Simultaneous association of total energy consumption and activity-related energy expenditure with risks of cardiovascular disease, cancer, and diabetes among postmenopausal women

Relevance of Cardiovascular Exercise in Cancer and Cancer Therapy-Related Cardiac Dysfunction

PURPOSE OF THE REVIEW

Cancer therapy-related cardiac dysfunction (CTRCD) has been identified as a threat to overall and cancer-related survival. Although aerobic exercise training (AET) has been shown to improve cardiorespiratory fitness (CRF), the relationship between specific exercise regimens and cancer survival, heart failure development, and reduction of CTRCD is unclear. In this review, we discuss the impact of AET on molecular pathways and the current literature of sports in the field of cardio-oncology.

RECENT FINDINGS

Cardio-oncological exercise trials have focused on variations of AET intensity by using moderate continuous and high intensity interval training, which are applicable, safe, and effective approaches to improve CRF. AET increases CRF, reduces cardiovascular morbidity and heart failure hospitalization and should thus be implemented as an adjunct to standard cancer therapy, although its long-term effect on CTRCD remains unknown. Despite modulating diverse molecular pathways, it remains unknown which exercise regimen, including variations of AET duration and frequency, is most suited to facilitate peripheral and central adaptations to exercise and improve survival in cancer patients.

Physiopathology and Treatment of Obesity and Overweight: A Proposal for a New Anorectic

The "new epidemic," as WHO calls obesity, is caused by overeating, which, having exceeded the body's actual needs, accumulates in the form of health-damaging fat deposits. Moving more and eating less is the main remedy, but eating belongs to vital instincts, which are beyond the control of reason. In this sense, eating is different from drinking and breathing because without food it is possible to survive for a few weeks, without water for a few days, without oxygen for a few minutes. The first part of this article provides an overview of obesity and its treatment, focusing on the new anorectic anticipated in the title. The second part focuses on compulsive obesity, typically represented by constitutional obesity and food addiction. The article concludes with a discussion of the pharmacological treatment of compulsive diseases, to which some forms of obesity belong.

Association between doubly labelled water-calibrated energy intake and objectively measured physical activity with mortality risk in older adults

BACKGROUND

Physical activity or biomarker-calibrated energy intake (EI) alone is associated with mortality in older adults; the interaction relationship between the combined use of both factors and mortality has not been examined. We evaluated the relationship between mortality and calibrated EI and step counts in older adults.

METHODS

This prospective study included 4,159 adults aged ≥65 years who participated in the Kyoto-Kameoka study in Japan and wore a triaxial accelerometer between 1 April and 15 November 2013. The calibrated EI was calculated based on a previously developed equation using EI biomarkers. The step count was obtained from the accelerometer ≥ 4 days. Participants were classified into the following four groups: low EI (LEI)/low step counts (LSC) group (EI: <2,400 kcal/day in men and <1,900 kcal/day in women; steps: <5,000 /day), n = 1,352; high EI (HEI)/LSC group (EI: ≥2,400 kcal/day in men and ≥1,900 kcal/day in women; steps: <5,000 /day), n = 1,586; LEI/high step counts (HSC) group (EI: <2,400 kcal/day in men and < 1,900 kcal/day in women; steps: ≥5,000 /day), n = 471; and HEI/HSC group (EI: ≥2,400 kcal/day in men and ≥1,900 kcal/day in women; steps: ≥5,000 /day), n = 750. Mortality-related data were collected until 30 November 2016. We performed a multivariable Cox proportional hazard analysis.

RESULTS

The median follow-up period was 3.38 years (14,046 person-years), and 111 mortalities were recorded. After adjusting for confounders, the HEI/HSC group had the lowest all-cause mortality rate compared to other groups (LEI/LSC: reference; HEI/LSC: hazard ratio [HR]: 0.71, 95% confidence interval [CI]: 0.41-1.23; LEI/HSC: HR: 0.59, 95% CI: 0.29-1.19; and HEI/HSC: HR: 0.10, 95% CI: 0.01-0.76). No significant interaction was observed between the calibrated EI and steps with mortality. The spline model showed that 35-42 kcal/100 steps/day of EI/100 steps was associated with the lowest mortality risk.

CONCLUSIONS

HR mortality risk was lowest at 35-42 kcal/100 steps/day, suggesting that very high (≥56 kcal) or low (<28 kcal) EI/100 steps are not inversely associated with mortality. Adherence to optimal EI and adequate physical activity may provide sufficient energy balance to explain the inverse association with mortality among older Japanese adults.

A Combination Study of Pre- and Clinical Trial: Seaweed Consumption Reduces Aging-Associated Muscle Loss!

Seaweed consumption in Asian food cultures may benefit longevity and age-related conditions like sarcopenia with aging. However, sarcopenia lacks a definitive treatment, and pharmaceutical options have limitations in efficacy and safety. Recent studies on aging female mice found that Ishige okamurae (IO), a brown algae, and its active compound diphloroethohydroxycarmalol improved sarcopenia. Further research is needed to understand the effects of seaweed consumption on sarcopenia in humans. This clinical trial divided participants into a test group (receiving 500 mg/kg IO supplementation, mean±SD; age 62.73±7.18 years, n=40) and a control group (age 63.10±7.06 years, n=40). Hazard analysis assessed vital signs and muscle strength improvement during the trial. Additionally, 12-month-old mice were oral-fed IO at different doses (50, 100, 200 mg/kg) for 6-weeks. Aging and muscle-wasting related markers were evaluated, including grip strength, body weight and compositions, serum-parameters, and molecular-changes. The clinical trial found no significant changes in toxicity-parameters between the groups (p<0.05) after 12-weeks of IO supplementation. The IO group exhibited a remarkable increase in lower-limb quadriceps muscle-strength compared to the control (p=0.002). Furthermore, IO treatment improved age-related decline in quadriceps strength in the subgroup; under 61-years-old (p=0.004), without significant differences in foot-dominancy between groups (p=0.171). In 12-month-old male mice, IO administration improved age-related deficiencies in grip strength (p>0.0001) and testosterone (p=0.0001). Muscular regeneration parameters, such as lean-mass (p>0.0001), inhibition of proteolysis (measured by changes in myogenin and atrogin-1 protein expressions), cross-sectional myofiber area (p>0.0001), number of satellite cells (p=0.0001), and increased mitochondrial oxidative phosphorylation complexes in muscle tissue indicative of mitochondrial biogenesis, were also improved by IO administration. This trial is the first to explore the positive association between consuming brown-algae IO and age-related decreases in muscle strength. IO treatment helps maintain muscle mass and delays muscle wasting during aging, suggesting it as a potent nutritional strategy to protect against aging-associated sarcopenia.

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.

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.

Doubly labelled water-calibrated energy intake associations with mortality risk among older adults

BACKGROUND

The body mass index (BMI) is closely related to mortality risk, and energy intake (EI) is essential for maintaining energy balance in weight control. However, self-reported EI has been shown to lead to a systematic underestimation. Total energy expenditure measured using the doubly labelled water (DLW) method is considered an objective biomarker of EI and the gold standard for its estimation in individuals with stable body weight. We aimed to examine the association between DLW-calibrated EI and BMI on overall mortality risk in older adults.

METHODS

A prospective cohort study was performed using data of 8051 (4267 women and 3784 men) Japanese older adults from the Kyoto-Kameoka Study in Japan. Calibrated EI was calculated from the estimated EI using a food frequency questionnaire and equation developed based on DLW. Participants were classified by quartiles based on their EI stratified by sex. BMI was calculated using self-reported height and body weight. Mortality data were collected between 30 July 2011 and 30 November 2016. Statistical analysis was performed using the multivariable-adjusted Cox proportional hazard model with a restricted cubic spline.

RESULTS

The 8051 participants' mean (standard deviation) age and BMI were 73.5 (6.1) years and 22.6 (3.0) kg/m2 , respectively. The mean (standard deviation) EI with and without calibration was 1909 (145) kcal/day and 1569 (358) kcal/day in women and 2383 (160) kcal/day and 1980 (515) kcal/day in men, respectively. During the median 4.75 years of follow-up (36 552 person-years), 661 deaths were recorded. In both women (hazard ratio [HR], 0.63; 95% confidence interval [CI] [0.41, 0.98]) and men (HR, 0.62; 95% CI [0.44, 0.87]), after adjusting for confounders, the top quartile as compared with the bottom calibrated EI quartile showed a negative association with risk of all-cause mortality. The lowest HR for all-cause mortality was 1900-2000 kcal/day in women and 2400-2600 kcal/day in men. However, after adjusting for BMI, no significant association was observed between the calibrated EI and the risk of death. These associations could not be confirmed in the uncalibrated EI. The HR for mortality was minimal at a BMI of 23 kg/m2 in both men and women, with or without adjustment for the calibrated EI.

CONCLUSIONS

Calibrated EI was negatively associated with mortality risk but not uncalibrated EI. This may be mediated by an increase in body weight over time. Caution is required when interpreting the association between EI and mortality risk without adjusting for self-reported measurement errors and outcomes.

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.

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.

Association of Dietary Pattern with Cardiovascular Risk Factors among Postmenopausal Women in Taiwan: A Cross-Sectional Study from 2001 to 2015

Unhealthy diet and inappropriate lifestyle contribute to an imbalance in cardiometabolic profiles among postmenopausal women. This research aimed to analyze the association between dietary pattern and changes in cardiovascular risk factors among postmenopausal Taiwanese women using binary logistic regression. This cross-sectional study involved 5689 postmenopausal Taiwanese women aged 45 years and above, and the data were obtained from Mei Jau Health Management Institution database between 2001 and 2015. The cardiovascular risk dietary pattern characterized by high intakes of processed food, rice/flour products, organ meat, and sauce was derived by reduced rank regression. Participants in the highest quartile of the cardiovascular risk dietary pattern were more likely to have high levels of systolic blood pressure (OR = 1.29, 95% CI 1.08-1.53), diastolic blood pressure (OR = 1.28, 95% CI 1.01-1.62), atherogenic index of plasma (OR = 1.26, 95% CI 1.06-1.49), triglycerides (OR = 1.38, 95% CI 1.17-1.62), and fasting blood glucose (Q3: OR = 1.45, 95% CI 1.07-1.97). However, this dietary pattern was not correlated with total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and C-reactive protein. Therefore, adherence to the cardiovascular risk dietary pattern increases the risk of having higher levels of blood pressure, triglycerides, fasting blood glucose in postmenopausal Taiwanese women.

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.

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.

Four-Day Food Record Macronutrient Intake, With and Without Biomarker Calibration, and Chronic Disease Risk in Postmenopausal Women

We recently evaluated associations of biomarker-calibrated protein intake, protein density, carbohydrate intake, and carbohydrate density with the incidence of cardiovascular disease, cancer, and diabetes among postmenopausal women in the Women's Health Initiative (1993-present, 40 US clinical centers). The biomarkers relied on serum and urine metabolomics profiles, and biomarker calibration used regression of biomarkers on food frequency questionnaires. Here we develop corresponding calibration equations using food records and dietary recalls. In addition, we use calibrated intakes based on food records in disease association estimation in a cohort subset (n = 29,294) having food records. In this analysis, more biomarker variation was explained by food records than by FFQs for absolute macronutrient intake, with 24-hour recalls being intermediate. However, the percentage of biomarker variation explained was similar for each assessment approach for macronutrient densities. Invasive breast cancer risk was related inversely to carbohydrate and protein densities using food records, in analyses that included (calibrated) total energy intake and body mass index. Corresponding analyses for absolute intakes did not differ from the null, nor did absolute or relative intakes associate significantly with colorectal cancer or coronary heart disease. These analyses do not suggest major advantages for food records or dietary recalls in comparison with less costly and logistically simpler food frequency questionnaires for these nutritional variables.

The association of predicted resting energy expenditure with risk of breast cancer among postmenopausal women in the Women's Health Initiative cohort

Obesity and obesity-related metabolic disorders, such as obesity and chronic inflammation, have been positively associated both with postmenopausal breast cancer and with resting energy expenditure (REE). However, there is limited epidemiological evidence on the associations between REE and risk of postmenopausal breast cancer. We used multivariable Cox proportional hazards models to examine the association between predicted REE (calculated using the Ikeda, Livingston and Mifflin equations) and risk of postmenopausal breast cancer overall and by subtypes, and by level of body fat) among 137,305 postmenopausal women in the Women's Health Initiative (WHI). All predicted REEs were positively associated with risk of invasive breast cancer (HRq5 vs q1: 1.69; 95% CI: 1.57-1.81, HR: 1.69; 95% CI: 1.57-1.82 and HR: 1.68; 95% CI: 1.56-1.80 for Ikeda, Livingston and Mifflin, respectively). These positive associations were observed irrespective of the hormone receptor subtype, grade and stage of the tumors, but were most pronounced for estrogen receptor positive/progesterone receptor positive tumors. After additional adjustment for BMI, the associations were mostly attenuated and remained statistically significant for most of the outcomes. We also observed an interaction between the predicted REEs and BMI, with the associations being somewhat stronger among normal weight and overweight women than among obese women (pinteractions <0.05). Our findings indicate that relatively high REE is associated with increased risk of invasive breast cancer among postmenopausal women (particularly for the obesity-related tumor subtypes), irrespective of the equation used. Further studies using more objective measures of REE are, however, needed to confirm our findings.

A review of research on the intersection between breast cancer and cardiovascular research in the Women's Health Initiative (WHI)

Both obesity and metabolic syndrome are linked to increased incidence of type 2 diabetes, cardiovascular disease (CVD), and cancers of the breast (post-menopausal), and other obesity-related cancers. Over the past 50 years, the worldwide prevalence of obesity and metabolic syndrome has increased, with a concomitant higher incidence of associated co-morbidities and mortality. The precise mechanism linking metabolic syndrome to increased cancer incidence is incompletely understood, however, individual components of metabolic syndrome have been linked to increased breast cancer incidence and worse survival. There is a bidirectional relationship between the risk of CVD and cancer due to a high burden of shared risk factors and higher rates of CVD among cancer survivors, which may be impacted by the pro-inflammatory microenvironment associated with metabolic syndrome and cancer-directed therapies. The Women's Health Initiative (WHI) is an excellent resource to study a dual relationship between cancer and CVD (cardio-oncology) with extensive information on risk factors and long-term outcomes. The purpose of this review is to provide an overview of research on cardio-oncology conducted utilizing WHI data with focus on studies evaluating both breast cancer and CVD including shared risk factors and outcomes after cancer. The review also includes results on other obesity related cancers which were included in the analyses of breast cancer, articles looking at cancer after heart disease (reverse cardio-oncology) and the role of Clonal Hematopoiesis of Indeterminate Potential (CHIP) as a shared risk factor between CVD and cancer. A summary of pertinent WHI literature helps to delineate the direction of future research evaluating the relationship between CVD and other cancer sites, and provides information on the opportunity for other novel analyses within the WHI.

Novel Application of Nutritional Biomarkers From a Controlled Feeding Study and an Observational Study to Characterization of Dietary Patterns in Postmenopausal Women

Dietary guidance emphasizes healthy dietary patterns, but supporting evidence comes from self-reported dietary data, which are prone to measurement error. We explored whether nutritional biomarkers from the Women's Health Initiative Nutrition and Physical Activity Assessment Study Feeding Study (NPAAS-FS) (n = 153; 2010-2014) and the Women's Health Initiative Nutrition and Physical Activity Assessment Study Observational Study (NPAAS-OS) (n = 450; 2006-2009) could identify biomarker signatures of dietary patterns for development of corresponding regression calibration equations to help mitigate measurement error. Fasting blood samples were assayed for a specific panel of vitamins, carotenoids, and phospholipid fatty acids; 24-hour urine samples were assayed for nitrogen, sodium, and potassium levels. Intake records from the NPAAS-FS were used to calculate Healthy Eating Index 2010 (HEI-2010), Alternative Healthy Eating Index 2010 (AHEI-2010), alternative Mediterranean diet (aMED), and Dietary Approaches to Stop Hypertension (DASH) scores. Scores were regressed on blood and urine nutritional measures for discovery of dietary pattern biomarkers using a cross-validated model R2 ≥ 36% criterion (stage 1). Next, stepwise models (P ≤ 0.10 for entry/removal) using NPAAS-OS data were used to regress stage 1 dietary pattern biomarkers on NPAAS-OS self-reported dietary pattern scores using a food frequency questionnaire, a 4-day food record, and a 24-hour recall (stage 2). HEI-2010 and aMED analyses met the cross-validated R2 ≥ 36% criterion in stage 1, while AHEI-2010 and DASH analyses did not. The R2 values for HEI-2010 stage 2 calibration equations were as follows: food frequency questionnaire, 63.5%; 4-day food record, 83.1%; and 24-hour recall, 77.8%. Stage 2 aMED R2 values were 34.9%-46.8%. Dietary pattern biomarkers have potential for calibrating self-reports to enhance studies of diet-disease associations.

NUQUEST-NUtrition QUality Evaluation Strengthening Tools: development of tools for the evaluation of risk of bias in nutrition studies

BACKGROUND

Dietary exposure assessments are a critical issue in evaluating human nutrition studies; however, nutrition-specific criteria are not consistently included in existing bias assessment tools.

OBJECTIVES

Our objective was to develop a set of risk of bias (RoB) tools that integrated nutrition-specific criteria into validated generic assessment tools to address RoB issues, including those specific to dietary exposure assessment.

METHODS

The Nutrition QUality Evaluation Strengthening Tools (NUQUEST) development and validation process included 8 steps. The first steps identified 1) a development strategy; 2) generic assessment tools with demonstrated validity; and 3) nutrition-specific appraisal issues. This was followed by 4) generation of nutrition-specific items and 5) development of guidance to aid users of NUQUEST. The final steps used established ratings of selected studies and feedback from independent raters to 6) assess reliability and validity; 7) assess formatting and usability; and 8) finalize NUQUEST.

RESULTS

NUQUEST is based on the Scottish Intercollegiate Guidelines Network checklists for randomized controlled trials, cohort studies, and case-control studies. Using a purposive sample of 45 studies representing the 3 study designs, interrater reliability was high (Cohen's κ: 0.73; 95% CI: 0.52, 0.93) across all tools and at least moderate for individual tools (range: 0.57-1.00). The use of a worksheet improved usability and consistency of overall interrater agreement across all study designs (40% without worksheet, 80%-100% with worksheet). When compared to published ratings, NUQUEST ratings for evaluated studies demonstrated high concurrent validity (93% perfect or near-perfect agreement). Where there was disagreement, the nutrition-specific component was a contributing factor in discerning exposure methodological issues.

CONCLUSIONS

NUQUEST integrates nutrition-specific criteria with generic criteria from assessment tools with demonstrated reliability and validity. NUQUEST represents a consistent and transparent approach for evaluating RoB issues related to dietary exposure assessment commonly encountered in human nutrition studies.

Evaluation of potential metabolomic-based biomarkers of protein, carbohydrate and fat intakes using a controlled feeding study

PURPOSE

Objective biomarkers of dietary exposure are needed to establish reliable diet-disease associations. Unfortunately, robust biomarkers of macronutrient intakes are scarce. We aimed to assess the utility of serum, 24-h urine and spot urine high-dimensional metabolites for the development of biomarkers of daily intake of total energy, protein, carbohydrate and fat, and the percent of energy from these macronutrients (%E).

METHODS

A 2-week controlled feeding study mimicking the participants' habitual diets was conducted among 153 postmenopausal women from the Women's Health Initiative (WHI). Fasting serum metabolomic profiles were analyzed using a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for aqueous metabolites and a direct-injection-based quantitative lipidomics platform. Urinary metabolites were analyzed using ¹H nuclear magnetic resonance (NMR) spectroscopy at 800 MHz and by untargeted gas chromatography-mass spectrometry (GC-MS). Variable selection was performed to build prediction models for each dietary variable.

RESULTS

The highest cross-validated multiple correlation coefficients (CV-R²) for protein intake (%E) and carbohydrate intake (%E) using metabolites only were 36.3 and 37.1%, respectively. With the addition of established dietary biomarkers (doubly labeled water for energy and urinary nitrogen for protein), the CV-R² reached 55.5% for energy (kcal/d), 52.0 and 45.0% for protein (g/d, %E), 55.9 and 37.0% for carbohydrate (g/d, %E).

CONCLUSION

Selected panels of serum and urine metabolites, without the inclusion of doubly labeled water and urinary nitrogen biomarkers, give a reliable and robust prediction of daily intake of energy from protein and carbohydrate.

Biomarker-Calibrated Macronutrient Intake and Chronic Disease Risk among Postmenopausal Women

BACKGROUND

Knowledge about macronutrient intake and chronic disease risk has been limited by the absence of objective macronutrient measures. Recently, we proposed novel biomarkers for protein, protein density, carbohydrate, and carbohydrate density, using established biomarkers and serum and urine metabolomics profiles in a human feeding study.

OBJECTIVES

We aimed to use these biomarkers to develop calibration equations for macronutrient variables using dietary self-reports and personal characteristics and to study the association between biomarker-calibrated intake estimates and cardiovascular disease, cancer, and diabetes risk in Women's Health Initiative (WHI) cohorts.

METHODS

Prospective disease association analyses are based on WHI cohorts of postmenopausal US women aged 50-79 y when enrolled at 40 US clinical centers (n = 81,954). We used biomarker intake values in a WHI nutritional biomarker study (n = 436) to develop calibration equations for each macronutrient variable, leading to calibrated macronutrient intake estimates throughout WHI cohorts. We then examined the association of these intakes with chronic disease incidence over a 20-y (median) follow-up period using HR regression methods.

RESULTS

In analyses that included doubly labeled water-calibrated total energy, HRs for cardiovascular diseases and cancers were mostly unrelated to calibrated protein density. However, many were inversely related to carbohydrate density, with HRs (95% CIs) for a 20% increment in carbohydrate density of 0.81 (0.69, 0.95) and 0.83 (0.74, 0.93), respectively, for primary outcomes of coronary heart disease and breast cancer, as well as 0.74 (0.60, 0.91) and 0.87 (0.81, 0.93) for secondary outcomes of heart failure and total invasive cancer. Corresponding HRs (95% CIs) for type 2 diabetes incidence in relation to protein density and carbohydrate density were 1.17 (1.09, 1.75) and 0.73 (0.66, 0.80), respectively.

CONCLUSIONS

At specific energy intake, a diet high in carbohydrate density is associated with substantially reduced risk of major chronic diseases in a population of US postmenopausal women. This trial was registered at clinicaltrials.gov as NCT00000611.

Nutritional epidemiology and the Women's Health Initiative: a review

The dietary modification (DM) clinical trial, within the Women's Health Initiative (WHI), studied a low-fat dietary pattern intervention that included guidance to increase vegetables, fruit, and grains. This study was motivated in part from uncertainty about the reliability of observational studies examining the association between dietary fat and chronic disease risk by using self-reported dietary data. In addition to this large trial, which had breast and colorectal cancer as its primary outcomes, a substantial biomarker research effort was initiated midway in the WHI program to contribute to nutritional epidemiology research more broadly. Here we review and update findings from the DM trial and from the WHI nutritional biomarker studies and examine implications for future nutritional epidemiology research. The WHI included the randomized controlled DM trial (n = 48,835) and a prospective cohort observational (OS) study (n = 93,676), both among postmenopausal US women, aged 50-79 y when enrolled during 1993-1998. Also reviewed is a nutrition and physical activity assessment study in a subset of 450 OS participants (2007-2009) and a related controlled feeding study among 153 WHI participants (2010-2014). Long-term follow-up in the DM trial provides evidence for intervention-related reductions in breast cancer mortality, diabetes requiring insulin, and coronary artery disease in the subset of normotensive healthy women, without observed adverse effects or changes in all-cause mortality. Studies of intake biomarkers, and of biomarker-calibrated intake, suggest important associations of total energy intake and macronutrient dietary composition with the risk for major chronic diseases among postmenopausal women. Collectively these studies argue for a nutrition epidemiology research agenda that includes major efforts in nutritional biomarker development, and in the application of biomarkers combined with self-reported dietary data in disease association analyses. We expect such efforts to yield novel disease association findings and to inform disease prevention approaches for potential testing in dietary intervention trials. This trial was registered at clinicaltrials.gov as NCT00000611.

Physical activity energy expenditure and fat-free mass: relationship with metabolic syndrome in overweight or obese postmenopausal women

Menopause transition is associated with detrimental changes in physical activity, body composition, and metabolic profile. Although physical activity energy expenditure (PAEE) is inversely associated with metabolic syndrome (MetS) in individuals at higher risk of cardiovascular disease, the association is unknown in low-risk individuals. The aim of the study was to investigate the association between PAEE and MetS (prevalence and severity) in inactive overweight or obese postmenopausal women with a low Framingham Risk Score (<10%). Cross-sectional data of 126 participants were divided into quartiles based on PAEE (Quartile (Q)1 = lowest PAEE) while fat-free mass (FFM) and fat mass were measured by dual-energy X-ray absorptiometry. MetS prevalence was significantly different between Q1 and Q4 (37.9% vs 13.3%, p = 0.03). After controlling for potential confounders, MetS severity was negatively associated with PAEE (B = -0.057, p < 0.01) and positively with FFM (B = 0.038, p < 0.001). Moderation analyses indicated that a greater FFM exacerbated the association between PAEE and MetS severity in Q1 and Q2 (PAEE × FFM; B = -0.004; p = 0.1). Our results suggest that displaying a low FRS and lower PAEE increase MetS prevalence and severity. In addition, greater FFM interacts with lower PAEE to worsens MetS severity, while higher PAEE lessened this effect. Novelty: Inactive individuals displaying higher daily PAEE also have a lower MetS prevalence. Greater FFM is associated with a worse MetS severity where a higher PAEE mitigated this deleterious effect in our cohort.

The Carbon Isotope Ratios of Serum Amino Acids in Combination with Participant Characteristics can be Used to Estimate Added Sugar Intake in a Controlled Feeding Study of US Postmenopausal Women

BACKGROUND

The carbon isotope ratio (CIR) is a proposed biomarker for added sugar (AS) intake in the United States; however, because the CIR is also associated with meat intake in most populations the need for specificity remains. The CIR of amino acids (AAs) has the potential to differentiate sugars from meat intakes, because essential AAs must derive from dietary protein whereas certain nonessential AAs can be synthesized from sugars.

OBJECTIVES

We tested whether serum CIR-AAs in combination with participant characteristics could meet a prespecified biomarker criterion for AS intake in the Nutrition and Physical Activity Assessment Study Feeding Study (NPAAS-FS) of the Women's Health Initiative, a population in which the whole-serum CIR was not associated with AS intake.

METHODS

Postmenopausal women (n = 145) from Seattle, WA, were provided with individualized diets that approximated their habitual food intakes for 2 wk. Dietary intakes from consumed foods were characterized over the feeding period using the Nutrition Data System for Research. The CIR of 7 AAs-Ala, Gly, Val, Leu, Ile, Pro, and Phe-were measured in fasting serum collected at the end of the 2-wk feeding period, using gas chromatography-combustion isotope ratio mass spectrometry. Biomarker models were evaluated using regression R2 ≥ 0.36 as a major biomarker criterion, based on the benchmark R2 values of well-established recovery biomarkers in the NPAAS-FS.

RESULTS

AS intake was associated with CIR-Ala (ρ = 0.32; P < 0.0001). A model of AS intake based on CIR-Ala, CIR-Gly, CIR-Ile, smoking, leisure physical activity, and body weight met the biomarker criterion (R2 = 0.37). Biomarker-estimated AS intake was not associated with meat or animal protein intake.

CONCLUSIONS

Results support serum CIR-AAs in combination with participant characteristics as potential biomarkers of AS intake in US populations, including those with low AS intake.The Women's Health Initiative is registered at clinicaltrials.gov (NCT00000611).

Can dietary self-reports usefully complement blood concentrations for estimation of micronutrient intake and chronic disease associations?

BACKGROUND

We recently presented associations between serum-based biomarkers of carotenoid and tocopherol intake and chronic disease risk in a Women's Health Initiative (WHI) Measurement Precision subcohort (n = 5488). Questions remain as to whether self-reported dietary data can usefully augment such biomarkers or can be calibrated using biomarkers for reliable disease association estimation in larger WHI cohorts.

OBJECTIVES

The aims were to examine the potential of FFQ data to explain intake variation in a WHI Feeding Study and to compare association parameter estimates and their precision from studies based on biomarker-calibrated FFQ intake in larger WHI cohorts, with those previously presented.

METHODS

Serum-based intake measures were augmented by using FFQ data in a WHI Feeding Study (n = 153). Corresponding calibration equations were generated, both in a companion Nutritional Biomarker Study (n = 436) and in the previously mentioned subcohort (n = 5488), by regressing these intake measures on dietary data and participant characteristics, for α- and β-carotene, lutein plus zeaxanthin, and α-tocopherol. The supplemental value of FFQ data was considered by examining the fraction of feeding study intake variation explained by these regression models. Calibrated intake and disease association analyses were evaluated by comparisons with previously reported subcohort results.

RESULTS

The inclusion of FFQ data led to some increases in feeding study intake variation explained (total R2 of ∼50%). Calibrated intake estimates explained 25-75% of serum-based intake variation, whether developed using either of the 2 cohort subsamples. Related disease associations for micronutrients were precisely estimated in larger WHI cohorts (n = 76,691) but were often closer to the null compared with previously reported associations.

CONCLUSIONS

FFQ data may usefully augment blood concentrations in estimating the intake of carotenoids and tocopherols. Calibrated intake estimates using FFQ, dietary supplement, and participant characteristics only may require further justification to ensure reliable estimation of related disease associations.

Combining biomarker and food intake data: calibration equations for citrus intake

BACKGROUND

Measurement error associated with self-reported dietary intake is a well-documented issue. Combining biomarkers of food intake and dietary intake data is a high priority.

OBJECTIVES

The aim of this study was to develop calibration equations for food intake, illustrated with an application for citrus intake. Further, a simulation-based framework was developed to determine the portion of biomarker data needed for stable calibration equation estimation in large population studies.

METHODS

Calibration equations were developed using mean daily self-reported citrus intake (4-d semiweighed food diaries) and biomarker-derived intake (urinary proline betaine biomarker) data from participants (n = 565) as part of a cross-sectional study. Different functional specifications and biomarker transformations were tested to derive the optimal calibration equation specifications. The simulation study was developed using linear regression for the calibration equations. Stability in the calibration equation estimations was investigated for varying portions of biomarker and intake data "qualities."

RESULTS

With citrus intake, linear regression on nontransformed biomarker data resulted in the optimal calibration equation specifications and produced good-quality predicted intakes. The lowest mean squared error (14,354) corresponded to a linear regression model, defined with biomarker-derived estimates of intakes on the original scale. Using this model in a subpopulation without biomarker data resulted in an average mean ± SD citrus intake of 81 ± 66 g/d. The simulation study suggested that in large population studies, biomarker data on 20-30% of the subjects are required to guarantee stable estimation of calibration equations. This article is accompanied by a web application ("Bio-Intake"), which was developed to facilitate measurement error correction in self-reported mean daily citrus intake data.

CONCLUSIONS

Calibration equations proved to be a useful instrument to correct measurement error in self-reported food intake data. The simulation study demonstrated that the use of food intake biomarkers may be feasible and beneficial in the context of large population studies.

Low-Fat Dietary Pattern among Postmenopausal Women Influences Long-Term Cancer, Cardiovascular Disease, and Diabetes Outcomes

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.

Application of blood concentration biomarkers in nutritional epidemiology: example of carotenoid and tocopherol intake in relation to chronic disease risk

BACKGROUND

Biomarkers provide potential to objectively measure the intake of nutrients and foods, and thereby to strengthen nutritional epidemiology association studies. However, there are only a few established intake biomarkers, mostly based on recovery of nutrients or their metabolites in urine. Blood concentration measures provide a potential biomarker source for many additional nutritional variables, but their use in disease-association studies requires further development.

OBJECTIVE

The aim of this study was to apply recently proposed serum-based carotenoid and tocopherol intake biomarkers and to examine their association with the incidence of major cardiovascular diseases, cancers, and diabetes in a subset of Women's Health Initiative (WHI) cohorts.

METHODS

Serum concentrations of α- and β-carotene, lutein plus zeaxanthin (L + Z), and α-tocopherol were routinely measured at baseline in a subset of 5488 enrollees in WHI cohorts. Intake biomarkers for these 4 micronutrients, obtained by combining serum concentrations with participant characteristics, were recently proposed using a 153-woman feeding study within WHI. These biomarker equations are augmented here to include pertinent disease risk factors and are associated with subsequent chronic disease incidence in this WHI subset.

RESULTS

HRs for a doubling of micronutrient intake differed only moderately from the null for the outcomes considered. However, somewhat lower risks of specific cardiovascular outcomes, breast cancer, and diabetes were associated with a higher intake of α- and β-carotene, lower risk of diabetes was associated with higher L + Z intake, and elevated risks of certain cardiovascular outcomes were associated with a higher intake of α-tocopherol. These patterns remained following the exclusion of baseline users of dietary supplements.

CONCLUSIONS

Concentration biomarkers can be calculated from blood specimens obtained in large epidemiologic cohorts and applied directly in disease-association analyses, without relying on self-reported dietary data. Observed associations between carotenoid and tocopherol biomarkers and chronic disease risk could be usefully evaluated further using stored serum specimens on the entire WHI cohort. This study was registered at www.clinicaltrials.gov as NCT00000611.

Effect of physical exercise on cardiometabolic parameters in post-menopause: an integrative review

Abstract Objective: To identify the evidence available in literature which relates the practice of physical exercise to improvements in the cardiovascular and metabolic parameters of postmenopausal women. Method: A search was performed of works published between 2008 and 2018 included in the MEDLINE, BDENF, IBCS and LILACS databases. Of the 792 studies identified, 23 met the inclusion criteria. Results: Following analysis, the studies were separated into three categories. In the first category it was observed that physical exercise improved lipid metabolism, reduced abdominal circumference and promoted weight loss. The second category revealed that physical exercise reduced systolic blood pressure, prevented the development of arterial hypertension and reduced the release of sympathomimetic hormones. In the third category the studies indicated that physical exercise elevated the antioxidant mediators and reversed the oxidative stress involved in the inflammatory reactions present in cardiovascular diseases. Conclusion: The studies confirm the beneficial effects of physical exercise on the metabolic and cardiovascular parameters of postmenopausal women.

Associations of Biomarker-Calibrated Intake of Total Sugars With the Risk of Type 2 Diabetes and Cardiovascular Disease in the Women's Health Initiative Observational Study

The inconsistent findings from epidemiologic studies relating total sugars (TS) consumption to cardiovascular disease (CVD) or type 2 diabetes (T2D) risk may be partly due to measurement error in self-reported intake. Using regression calibration equations developed based on the predictive biomarker for TS and recovery biomarker for energy, we examined the association of TS with T2D and CVD risk, before and after dietary calibration, in 82,254 postmenopausal women participating in the Women's Health Initiative Observational Study. After up to 16 years of follow-up (1993-2010), 6,621 T2D and 5,802 CVD incident cases were identified. The hazard ratio for T2D per 20% increase in calibrated TS was 0.94 (95% confidence interval (CI): 0.77, 1.15) in multivariable energy substitution, and 1.00 (95% CI: 0.85, 1.18) in energy partition models. Multivariable hazard ratios for total CVD were 0.97 (95% CI: 0.87, 1.09) from energy substitution, and 0.91 (95% CI: 0.80, 1.04) from energy partition models. Uncalibrated TS generated a statistically significant inverse association with T2D and total CVD risk in multivariable energy substitution and energy partition models. The lack of conclusive findings from our calibrated analyses may be due to the low explanatory power of the calibration equations for TS, which could have led to incomplete deattenuation of the risk estimates.

Diet and Anthropometrics of Children With Inflammatory Bowel Disease: A Comparison With the General Population

BACKGROUND

There is a lack of knowledge regarding the diet of children with inflammatory bowel disease (IBD). Therefore, we investigated dietary intake in pediatric IBD compared to the general population and assessed anthropometrics and food avoidance.

METHODS

In this cross-sectional cohort study, patients younger than 18 years with IBD were included (2014-2017). Dietary intake (total energy, macro nutrients, food types) was assessed using a Food Frequency Questionnaire (FFQ) and compared with a matched reference population (n = 306).

RESULTS

There were 102 patients included (55% male, median age 15.0 years). Median height Z-score was -0.39 (interquartile range [IQR]: -1.17 to 0.26). Growth failure (height Z-scores<-1.64) was present in 11% of patients. Median BMI Z-score was 0.36 (IQR: -0.70 to 0.96). Acute malnutrition (weight-for-height Z-score<-2) was present in 3% of patients. Energy intake was lower in pediatric IBD compared to the reference population (mean kilojoule/day: 8286 vs 9794, P < 0.001). Protein intake did not differ, while fat intake was higher in pediatric IBD (mean gram/day: 101 vs 91, P < 0.001), with higher intake of vegetable oils/fats. Carbohydrate intake was lower in pediatric IBD (mean gram/day: 267 vs 305, P < 0.001), with lower intake of food types high in sugar. Food avoidance was reported in 53% of patients, with frequent avoidance of spicy (46%), high-fat food (30%), and dairy (30%).

CONCLUSIONS

The diet of children with IBD differs from the general pediatric population, with lower energy intake and high rates of food avoidance. Evaluation of the dietary intake alongside anthropometrics may be important to prevent nutrition deficiencies and promote health.

Understanding the Nature of Measurement Error When Estimating Energy Expenditure and Physical Activity via Physical Activity Recall

Background: The National Health and Nutrition Examination Survey physical activity questionnaire (PAQ) is used to estimate activity energy expenditure (AEE) and moderate to vigorous physical activity (MVPA). Bias and variance in estimates of AEE and MVPA from the PAQ have not been described, nor the impact of measurement error when utilizing the PAQ to predict biomarkers and categorize individuals.Methods: The PAQ was administered to 385 adults to estimate AEE (AEE:PAQ) and MVPA (MVPA:PAQ), while simultaneously measuring AEE with doubly labeled water (DLW; AEE:DLW) and MVPA with an accelerometer (MVPA:A).Results: Although AEE:PAQ [3.4 (2.2) MJ·d−1] was not significantly different from AEE:DLW [3.6 (1.6) MJ·d−1;P > .14], MVPA:PAQ [36.2 (24.4) min·d−1] was significantly higher than MVPA:A [8.0 (10.4) min·d−1;P < .0001]. AEE:PAQ regressed on AEE:DLW and MVPA:PAQ regressed on MVPA:A yielded not only significant positive relationships but also large residual variances. The relationships between AEE and MVPA, and 10 of the 12 biomarkers were underestimated by the PAQ. When compared with accelerometers, the PAQ overestimated the number of participants who met the Physical Activity Guidelines for Americans.Conclusions: Group-level bias in AEE:PAQ was small, but large for MVPA:PAQ. Poor within-participant estimates of AEE:PAQ and MVPA:PAQ lead to attenuated relationships with biomarkers and misclassifications of participants who met or who did not meet the Physical Activity Guidelines for Americans.

Determining Risk of Colorectal Cancer and Starting Age of Screening Based on Lifestyle, Environmental, and Genetic Factors

BACKGROUND & AIMS

Guidelines for initiating colorectal cancer (CRC) screening are based on family history but do not consider lifestyle, environmental, or genetic risk factors. We developed models to determine risk of CRC, based on lifestyle and environmental factors and genetic variants, and to identify an optimal age to begin screening.

METHODS

We collected data from 9748 CRC cases and 10,590 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colorectal Transdisciplinary study, from 1992 through 2005. Half of the participants were used to develop the risk determination model and the other half were used to evaluate the discriminatory accuracy (validation set). Models of CRC risk were created based on family history, 19 lifestyle and environmental factors (E-score), and 63 CRC-associated single-nucleotide polymorphisms identified in genome-wide association studies (G-score). We evaluated the discriminatory accuracy of the models by calculating area under the receiver operating characteristic curve values, adjusting for study, age, and endoscopy history for the validation set. We used the models to project the 10-year absolute risk of CRC for a given risk profile and recommend ages to begin screening in comparison to CRC risk for an average individual at 50 years of age, using external population incidence rates for non-Hispanic whites from the Surveillance, Epidemiology, and End Results program registry.

RESULTS

In our models, E-score and G-score each determined risk of CRC with greater accuracy than family history. A model that combined both scores and family history estimated CRC risk with an area under the receiver operating characteristic curve value of 0.63 (95% confidence interval, 0.62-0.64) for men and 0.62 (95% confidence interval, 0.61-0.63) for women; area under the receiver operating characteristic curve values based on only family history ranged from 0.53 to 0.54 and those based only E-score or G-score ranged from 0.59 to 0.60. Although screening is recommended to begin at age 50 years for individuals with no family history of CRC, starting ages calculated based on combined E-score and G-score differed by 12 years for men and 14 for women, for individuals with the highest vs the lowest 10% of risk.

CONCLUSIONS

We used data from 2 large international consortia to develop CRC risk calculation models that included genetic and environmental factors along with family history. These determine risk of CRC and starting ages for screening with greater accuracy than the family history only model, which is based on the current screening guideline. These scoring systems might serve as a first step toward developing individualized CRC prevention strategies.

Differences of energy expenditure while sitting versus standing: A systematic review and meta-analysis

Background Replacing sitting with standing is one of several recommendations to decrease sedentary time and increase the daily energy expenditure, but the difference in energy expenditure between standing versus sitting has been controversial. This systematic review and meta-analysis aimed to determine this difference. Designs and methods We searched Ovid MEDLINE, Ovid Embase Scopus, Web of Science and Google Scholar for observational and experimental studies that compared the energy expenditure of standing versus sitting. We calculated mean differences and 95% confidence intervals using a random effects model. We conducted different predefined subgroup analyses based on characteristics of participants and study design. Results We identified 658 studies and included 46 studies with 1184 participants for the final analysis. The mean difference in energy expenditure between sitting and standing was 0.15 kcal/min (95% confidence interval (CI) 0.12-0.17). The difference among women was 0.1 kcal/min (95% CI 0.0-0.21), and was 0.19 kcal/min (95% CI 0.05-0.33) in men. Observational studies had a lower difference in energy expenditure (0.11 kcal/min, 95% CI 0.08-0.14) compared to randomised trials (0.2 kcal/min, 95% CI 0.12-0.28). By substituting sitting with standing for 6 hours/day, a 65 kg person will expend an additional 54 kcal/day. Assuming no increase in energy intake, this difference in energy expenditure would be translated into the energy content of about 2.5 kg of body fat mass in 1 year. Conclusions The substitution of sitting with standing could be a potential solution for a sedentary lifestyle to prevent weight gain in the long term. Future studies should aim to assess the effectiveness and feasibility of this strategy.

Optimism predicts sustained vigorous physical activity in postmenopausal women

Optimism and cynical hostility are associated with health behaviors and health outcomes, including morbidity and mortality. This analysis assesses their association with longitudinal vigorous physical activity (PA) in postmenopausal women of the Women's Health Initiative (WHI). Subjects include 73,485 women nationwide without history of cancer or cardiovascular disease (CVD), and no missing baseline optimism, cynical hostility, or PA data. The Life Orientation Test-Revised Scale measured optimism. A Cook Medley questionnaire subscale measured cynical hostility. Scale scores were divided into quartiles. Vigorous PA three times or more per week was assessed via self-report at study baseline (1994–1998) and through follow-up year 6. Descriptive analysis mapped lifetime trajectories of vigorous PA (recalled at ages 18, 25, 50; prospectively assessed at baseline, and 3 and 6 years later). Hierarchical generalized linear mixed models examined the prospective association between optimism, cynical hostility, and vigorous PA over 6 years. Models adjusted for baseline sociodemographic variables, psychosocial characteristics, and health conditions and behaviors. Vigorous PA rates were highest for most optimistic women, but fell for all women by approximately 60% between age 50 and study baseline. In adjusted models from baseline through year 6, most vs. least optimistic women were 15% more likely to exercise vigorously (p < 0.001). Cynical hostility was not associated with lower odds of longitudinal vigorous PA after adjustment. Results did not differ by race/ethnicity or socioeconomic status. Higher optimism is associated with maintaining vigorous PA over time in post-menopausal women, and may protect women's health over the lifespan.

Can a workplace 'sit less, move more' programme help Spanish office employees achieve physical activity targets?

We evaluated the impact of a workplace 'sit less, move more' programme (Walk@WorkSpain, W@WS, 19-week) on self-reported activity-related energy expenditure (AREE) in Spanish office employees (n = 264; 42 ± 10 years; 171 female) randomly assigned to Intervention (IG; used W@WS; n = 129) or comparison groups (CGs; n = 135). A linear mixed model assessed changes in METs-min/wk of total, vigorous, moderate and light physical activity (IPAQ short form) between baseline and 2 months follow-up. Over the CG, IG significantly increased light intensity AREE (P = 0.027). W@WS secured sustained increases on AREE-but not on achieving PA recommendations-providing translational evidence that active living in office employees can be increased.

Alberta's Tomorrow Project: adherence to cancer prevention recommendations pertaining to diet, physical activity and body size

OBJECTIVE

To explore cross-sectional adherence to cancer prevention recommendations by adults enrolled in a prospective cohort in Alberta, Canada.

DESIGN

Questionnaire data were used to construct a composite cancer prevention adherence score for each participant, based on selected personal recommendations published by the World Cancer Research Fund/American Institute for Cancer Research (2007). Data were self-reported on health and lifestyle, past-year physical activity and past-year FFQ. The scores accounted for physical activity, dietary supplement use, body size, and intakes of alcohol, fruit, vegetables and red meat. Tobacco exposure was also included. Scores ranged from 0 (least adherent) to 7 (most adherent).

SETTING

Alberta's Tomorrow Project; a research platform based on a prospective cohort.

SUBJECTS

Adult men and women (n 24 988) aged 35-69 years recruited by random digit dialling and enrolled in Alberta's Tomorrow Project between 2001 and 2009.

RESULTS

Of the cohort, 14 % achieved adherence scores ≥5 and 60 % had scores ≤3. Overall adherence scores were higher in women (mean (sd): 3·4 (1·1)) than in men (3·0 (1·2)). The extent of overall adherence was also associated with level of education, employment status, annual household income, personal history of chronic disease, family history of chronic disease and age.

CONCLUSIONS

Reported adherence to selected personal recommendations for cancer prevention was low in this cohort of adults. In the short to medium term, these results suggest that more work is required to identify behaviours to target with cancer prevention strategies at a population level. Future work will explore the associations between adherence scores and cancer risk in this cohort.

BMI was found to be a consistent determinant related to misreporting of energy, protein and potassium intake using self-report and duplicate portion methods

OBJECTIVE

As misreporting, mostly under-reporting, of dietary intake is a generally known problem in nutritional research, we aimed to analyse the association between selected determinants and the extent of misreporting by the duplicate portion method (DP), 24 h recall (24hR) and FFQ by linear regression analysis using the biomarker values as unbiased estimates.

DESIGN

For each individual, two DP, two 24hR, two FFQ and two 24 h urinary biomarkers were collected within 1·5 years. Also, for sixty-nine individuals one or two doubly labelled water measurements were obtained. The associations of basic determinants (BMI, gender, age and level of education) with misreporting of energy, protein and K intake of the DP, 24hR and FFQ were evaluated using linear regression analysis. Additionally, associations between other determinants, such as physical activity and smoking habits, and misreporting were investigated.

SETTING

The Netherlands.

SUBJECTS

One hundred and ninety-seven individuals aged 20-70 years.

RESULTS

Higher BMI was associated with under-reporting of dietary intake assessed by the different dietary assessment methods for energy, protein and K, except for K by DP. Men tended to under-report protein by the DP, FFQ and 24hR, and persons of older age under-reported K but only by the 24hR and FFQ. When adjusted for the basic determinants, the other determinants did not show a consistent association with misreporting of energy or nutrients and by the different dietary assessment methods.

CONCLUSIONS

As BMI was the only consistent determinant of misreporting, we conclude that BMI should always be taken into account when assessing and correcting dietary intake.

Dietary biomarker evaluation in a controlled feeding study in women from the Women's Health Initiative cohort

BACKGROUND

Controlled human feeding studies are necessary for robust nutritional biomarker development and validation. Previous feeding studies have typically evaluated single nutrients and tested relatively few diets.

OBJECTIVES

The objectives were 1) to simultaneously associate dietary intake with a range of potential nutritional biomarkers in postmenopausal women by using a controlled feeding study whereby each participant was provided a diet similar to her usual diet and 2) to evaluate serum concentrations of select nutrients as potential biomarkers with the use of established urinary recovery biomarkers of energy and protein as benchmarks for evaluation.

DESIGN

Postmenopausal women from the Women's Health Initiative (n = 153) were provided with a 2-wk controlled diet in which each individual's menu approximated her habitual food intake as estimated from her 4-d food record and adjusted for estimated energy requirements. Serum biomarkers, including carotenoids, tocopherols, folate, vitamin B-12, and phospholipid fatty acids, were collected at the beginning and end of the feeding period. Doubly labeled water and urinary nitrogen biomarkers were used to derive estimates of energy and protein consumption, respectively.

RESULTS

Linear regression of (ln-transformed) consumed nutrients on (ln-transformed) potential biomarkers and participant characteristics led to the following regression (R²) values for serum concentration biomarkers: folate, 0.49; vitamin B-12, 0.51; α-carotene, 0.53; β-carotene, 0.39; lutein + zeaxanthin, 0.46; lycopene, 0.32; and α-tocopherol, 0.47. R² values for percentage of energy from polyunsaturated fatty acids and urinary recovery biomarkers of energy and protein intakes were 0.27, 0.53, and 0.43, respectively. Phospholipid saturated fatty acids and monounsaturated fatty acids and serum γ-tocopherol were weakly associated with intake (R² < 0.25).

CONCLUSIONS

Serum concentration biomarkers of several vitamins and carotenoids performed similarly to established energy and protein urinary recovery biomarkers in representing nutrient intake variation in a feeding study, and thus are likely suitable for application in this population of postmenopausal women. Further work is needed to identify objective measures of categories of fatty acid intake. This trial was registered at clinicaltrials.gov as NCT00000611.

Options for basing Dietary Reference Intakes (DRIs) on chronic disease endpoints: report from a joint US-/Canadian-sponsored working group

Dietary Reference Intakes (DRIs) are used in Canada and the United States in planning and assessing diets of apparently healthy individuals and population groups. The approaches used to establish DRIs on the basis of classical nutrient deficiencies and/or toxicities have worked well. However, it has proved to be more challenging to base DRI values on chronic disease endpoints; deviations from the traditional framework were often required, and in some cases, DRI values were not established for intakes that affected chronic disease outcomes despite evidence that supported a relation. The increasing proportions of elderly citizens, the growing prevalence of chronic diseases, and the persistently high prevalence of overweight and obesity, which predispose to chronic disease, highlight the importance of understanding the impact of nutrition on chronic disease prevention and control. A multidisciplinary working group sponsored by the Canadian and US government DRI steering committees met from November 2014 to April 2016 to identify options for addressing key scientific challenges encountered in the use of chronic disease endpoints to establish reference values. The working group focused on 3 key questions: 1) What are the important evidentiary challenges for selecting and using chronic disease endpoints in future DRI reviews, 2) what intake-response models can future DRI committees consider when using chronic disease endpoints, and 3) what are the arguments for and against continuing to include chronic disease endpoints in future DRI reviews? This report outlines the range of options identified by the working group for answering these key questions, as well as the strengths and weaknesses of each option.

Prediction of activity-related energy expenditure using accelerometer-derived physical activity under free-living conditions: a systematic review

BACKGROUND/OBJECTIVES

Activity-related energy expenditure (AEE) might be an important factor in the etiology of chronic diseases. However, measurement of free-living AEE is usually not feasible in large-scale epidemiological studies but instead has traditionally been estimated based on self-reported physical activity. Recently, accelerometry has been proposed for objective assessment of physical activity, but it is unclear to what extent this methods explains the variance in AEE.

SUBJECTS/METHODS

We conducted a systematic review searching MEDLINE database (until 2014) on studies that estimated AEE based on accelerometry-assessed physical activity in adults under free-living conditions (using doubly labeled water method). Extracted study characteristics were sample size, accelerometer (type (uniaxial, triaxial), metrics (for example, activity counts, steps, acceleration), recording period, body position, wear time), explained variance of AEE (R(2)) and number of additional predictors. The relation of univariate and multivariate R(2) with study characteristics was analyzed using nonparametric tests.

RESULTS

Nineteen articles were identified. Examination of various accelerometers or subpopulations in one article was treated separately, resulting in 28 studies. Sample sizes ranged from 10 to 149. In most studies the accelerometer was triaxial, worn at the trunk, during waking hours and reported activity counts as output metric. Recording periods ranged from 5 to 15 days. The variance of AEE explained by accelerometer-assessed physical activity ranged from 4 to 80% (median crude R(2)=26%). Sample size was inversely related to the explained variance. Inclusion of 1 to 3 other predictors in addition to accelerometer output significantly increased the explained variance to a range of 12.5-86% (median total R(2)=41%). The increase did not depend on the number of added predictors.

CONCLUSIONS

We conclude that there is large heterogeneity across studies in the explained variance of AEE when estimated based on accelerometry. Thus, data on predicted AEE based on accelerometry-assessed physical activity need to be interpreted cautiously.

A statistical model for measurement error that incorporates variation over time in the target measure, with application to nutritional epidemiology

Most statistical methods that adjust analyses for measurement error assume that the target exposure T is a fixed quantity for each individual. However, in many applications, the value of T for an individual varies with time. We develop a model that accounts for such variation, describing the model within the framework of a meta-analysis of validation studies of dietary self-report instruments, where the reference instruments are biomarkers. We demonstrate that in this application, the estimates of the attenuation factor and correlation with true intake, key parameters quantifying the accuracy of the self-report instrument, are sometimes substantially modified under the time-varying exposure model compared with estimates obtained under a traditional fixed-exposure model. We conclude that accounting for the time element in measurement error problems is potentially important.

Measurement error models with interactions

An important use of measurement error models is to correct regression models for bias due to covariate measurement error. Most measurement error models assume that the observed error-prone covariate (WW ) is a linear function of the unobserved true covariate (X) plus other covariates (Z) in the regression model. In this paper, we consider models for W that include interactions between X and Z. We derive the conditional distribution of X given W and Z and use it to extend the method of regression calibration to this class of measurement error models. We apply the model to dietary data and test whether self-reported dietary intake includes an interaction between true intake and body mass index. We also perform simulations to compare the model to simpler approximate calibration models.

Diabetes in Sub-Saharan Africa: Distribution Based on Social Status in Libreville (Gabon)

OBJECTIVE

Many researchers continue to believe that urbanization is a major contributor to diabetes. We seek to demonstrate that the social status associated with urbanization has an impact on the prevalence of diabetes in Libreville, Gabon in sub-Saharan Africa.

METHODS

Our study was conducted in Libreville, the capital of Gabon; the city has a population of 397,000. Our study analyzed data from the registries of patients hospitalized in 2013 in the main diabetes center in Libreville.

RESULTS

The results revealed that, for 2013, 798 patients were hospitalized with diabetes at a prevalence of .2%. We found differences (P<.05) between women (423) and men (375). Mean age for women was 52.02 years and 48.88 years for men. The number of existing cases hospitalized was significantly more than new cases. All levels of society were represented in our study: students (42); military (36); administratives (99); technicians (180); unemployed (295); and retired (146). The results showed that the unemployed (36%), particularly women (29.40%) are most affected by diabetes.

CONCLUSIONS

Our results show the impact of social status on the increase of diabetes in Libreville. We found that urbanization, associated with insecurity especially in women, had an effect on the prevalence of diabetes in Libreville. These results indicate that, apart from the non-modifiable factors (age, race, ethnicity), insecurity is a modifiable factor that should be taken into account.

Application of a New Statistical Model for Measurement Error to the Evaluation of Dietary Self-report Instruments

Most statistical methods that adjust analyses for dietary measurement error treat an individual's usual intake as a fixed quantity. However, usual intake, if defined as average intake over a few months, varies over time. We describe a model that accounts for such variation and for the proximity of biomarker measurements to self-reports within the framework of a meta-analysis, and apply it to the analysis of data on energy, protein, potassium, and sodium from a set of five large validation studies of dietary self-report instruments using recovery biomarkers as reference instruments. We show that this time-varying usual intake model fits the data better than the fixed usual intake assumption. Using this model, we estimated attenuation factors and correlations with true longer-term usual intake for single and multiple 24-hour dietary recalls (24HRs) and food frequency questionnaires (FFQs) and compared them with those obtained under the "fixed" method. Compared with the fixed method, the estimates using the time-varying model showed slightly larger values of the attenuation factor and correlation coefficient for FFQs and smaller values for 24HRs. In some cases, the difference between the fixed method estimate and the new estimate for multiple 24HRs was substantial. With the new method, while four 24HRs had higher estimated correlations with truth than a single FFQ for absolute intakes of protein, potassium, and sodium, for densities the correlations were approximately equal. Accounting for the time element in dietary validation is potentially important, and points toward the need for longer-term validation studies.

Nutritional epidemiology--there's life in the old dog yet!

Consideration is given to the idea that the nutritional epidemiology of cancer is dead, as some in the media have claimed. The basis for the claim does not lie in science nor has anyone with relevant knowledge made such a statement-although that, too, has been claimed. Evidence is adduced for the importance of past achievements of nutritional epidemiology. Attention is similarly drawn to recent contributions. In particular, I note the state of play of cancer and plant foods, fat and breast cancer, meat and cancer, vegetarians, intervention studies, migrant studies, and westernization of diet and lifestyle. Some next steps and some currently important questions are outlined.