-selected portions for each food. The weights of provided and uneaten/leftover foods were used to determine true intake. For total energy intake (three meals combined), validity (Pearson correlation) was significantly higher for MS3D vs. the WFR (p < 0.001); when interpreted as the percentage of variance in energy intake explained, MS3D explained 84.6% of true variance, a 25.3% absolute and 42.6% relative increase over the 59.3% explained by the WFR. For 9 of 15 individual foods, the Pearson correlations between true and reported portion size estimates were significantly larger for MS3D than the WFR. Bias was smaller (intercepts were closer to the means) for 9 of 15 foods and the regression coefficients for 10 of 15 foods were significantly closer to 1.0 in the MS3D arm. MS3D is feasible for dietary assessment and may provide improvements in accuracy compared to WFRs.

Development and validation of age-specific predictive equations for total energy expenditure and physical activity levels for older adults.

BACKGROUND: Predicting energy requirements for older adults is compromised by the underpinning data being extrapolated from younger adults. OBJECTIVES: To generate and validate new total energy expenditure (TEE) predictive equations specifically for older adults using readily available measures (age, weight, height) and to generate and test new physical activity level (PAL) values derived from 1) reference method of indirect calorimetry and 2) predictive equations in adults aged ≥65 y. METHODS: TEE derived from "gold standard" methods from n = 1657 (n = 1019 females, age range 65-90 y), was used to generate PAL values. PAL ranged 1.28-2.05 for males and 1.26-2.06 for females. Physical activity (PA) coefficients were also estimated and categorized (inactive to very active) from population means. Nonlinear regression was used to develop prediction equations for estimating TEE. Double cross-validation in a randomized, sex-stratified, age-matched 50:50 split, and leave one out cross-validation were performed. Comparisons were made with existing equations. RESULTS: Equations predicting TEE using the Institute of Medicine method are as follows: For males, TEE = -5680.17 - 17.50 × age (years) + PA coefficient × (6.96 × weight [kilograms] + 44.21 × height [centimeters]) + 1.13 × resting metabolic rate (RMR) (kilojoule/day). For females, TEE = -5290.72 - 8.38 × age (years) + PA coefficient × (9.77 × weight [kilograms] + 41.51 × height [centimeters]) + 1.05 × RMR (kilojoule/day), where PA coefficient values range from 1 (inactive) to 1.51 (highly active) in males and 1 to 1.44 in females respectively. Predictive performance for TEE from anthropometric variables and population mean PA was moderate with limits of agreement approximately ±30%. This improved to ±20% if PA was adjusted for activity category (inactive, low active, active, and very active). Where RMR was included as a predictor variable, the performance improved further to ±10% with a median absolute prediction error of approximately 4%. CONCLUSIONS: These new TEE prediction equations require only simple anthropometric data and are accurate and reproducible at a group level while performing better than existing equations. Substantial individual variability in PAL in older adults is the major source of variation when applied at an individual level.

The Prostate Cancer Active Lifestyle Study (PALS): A randomized controlled trial of diet and exercise in overweight and obese men on active surveillance.

BACKGROUND: Active surveillance (AS) is increasingly used to monitor patients with lower risk prostate cancer (PCa). The Prostate Cancer Active Lifestyle Study (PALS) was a randomized controlled trial to determine whether weight loss improves obesity biomarkers on the causal pathway to progression in patients with PCa on AS. METHODS: Overweight/obese men (body mass index >25 kg/m2 ) diagnosed with PCa who elected AS were recruited. The intervention was a 6-month, individually delivered, structured diet and exercise program adapted from the Diabetes Prevention Program with a 7% weight loss goal from baseline. Control participants attended one session reviewing the US Dietary and Physical Activity Guidelines. The primary outcome was change in glucose regulation from baseline to the end of the 6-month intervention, which was measured by fasting plasma glucose, C-peptide, insulin, insulin-like growth factor 1, insulin-like growth factor binding protein-3, adiponectin, and homeostatic model assessment for insulin resistance. RESULTS: Among 117 men who were randomized, 100 completed the trial. The mean percentage weight loss was 7.1% and 1.8% in the intervention and control arms, respectively (adjusted between-group mean difference, -6.0 kg; 95% confidence interval, -8.0, -4.0). Mean percentage changes from baseline for insulin, C-peptide, and homeostatic model assessment for insulin resistance in the intervention arm were -23%, -16%, and -25%, respectively, compared with +6.9%, +7.5%, and +6.4%, respectively, in the control arm (all p for intervention effects ≤ .003). No significant between-arm differences were detected for the other biomarkers. CONCLUSIONS: Overweight/obese men with PCa undergoing AS who participated in a lifestyle-based weight loss intervention successfully met weight loss goals with this reproducible lifestyle intervention and experienced improvements in glucose-regulation biomarkers associated with PCa progression.

Traditional Mexican dietary pattern and cancer risk among women of Mexican descent.

PURPOSE: To examine the association of a traditional Mexican diet score with risk of total, breast, and colorectal cancer among women of Mexican ethnic descent in the Women's Health Initiative (WHI). METHODS: Participants were WHI enrollees who self-identified as being of Mexican descent. Data from food frequency questionnaires self-administered at study baseline were used to calculate the MexD score, with higher scores indicating greater adherence to an a priori-defined traditional Mexican diet (high in dietary fiber, vegetables, and legumes). Incident cancers were self-reported by participants from 1993 to 2020 and adjudicated by trained physicians. We used multivariable-adjusted Cox proportional hazards models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Among 2,343 Mexican descent women (median baseline age: 59 years), a total of 270 cancers (88 breast, 37 colorectal) occurred during a mean follow-up of 14.4 years. The highest tertile of MexD score was associated with a lower risk of all-cancer incidence (HR: 0.67; 95% CI 0.49-0.91; p-trend: 0.01) and colorectal cancer (HR: 0.38; 95% CI 0.14-0.998; p-trend < 0.05), with each unit increase in the MexD score associated with a 6% lower risk of all-cancer incidence (HR: 0.94; 95% CI 0.88-0.99). There was no statistically significant association with risk of breast cancer. CONCLUSION: Consumption of a traditional Mexican diet was associated with a significantly lower risk of all-cancer incidence and colorectal cancer. Confirmation of these findings in future studies is important, given the prevalence of colorectal cancer and a growing U.S. population of women of Mexican descent.

Genome-Wide Interaction Analysis With DASH Diet Score Identified Novel Loci for Systolic Blood Pressure.

BACKGROUND: The Dietary Approaches to Stop Hypertension (DASH) diet score lowers blood pressure (BP). We examined interactions between genotype and the DASH diet score in relation to systolic BP. METHODS: We analyzed up to 9 420 585 single nucleotide polymorphisms in up to 127 282 individuals of 6 population groups (91% of European population) from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (n=35 660) and UK Biobank (n=91 622) and performed European population-specific and cross-population meta-analyses. RESULTS: We identified 3 loci in European-specific analyses and an additional 4 loci in cross-population analyses at Pinteraction<5e-8. We observed a consistent interaction between rs117878928 at 15q25.1 (minor allele frequency, 0.03) and the DASH diet score (Pinteraction=4e-8; P for heterogeneity, 0.35) in European population, where the interaction effect size was 0.42±0.09 mm Hg (Pinteraction=9.4e-7) and 0.20±0.06 mm Hg (Pinteraction=0.001) in Cohorts for Heart and Aging Research in Genomic Epidemiology and the UK Biobank, respectively. The 1 Mb region surrounding rs117878928 was enriched with cis-expression quantitative trait loci (eQTL) variants (P=4e-273) and cis-DNA methylation quantitative trait loci variants (P=1e-300). Although the closest gene for rs117878928 is MTHFS, the highest narrow sense heritability accounted by single nucleotide polymorphisms potentially interacting with the DASH diet score in this locus was for gene ST20 at 15q25.1. CONCLUSIONS: We demonstrated gene-DASH diet score interaction effects on systolic BP in several loci. Studies with larger diverse populations are needed to validate our findings.

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.

Genome-Wide Interaction Analysis with DASH Diet Score Identified Novel Loci for Systolic Blood Pressure.

Objective: We examined interactions between genotype and a Dietary Approaches to Stop Hypertension (DASH) diet score in relation to systolic blood pressure (SBP). Methods: We analyzed up to 9,420,585 biallelic imputed single nucleotide polymorphisms (SNPs) in up to 127,282 individuals of six population groups (91% of European population) from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (CHARGE; n=35,660) and UK Biobank (n=91,622) and performed European population-specific and cross-population meta-analyses. Results: We identified three loci in European-specific analyses and an additional four loci in cross-population analyses at P for interaction < 5e-8. We observed a consistent interaction between rs117878928 at 15q25.1 (minor allele frequency = 0.03) and the DASH diet score (P for interaction = 4e-8; P for heterogeneity = 0.35) in European population, where the interaction effect size was 0.42±0.09 mm Hg (P for interaction = 9.4e-7) and 0.20±0.06 mm Hg (P for interaction = 0.001) in CHARGE and the UK Biobank, respectively. The 1 Mb region surrounding rs117878928 was enriched with cis-expression quantitative trait loci (eQTL) variants (P = 4e-273) and cis-DNA methylation quantitative trait loci (mQTL) variants (P = 1e-300). While the closest gene for rs117878928 is MTHFS, the highest narrow sense heritability accounted by SNPs potentially interacting with the DASH diet score in this locus was for gene ST20 at 15q25.1. Conclusion: We demonstrated gene-DASH diet score interaction effects on SBP in several loci. Studies with larger diverse populations are needed to validate our findings.

Randomized Trial of Exercise and Nutrition on Chemotherapy Completion and Pathologic Complete Response in Women With Breast Cancer: The Lifestyle, Exercise, and Nutrition Early After Diagnosis Study.

PURPOSE: Successful completion of chemotherapy is critical to improve breast cancer outcomes. Relative dose intensity (RDI), defined as the ratio of chemotherapy delivered to prescribed, is a measure of chemotherapy completion and is associated with cancer mortality. The effect of exercise and eating a healthy diet on RDI is unknown. We conducted a randomized trial of an exercise and nutrition intervention on RDI and pathologic complete response (pCR) in women diagnosed with breast cancer initiating chemotherapy. METHODS: One hundred seventy-three women with stage I-III breast cancer were randomly assigned to usual care (UC; n = 86) or a home-based exercise and nutrition intervention with counseling sessions delivered by oncology-certified registered dietitians (n = 87). Chemotherapy dose adjustments and delays and pCR were abstracted from electronic medical records. T-tests and chi-square tests were used to examine the effect of the intervention versus UC on RDI and pCR. RESULTS: Participants randomly assigned to intervention had greater improvements in exercise and diet quality compared with UC (P < .05). RDI was 92.9% ± 12.1% and 93.6% ± 11.1% for intervention and UC, respectively (P = .69); the proportion of patients in the intervention versus UC who achieved ≥85% RDI was 81% and 85%, respectively (P = .44). The proportion of patients who had at least one dose reduction and/or delay was 38% intervention and 36% UC (P = .80). Among 72 women who received neoadjuvant chemotherapy, women randomly assigned to intervention were more likely to have a pCR than those randomly assigned to UC (53% v 28%; P = .037). CONCLUSION: Although a diet and exercise intervention did not affect RDI, the intervention was associated with a higher pCR in patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative and triple-negative breast cancer undergoing neoadjuvant chemotherapy.

Association of dietary insulinemic and inflammatory potential with risk of liver cancer and chronic liver disease mortality in postmenopausal women: a prospective cohort study.

BACKGROUND: Low diet quality, diabetes, and chronic inflammation are risk factors of liver cancer and chronic liver disease (CLD), but the extent to which insulinemic and inflammatory diets are independently associated with risk of liver cancer and CLD mortality is unknown. METHODS: We conducted a prospective cohort analysis among 78,356 postmenopausal women in the Women's Health Initiative Observational Study. Two validated dietary indices, the empirical dietary index for hyperinsulinemia (EDIH) and the empirical dietary inflammation pattern (EDIP), were estimated from a food-frequency questionnaire. Incident cases of liver cancer and CLD mortality were adjudicated via review of medical records and linkage to National Death Index. Multivariable hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using Cox proportional hazards models, adjusted for age, diabetes, body mass index, and other covariates. RESULTS: During a median 22.1 y of follow-up, we documented 176 primary liver cancer cases and 156 CLD mortality cases. EDIH was positively associated with incident liver cancer (HRQuartile 4 vs. Quartile 1 = 1.68; 95% CI: 1.00, 2.83; P-trend = 0.05) and CLD mortality (HRQ4 vs. Q1 = 2.28; 95% CI: 1.25, 4.15; P-trend = 0.02) in the multivariable model. EDIP was also positively associated with liver cancer (HRQ4 vs. Q1 = 1.88; 95% CI: 1.17, 3.03; P-trend = 0.009) and CLD mortality (HRQ4 vs. Q1 = 1.85; 95% CI: 1.09, 3.15; P-trend = 0.007). Estimates remained significant and robust in sensitivity analyses. Further analyses indicated positive associations for refined grains, processed meat, sugary beverages, and eggs, and inverse associations for coffee/tea and poultry. CONCLUSIONS: Dietary insulinemic and inflammatory potentials were independently associated with higher risk of liver cancer and CLD mortality in U.S. postmenopausal women. These findings suggest a potential role for diet modification to reduce risk of liver cancer and CLD.

Predicting All-Cause Mortality in Women With and Without Breast Cancer Using the Schonberg Index: A Women's Health Initiative Study.

BACKGROUND: When treating older women with breast cancer, life expectancy is an important consideration. ASCO recommends calculating 10-year mortality probabilities to inform treatment decisions. One useful tool is the Schonberg index, which predicts risk-based all-cause 10-year mortality. We investigated the use of this index in women aged ≥65 years with breast cancer in the Women's Health Initiative (WHI). METHODS: We calculated 10-year mortality risk scores for 2,549 WHI participants with breast cancer ("cases") and 2,549 age-matched breast cancer-free participants ("controls") using Schonberg index risk scoring. Risk scores were grouped into quintiles for comparisons. Risk-stratified observed mortality rates and 95% confidence intervals were compared across cases and controls. Observed 10-year mortality rates in cases and controls were also compared with Schonberg index-based predicted 10-year mortality rates. RESULTS: Compared with controls, cases were more often white (P=.005), had higher income and education levels (P<.001 for both), more often lived with their husband/partner (P<.001), scored higher on subjective health/happiness (P<.001), and needed less assistance in activities of daily living (P<.001). Participants with breast cancer had similar risk-stratified 10-year mortality rates compared with controls (34% vs 33%, respectively). Stratified results showed that cases had slightly higher mortality rates than controls in the lowest risk quintile and lower mortality rates in the 2 highest risk quintiles. Observed mortality rates in cases and controls were similar to Schonberg index-predicted mortality, with model c-indexes of 0.71 and 0.76, respectively. CONCLUSIONS: Among women aged ≥65 years with incident breast cancer, the Schonberg index-based risk-stratified 10-year mortality rates were similar to those in women without breast cancer, demonstrating a similar performance of the index among both populations. Along with other health measures, prognostic indexes can help predict survival among older women with breast cancer and support geriatric oncology guidelines that promote using life expectancy calculation tools for shared decision-making.

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.

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.

Total daily energy expenditure has declined over the past three decades due to declining basal expenditure, not reduced activity expenditure.

Obesity is caused by a prolonged positive energy balance1,2. Whether reduced energy expenditure stemming from reduced activity levels contributes is debated3,4. Here we show that in both sexes, total energy expenditure (TEE) adjusted for body composition and age declined since the late 1980s, while adjusted activity energy expenditure increased over time. We use the International Atomic Energy Agency Doubly Labelled Water database on energy expenditure of adults in the United States and Europe (n = 4,799) to explore patterns in total (TEE: n = 4,799), basal (BEE: n = 1,432) and physical activity energy expenditure (n = 1,432) over time. In males, adjusted BEE decreased significantly, but in females this did not reach significance. A larger dataset of basal metabolic rate (equivalent to BEE) measurements of 9,912 adults across 163 studies spanning 100 years replicates the decline in BEE in both sexes. We conclude that increasing obesity in the United States/Europe has probably not been fuelled by reduced physical activity leading to lowered TEE. We identify here a decline in adjusted BEE as a previously unrecognized factor.

Development and validation of new predictive equations for the resting metabolic rate of older adults aged ≥65 y.

BACKGROUND: The aging process alters the resting metabolic rate (RMR), but it still accounts for 50%-70% of the total energy needs. The rising proportion of older adults, especially those over 80 y of age, underpins the need for a simple, rapid method to estimate the energy needs of older adults. OBJECTIVES: This research aimed to generate and validate new RMR equations specifically for older adults and to report their performance and accuracy. METHODS: Data were sourced to form an international dataset of adults aged ≥65 y (n = 1686, 38.5% male) where RMR was measured using the reference method of indirect calorimetry. Multiple regression was used to predict RMR from age (y), sex, weight (kg), and height (cm). Double cross-validation in a randomized, sex-stratified, age-matched 50:50 split and leave one out cross-validation were performed. The newly generated prediction equations were compared with the existing commonly used equations. RESULTS: The new prediction equation for males and females aged ≥65 y had an overall improved performance, albeit marginally, when compared with the existing equations. It is described as follows: RMR (kJ/d) = 31.524 × W (kg) + 25.851 × H (cm) - 24.432 × Age (y) + 486.268 × Sex (M = 1, F = 0) + 530.557. Equations stratified by age (65-79.9 y and >80 y) and sex are also provided. The newly created equation estimates RMR within a population mean prediction bias of ∼50 kJ/d (∼1%) for those aged ≥65 y. Accuracy was reduced in adults aged ≥80 y (∼100 kJ/d, ∼2%) but was still within the clinically acceptable range for both males and females. Limits of agreement indicated a poorer performance at an individual level with 1.96-SD limits of approximately ±25%. CONCLUSIONS: The new equations, using simple measures of weight, height, and age, improved the accuracy in the prediction of RMR in populations in clinical practice. However, no equation performs optimally at the individual level.

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.

Reliability estimates for assessing meal timing derived from longitudinal repeated 24-hour dietary recalls.

BACKGROUND: Regulating meal timing may have efficacy for improving metabolic health for preventing or managing chronic disease. However, the reliability of measuring meal timing with commonly used dietary assessment tools needs characterization prior to investigating meal timing and health outcomes in epidemiologic studies. OBJECTIVES: To evaluate the reliability of estimating meal timing parameters, including overnight fasting duration, the midpoint of overnight fasting time, the number of daily eating episodes, the period with the largest percentage of daily caloric intake, and late last eating episode (> 09:00 pm) from repeated 24-h dietary recalls (24HRs). METHODS: Intraclass correlation coefficients (ICC), Light's Kappa estimates, and 95% CIs were calculated from repeated 24HR administered in 3 epidemiologic studies: The United States-based Interactive Diet and Activity Tracking in AARP (IDATA) study (n = 996, 6 24HR collected over 12-mo), German EPIC-Potsdam Validation Study (European Prospective Investigation into Cancer and Nutrition Potsdam Germany cohort) (n = 134, 12 24HR collected over 12-mo) and EPIC-Potsdam BMBF-II Study (Federal Ministry of Education and Research, "Bundesministerium für Bildung und Forschung") (n = 725, 4 24HR collected over 36 mo). RESULTS: Measurement reliability of overnight fasting duration based on a single 24HR was "poor" in all studies [ICC range: 0.27; 95% CI: 0.23, 0.32 - 0.46; 95% CI: 0.43, 0.50]. Reliability was "moderate" with 3 24HR (ICC range: 0.53; 95% CI: 0.47, 0.58 in IDATA, 0.62; 95% CI: 0.52, 0.69 in the EPIC-Potsdam Validation Study, and 0.72; 95% CI: 0.70-0.75 in the EPIC-Potsdam BMBF-II Study). Results were similar for the midpoint of overnight fasting time and the number of eating episodes. Reliability of measuring late eating was "fair" in IDATA (Light's Kappa: 0.30; 95% CI: 0.21, 0.39) and "slight" in the EPIC-Potsdam Validation study and the EPIC-Potsdam BMBF-II study (Light's Kappa: 0.19; 95% CI: 0.15, 0.25 and 0.09; 95% CI: 0.06, 0.12, respectively). Reliability estimates differed by sex, BMI, weekday, and season of 24HR administration in some studies. CONCLUSIONS: Our results show that ≥ 3 24HR over a 1-3-y period are required for reliable estimates of meal timing variables.