The carbon isotope ratio of breath is elevated by short-term and long-term added sugar and animal protein intake in a controlled feeding study.

Background: The breath carbon isotope ratio (CIR) was recently identified as a noninvasive candidate biomarker of short-term added sugars (AS) intake.

Objectives: This study aimed to better understand the potential of the breath CIR as a dietary biomarker. We evaluated the effects of short-term and long-term intakes of AS, animal protein (AP), and related variables on breath CIR, in the context of typical dietary intake patterns.

Measurement error models with zero inflation and multiple sources of zeros, with applications to hard zeros.

We consider measurement error models for two variables observed repeatedly and subject to measurement error. One variable is continuous, while the other variable is a mixture of continuous and zero measurements. This second variable has two sources of zeros.

Developing the POTOMAC Model: A Novel Prediction Model to Study the Impact of Lymphopenia Kinetics on Survival Outcomes in Head and Neck Cancer Via an Ensemble Tree-Based Machine Learning Approach.

Purpose: Lymphopenia is associated with poor survival outcomes in head and neck squamous cell carcinoma (HNSCC), yet there is no consensus on whether we should limit lymphopenia risks during treatment. To fully elucidate the prognostic role of baseline versus treatment-related lymphopenia, a robust analysis is necessary to investigate the relative importance of various lymphopenia metrics (LMs) in predicting survival outcomes.

Methods: In this prospective cohort study, 363 patients were eligible for analysis (patients with newly diagnosed, nonmetastatic HNSCC treated with neck radiation with or without chemotherapy in 2015-2019).

Issues in Implementing Regression Calibration Analyses.

Regression calibration is a popular approach for correcting biases in estimated regression parameters when exposure variables are measured with error. This approach involves building a calibration equation to estimate the value of the unknown true exposure given the error-prone measurement and other covariates. The estimated, or calibrated, exposure is then substituted for the unknown true exposure in the health outcome regression model.

Urinary Sucrose and Fructose From Spot Urine May Be Used as a Predictive Biomarker of Total Sugar Intake-Findings From a Controlled Feeding Study.

Background: Recently, we confirmed 24-h urinary sucrose plus fructose (24 uSF) as a predictive biomarker of total sugar intake. However, the collection of 24-h urine samples has limited feasibility in population studies.

Objective: We investigated the utility of the urinary sucrose plus fructose (uSF) biomarker measured in spot urine as a measure of 24 uSF biomarker and total sugar intake.

Evaluating a Model of Added Sugar Intake Based on Amino Acid Carbon Isotope Ratios in a Controlled Feeding Study of U.S. Adults.

Previous studies suggest that amino acid carbon stable isotope ratios (CIRs) may serve as biomarkers of added sugar (AS) intake, but this has not been tested in a demographically diverse population. We conducted a 15-day feeding study of U.S.

Establishing 24-Hour Urinary Sucrose Plus Fructose as a Predictive Biomarker for Total Sugars Intake.

Background: Twenty-four-hour urinary sucrose and fructose (24uSF) has been studied as a biomarker of total sugars intake in two feeding studies conducted in the United Kingdom (UK) and Arizona (AZ). We compare the biomarker performance in these populations, testing whether it meets the criteria for a predictive biomarker.

Methods: The UK and AZ feeding studies included 13 and 98 participants, respectively, aged 18 to 70 years, consuming their usual diet under controlled conditions.

Measurement Error Affecting Web- and Paper-Based Dietary Assessment Instruments: Insights From the Multi-Cohort Eating and Activity Study for Understanding Reporting Error.

Few biomarker-based validation studies have examined error in online self-report dietary assessment instruments, and food records (FRs) have been considered less than food frequency questionnaires (FFQs) and 24-hour recalls (24HRs). We investigated measurement error in online and paper-based FFQs, online 24HRs, and paper-based FRs in 3 samples drawn primarily from 3 cohorts, comprising 1,393 women and 1,455 men aged 45-86 years. Data collection occurred from January 2011 to October 2013.

An evaluation of the serum carbon isotope ratio as a candidate predictive biomarker of the dietary animal protein ratio (animal protein/total protein) in a 15-day controlled feeding study of US adults.

Background: The serum natural abundance carbon isotope ratio (CIR) was recently identified as a candidate biomarker of animal protein intake in postmenopausal women. Such a biomarker would help clarify the relation between dietary protein source (plant or animal) and chronic disease risk.

Objectives: We aimed to evaluate the performance of the serum CIR as a biomarker of dietary protein source in a controlled feeding study of men and women of diverse age and BMI.

Investigating the performance of 24-h urinary sucrose and fructose as a biomarker of total sugars intake in US participants - a controlled feeding study.

Background: Developing approaches for the objective assessment of sugars intake in population research is crucial for generating reliable disease risk estimates, and evidence-based dietary guidelines. Twenty-four-hour urinary sucrose and fructose (24uSF) was developed as a predictive biomarker of total sugars intake based on 3 UK feeding studies, yet its performance as a biomarker of total sugars among US participants is unknown.

Objectives: To investigate the performance of 24uSF as a biomarker of sugars intake among US participants, and to characterize its use.

Fatigue, anxiety, and quality of life in breast cancer patients compared to non-cancer controls: a nationwide longitudinal analysis.

Purpose: Fatigue and anxiety are common and significant symptoms reported by cancer patients. Few studies have examined the trajectory of multidimensional fatigue and anxiety, the relationships between them and with quality of life.

Methods: Breast cancer patients (n = 580) from community oncology clinics and age-matched controls (n = 364) completed fatigue and anxiety questionnaires prior to chemotherapy (A1), at chemotherapy completion (A2), and six months post-chemotherapy (A3).

Performance and Feasibility of Recalls Completed Using the Automated Self-Administered 24-Hour Dietary Assessment Tool in Relation to Other Self-Report Tools and Biomarkers in the Interactive Diet and Activity Tracking in AARP (IDATA) Study.

Background: Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) is a self-administered web-based tool designed to collect detailed dietary data at low cost in observational studies.

Objective: The objectives of this study were to describe, overall and by demographic groups, the performance and feasibility of ASA24-2011 recalls and compare Healthy Eating Index-2015 (HEI-2015) total and component scores to 4-day food records (4DFRs) and food frequency questionnaires (FFQs).

Design: Over 12 months, participants completed up to 6 ASA24 recalls, 2 web-based FFQs, and 2 unweighed paper-and-pencil 4DFRs.

STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 1-Basic theory and simple methods of adjustment.

Measurement error and misclassification of variables frequently occur in epidemiology and involve variables important to public health. Their presence can impact strongly on results of statistical analyses involving such variables. However, investigators commonly fail to pay attention to biases resulting from such mismeasurement.

STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 2-More complex methods of adjustment and advanced topics.

We continue our review of issues related to measurement error and misclassification in epidemiology. We further describe methods of adjusting for biased estimation caused by measurement error in continuous covariates, covering likelihood methods, Bayesian methods, moment reconstruction, moment-adjusted imputation, and multiple imputation. We then describe which methods can also be used with misclassification of categorical covariates.

Epidemiologic analyses with error-prone exposures: review of current practice and recommendations.

Purpose: Variables in observational studies are commonly subject to measurement error, but the impact of such errors is frequently ignored. As part of the STRengthening Analytical Thinking for Observational Studies Initiative, a task group on measurement error and misclassification seeks to describe the current practice for acknowledging and addressing measurement error.

Methods: Task group on measurement error and misclassification conducted a literature survey of four types of research studies that are typically impacted by exposure measurement error: (1) dietary intake cohort studies, (2) dietary intake population surveys, (3) physical activity cohort studies, and (4) air pollution cohort studies.

Combining a Food Frequency Questionnaire With 24-Hour Recalls to Increase the Precision of Estimation of Usual Dietary Intakes-Evidence From the Validation Studies Pooling Project.

Improving estimates of individuals' dietary intakes is key to obtaining more reliable evidence for diet-health relationships from nutritional cohort studies. One approach to improvement is combining information from different self-report instruments. Previous work evaluated the gains obtained from combining information from a food frequency questionnaire (FFQ) and multiple 24-hour recalls (24HRs), based on assuming that 24HRs provide unbiased measures of individual intakes.

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.

Comparison of self-reported dietary intakes from the Automated Self-Administered 24-h recall, 4-d food records, and food-frequency questionnaires against recovery biomarkers.

Background: A limited number of studies have evaluated self-reported dietary intakes against objective recovery biomarkers.

Objective: The aim was to compare dietary intakes of multiple Automated Self-Administered 24-h recalls (ASA24s), 4-d food records (4DFRs), and food-frequency questionnaires (FFQs) against recovery biomarkers and to estimate the prevalence of under- and overreporting.

Design: Over 12 mo, 530 men and 545 women, aged 50-74 y, were asked to complete 6 ASA24s (2011 version), 2 unweighed 4DFRs, 2 FFQs, two 24-h urine collections (biomarkers for protein, potassium, and sodium intakes), and 1 administration of doubly labeled water (biomarker for energy intake).

Categorizing a continuous predictor subject to measurement error.

Epidemiologists often categorize a continuous risk predictor, even when the true risk model is not a categorical one. Nonetheless, such categorization is thought to be more robust and interpretable, and thus their goal is to fit the categorical model and interpret the categorical parameters. We address the question: with measurement error and categorization, how can we do what epidemiologists want, namely to estimate the parameters of the categorical model that would have been estimated if the true predictor was observed? We develop a general methodology for such an analysis, and illustrate it in linear and logistic regression.

Evaluation of the 24-Hour Recall as a Reference Instrument for Calibrating Other Self-Report Instruments in Nutritional Cohort Studies: Evidence From the Validation Studies Pooling Project.

Calibrating dietary self-report instruments is recommended as a way to adjust for measurement error when estimating diet-disease associations. Because biomarkers available for calibration are limited, most investigators use self-reports (e.g.

Longitudinal functional additive model with continuous proportional outcomes for physical activity data.

Motivated by physical activity data obtained from the BodyMedia FIT device (www.bodymedia.com), we take a functional data approach for longitudinal studies with continuous proportional outcomes.

The impact of stratification by implausible energy reporting status on estimates of diet-health relationships.

The food frequency questionnaire (FFQ) is known to be prone to measurement error. Researchers have suggested excluding implausible energy reporters (IERs) of FFQ total energy when examining the relationship between a health outcome and FFQ-reported intake to obtain less biased estimates of the effect of the error-prone measure of exposure; however, the statistical properties of stratifying by IER status have not been studied. Under certain assumptions, including nondifferential error, we show that when stratifying by IER status, the attenuation of the estimated relative risk in the stratified models will be either greater or less in both strata (implausible and plausible reporters) than for the nonstratified model, contrary to the common belief that the attenuation will be less among plausible reporters and greater among IERs.

Methods to Assess Measurement Error in Questionnaires of Sedentary Behavior.

Sedentary behavior has already been associated with mortality, cardiovascular disease, and cancer. Questionnaires are an affordable tool for measuring sedentary behavior in large epidemiological studies. Here, we introduce and evaluate two statistical methods for quantifying measurement error in questionnaires.

Moment reconstruction and moment-adjusted imputation when exposure is generated by a complex, nonlinear random effects modeling process.

For the classical, homoscedastic measurement error model, moment reconstruction (Freedman et al., 2004, 2008) and moment-adjusted imputation (Thomas et al., 2011) are appealing, computationally simple imputation-like methods for general model fitting.