Appendix D
Definitions
Absolute risk of a disease: The risk of developing the disease over a time period. It can be expressed as a ratio (e.g., a 1 in 10 risk of developing a certain disease during a lifetime) or percentage (e.g., 10 percent risk, or a 0.1 risk).
Acceptable Macronutrient Distribution Range (AMDR): A range of usual intakes for a macronutrient that is associated with reduced risk of chronic disease while providing adequate intakes of essential nutrients. An AMDR is expressed as a percentage of total energy intake.
Accuracy: Closeness of a measured or computed value to its “true” value, where the “true” value is obtained with perfect information. Owing to the natural heterogeneity and stochastic nature of many biologic and environmental systems, the “true” value may be an integrated average over a defined time period.
Adequate Intake (AI): The average daily nutrient intake observed in an apparently healthy sex and age group. It is based on experimentally derived intake levels or observations of mean nutrient intakes by a group of apparently healthy people who are maintaining a defined criterion of adequacy. When available evidence is not sufficient to determine the EAR for a nutrient, an AI is set. It is not certain where an AI level of intake fits relative to an actual nutrient requirement, as no Estimated Average Requirement (EAR) or Recommended Dietary Allowance (RDA) has been specified for these
nutrients. It is generally believed that the AI would be equal to or exceed the RDA (if one existed).
Analytical validation: Assessing assays and measurement performance characteristics and determining the range of conditions under which the assays will give reproducible and accurate data.
Apparently healthy population: The general population, excluding individuals who are malnourished, have diseases that result in malabsorption or dialysis treatments, or who have increased or decreased energy needs because of disability or decreased mobility. For the purposes of this report, it is recognized that the “apparently healthy population” potentially encompasses a diverse group of individuals with many different health conditions, such as individuals who have other chronic conditions such as obesity, hypertension, or diabetes.
Bayesian statistical methods: Statistical models with the unique feature of requiring the specification of prior distributions for any unknown parameters. These prior distributions are as integral to a Bayesian approach to statistical modeling as the expression of probability distributions.
Bias: A systematic error or deviation in results or inferences from the truth. The main types of bias arise from systematic differences in the groups that are compared (selection bias), exposure to other factors apart from the intervention of interest (performance bias), withdrawals or exclusions of people entered into a study (attrition bias), or inaccuracies in the dietary intake or outcome assessment methodologies (ascertainment bias). Systematic reviews of studies may also be particularly affected by reporting bias, where a biased subset of all the relevant data is available. Risk of bias (internal validity) is the evaluation of systematic error due to limitations in the study design or execution. More rigorously designed (better quality) randomized controlled trials are more likely to yield results that are closer to the truth than less rigorous designs.
Bioavailability: The efficiency with which a dietary component is used systematically through normal metabolic pathways. It is expressed as a percentage of intakes that is capable of being absorbed by the intestine and made available either for metabolic use or storage. It is influenced by dietary and host factors.
Bioequivalence: The comparison of two or more products with respect to their bioavailability.
Biomarker: A particular measurement sampled from a biological system or organism. It may take many forms, including an anatomic depiction (e.g., brain imaging), a physiological process (e.g., the glomerular filtration rate of the kidney or an electroencephalographic tracing of brain activity), an indicator of dietary intake (e.g., blood vitamin B12 levels), psychological or cognitive functions (e.g., remembering nouns from a recited list), or an indicator of the presence of a disease (e.g., high levels of blood enzymes indicating liver inflammation). All biomarkers have the same general potential problems: measurement error, variation over time and space, and difficulties in biological interpretation. In research and clinical medicine, biomarkers have important uses in understanding biological processes and in predicting the risk, presence, severity, response to, adverse effects of treatment, and outcomes of diseases. More general information on biomarkers is available in the report Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease (IOM, 2010).1
Calibration of a self-reported dietary intake method: The process of using a suitable intake biomarker in an attempt to correct a self-reported intake assessment for measurement error. Calibration equations are typically developed by regressing biomarker intake values on corresponding self-reported values and possibly other study participant characteristics.
Case-control study: An observational study that identifies “cases” based on a diagnosis of a disease or identification of risk factors. “Controls” are those who are without the disease or risk factor. A case-control study compares characteristics of the cases to those of the controls to determine what risk factors may account for who does or does not get the disease being studied. This design is particularly useful where the outcome is rare and past exposure can be validly measured. Measures of past exposure obtained after diagnosis (retrospective case-control studies) are more likely subject to biases that compromise validity than when measures obtained substantially before diagnosis, as in “nested” case-control studies.
Certainty (as it relates to judgments about evidence): The extent to which one can be confident that an estimate of effect is correct.
Chronic disease: The culmination of a series of pathogenic processes in response to internal or external stimuli over time that results in a clinical diagnosis or ailment and health outcomes. Also known as noncommu-
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1IOM (Institute of Medicine). 2010. Evaluation of biomarkers and surrogate endpoints in chronic disease. Washington, DC: The National Academies Press.
nicable diseases; they are not passed from person to person. They are of long duration and generally slow progression. The main types of chronic diseases are cardiovascular diseases, cancers, chronic respiratory diseases, and diabetes.
Clinical endpoint: A characteristic or variable that reflects how an individual feels, functions, or survives. The value of an endpoint increases in relation to the degree to which it conveys information about the effect of an intervention on an individual’s experience of life. Endpoints can be conceptualized in a spectrum. At one end are endpoints defined by biomarkers alone that have less relationship to an individual’s experience; in the middle are clinical events that depend on biomarkers as part of the definition; further along the spectrum are endpoints that are more closely related to events that affect an individual’s life. At the other end of the spectrum are the clearest clinical endpoints, such as death.
Cohort study: An observational study in which a defined group of people (the cohort) is without the disease of interest at the time of cohort enrollment and is followed over time, often for many years. The disease outcomes of people in the cohort are compared, to examine people who were exposed or not exposed (or exposed at different levels) to a particular factor (exposure) of interest. A prospective cohort study assembles participants and follows them into the future. A retrospective (or historical) cohort study identifies subjects from past records and follows them from the time of those records to the present.
Concentration biomarkers: Biomarkers that assess concentrations or relative percentages of nutrients or other food substances in the blood, urine, or other tissues (e.g., serum folate concentration) and can be used as an estimate of the intake of such a nutrient or other food substance.
Confidence interval: A measure of the uncertainty around the main finding of a statistical analysis. Estimates of unknown quantities, such as the relative risk comparing an experimental intervention with a control, are usually presented as a point estimate and a 95 percent confidence interval. This means that if someone were to keep repeating a study in other samples from the same population, 95 percent of the calculated confidence intervals from those studies would include the true underlying value. Wider intervals indicate less precision; narrow intervals, greater precision.
Confounding factor: A variable that is correlated (directly or inversely) to both the dependent variable and independent variable.
Cross-sectional study: An observational study that analyzes data collected from a population, or a representative subset, at a specific point in time—that is, cross-sectional data.
Deficiency disease: An illness associated with an insufficient supply of one or more essential dietary constituents.
Disease marker (or biomarker of effect): A biomarker that may predict clinical benefit (or harm or lack of benefit or harm) based on epidemiologic, therapeutic, pathophysiologic, or other scientific evidence. Includes both surrogate disease markers and non-qualified disease markers.
Dietary Reference Intakes (DRIs): A set of nutrient-based reference values established under the National Academies of Sciences, Engineering, and Medicine that are used for planning and assessing diets of apparently healthy individuals and groups.
Epigenetics: The study of stable heritable traits (or “phenotypes”) that cannot be explained by changes in DNA sequence.
Essential nutrient: A substance that is required for normal physiological functioning that cannot be synthesized in the body or cannot be synthesized in sufficient amounts to meet needs and thus must be provided in the diet.
Estimated Average Requirement (EAR): The usual daily intake of a nutrient that is expected to meet the requirement of half of healthy individuals in a group defined by life-stage and sex. The requirement is based on a specific indicator of adequacy.
Estimated Energy Requirement (EER): A calculated level of energy intake that is estimated to maintain energy balance that incorporates weight, height, physiological state (i.e., pregnancy) and level of energy expenditure.
Evidence profile: Presentation of detailed information about the quality of evidence assessed and the summary of findings for each of the included outcomes. It presents information about the body of evidence (e.g., number of studies), the judgments about the underlying quality of evidence, key statistical results, and the quality of evidence rating for each outcome. Guideline panels (e.g., Dietary Reference Intake committees) are expected to review evidence profiles to ensure that members agree about the judgments underlying the quality assessments.
Evidentiary qualification: Assessment of available evidence on associations between a biomarker and disease states, including data showing effects of interventions on both the biomarker and clinical outcomes.
Food substances: Nutrients that are essential or conditionally essential, energy nutrients, or other naturally occurring bioactive food components.
Guideline panel: A panel of a knowledgeable, multidisciplinary group of experts and representatives from key affected groups that are charged with developing clinical practice guidelines. Standards for panel composition and managing members’ conflicts of interests exist and should be followed as closely as possible. In the Dietary Reference Intake (DRI) process, a DRI committee is equivalent to the guideline panel in the Clinical Practice Guideline process.
GRADE (Grading of Recommendations, Assessment, Development and Evaluation): A method of assessing the certainty in evidence and the strength of recommendations in health care. It provides a structured and transparent evaluation of the importance of outcomes of alternative management strategies, acknowledgment of patients and the public values and preferences, and comprehensive criteria for rating down or up the certainty in evidence.
Hazard characterization: A description, preferably quantitative, of the relationship between a dose of a hazard and its effect.
Heterogeneity: The variation in study outcomes within the body of evidence for a particular outcome. It can be due to variability in participants, outcomes, or interventions, or intake response (clinical heterogeneity) or to variability in methods used, such as blinding, participant recruitment, or data collected (methodological heterogeneity).
Imprecision: A measurement of random error that often occurs when studies within the body of evidence for a particular outcome have a small sample size and the number of events is also small, resulting in a wide 95 percent confidence interval around the estimate of the effect.
Inconsistency: Unexplained heterogeneity or variability in the body of evidence for a particular outcome.
Indicator (of adequacy or toxicity): Clinical endpoints, surrogate endpoints, biomarkers, or risk factors for a chronic disease that may serve as the basis for estimating nutrient intake requirements or excessive levels of nutrient intake that might result in adverse health effects.
Indirectness: A situation that occurs when in the body of evidence for a particular outcome, studies do not directly compare the interventions of interest, apply the intervention to the population of interest, or measure the important outcomes.
Intake-response relationship: The relationship between levels of intake of a nutrient or food substance and a measure of chronic disease. If sufficient data exist, an intake-response relationship may be characterized quantitatively and may lead to a chronic disease Dietary Reference Intake.
Meta-analysis: A systematic review technique that uses statistical methods to quantitatively combine the results of similar studies in an attempt to allow inferences to be made from the sample of studies and be applied to a population of interest.
Metabolomics: The scientific study of chemical processes involving metabolites. Specifically, metabolomics is the “systematic study of the unique chemical fingerprints that specific cellular processes leave behind” (i.e., the study of their small-molecule metabolite profiles).
Monte Carlo simulation: A computerized mathematical technique that allows people to account for risk in quantitative analysis and decision making. It furnishes the decision maker with a range of possible outcomes and the probabilities they will occur for any choice of action. The technique is used by professionals in such widely disparate fields as finance, project management, transportation, the environment, and public health.
Neural tube defects: Birth defects of the brain, spine, or spinal cord that occur in the first month of pregnancy, often before a woman even knows that she is pregnant. The two most common neural tube defects are spina bifida and anencephaly. In spina bifida, the fetal spinal column does not close completely. There is usually nerve damage that causes at least some paralysis of the legs. In anencephaly, most of the brain and skull do not develop. Babies with anencephaly are usually either stillborn or die shortly after birth. Another type of defect, Chiari malformation, causes the brain tissue to extend into the spinal canal. The exact causes of neural tube defects are not known.
Non-qualified disease marker: A possible biomarker of effect that predicts a chronic disease outcome but lacks adequate evidence to be suitable as an accurate and reliable substitute for that outcome. Also known as an intermediate disease outcome marker or intermediate endpoint.
Observational study: A study in which the investigators do not intervene, but simply observe a study population. Changes or differences in characteristics or exposures are studied in relation to changes or differences in other characteristic(s) (e.g., whether or not they died), without action by the investigator. This study design has a greater risk of selection bias and ascertainment bias than do experimental studies. Cross-sectional studies, cohort studies, and case-control studies are types of observational studies.
Outcome: A term, used synonymously with “endpoints,” that refers to the clinical results of a particular illness(es), often after particular therapeutic interventions. With regard to Dietary Reference Intakes, the outcome might be a change in disease incidence (primary prevention of coronary disease) but also can be improvement of the clinical outcome of patients who have already sustained a heart attack (secondary prevention).
PICO: A technique used in evidence-based practice to frame and answer a clinical or a health care–related question. The PICO framework is also used to develop literature search strategies. The PICO acronym stands for population (P), intervention (I), comparator (C), and outcome (O).
Precision: The quality of a measurement that is reproducible in amount or performance. Measurements can be precise in that they are reproducible, but can be inaccurate and differ from “true” values when biases exist. Measurement error can also affect precision. In risk assessment outcomes and other forms of quantitative information, precision refers specifically to variation among a set of quantitative estimates of outcomes.
Primary prevention: An effort to prevent the onset of specific diseases before they occur through risk reduction, by altering behaviors or exposures that can lead to disease (e.g., smoking cessation), or by enhancing resistance to the effects of exposure to a disease agent (e.g., immunization). Primary prevention reduces the incidence of disease by addressing disease risk factors or by enhancing resistance.
Publication bias: A systematic under-estimation or over-estimation of the underlying beneficial or harmful effect due to the selective publication of studies.
Quasi-experiment: Experimental research designs that test causal hypotheses of an intervention. In contrast to a randomized controlled trial, a quasi-experiment lacks random assignment, and assignment to conditions (e.g., treatment versus no treatment or comparison condition) is by means of self-selection or administrator selection. Quasi-experimental designs
identify a comparison group that is as similar as possible to the treatment group in terms of baseline (pre-intervention) characteristics.
Random error: The difference between assessments of a variable or variables collected from one administration of an instrument compared to a long-term average based on multiple administrations of an instrument.
Randomized controlled trial: An experimental study in which two or more interventions are compared by being randomly allocated to participants. In most trials, one intervention is assigned to each individual but sometimes assignment is to defined groups of individuals (e.g., in a household, worksite, or a community) or interventions are assigned within individuals (e.g., in different orders or to different parts of the body).
Recommended Dietary Allowance (RDA): The usual daily intake level that is sufficient to meet the nutrient requirements of 97 to 98 percent of healthy individuals in the specified life-stage and sex group. If the requirements in a specified group are normally distributed, the RDA is equivalent to the EAR plus two standard deviations.
Recovery biomarkers: Biomarkers that measure a nutrient of food substance intake and output that can be “recovered” and measured quantitatively (e.g., doubly labeled water or urinary nitrogen from 24-hour urine collections).
Relative risk: In statistics and epidemiology, relative risk or risk ratio (RR) is the ratio of the probability of an event occurring (e.g., developing a disease, being injured) in an exposed group to the probability of the event occurring in a comparison, non-exposed group.
Review of the totality of the evidence: In the context of setting chronic disease Dietary Reference Intakes (DRIs), it refers to evaluating the evidence about whether a chronic disease DRI should be developed, including the systematic review evidence profiles, quantitative characterization of the intake-response, consideration of relationships with various chronic diseases, potential overlapping benefits and harms, need and appropriateness of extrapolation to other populations, and other relevant evidence.
Risk assessment: The process that serves to estimate the risk to a given target organism, system, or population, including the identification of attendant uncertainties following exposure to a particular agent. Risk assessment encompasses four steps: hazard identification, hazard characterization, exposure assessment, and risk characterization.
Risk factors: Variables that predict outcomes and can be biomarkers and social and environmental factors. The value of a risk factor depends on the degree to which it can predict an event.
Risk identification: The determination that a substance with hazardous properties is present, but also more generally refers to the identification of the type and nature of adverse effects that an agent can cause in an organism, system, or given population.
Risk management: A set of actions that entail identifying foreseeable hazards and their associated risks, assessing the risks, controlling the risks, and monitoring and reviewing the risk management process.
Secondary prevention: Efforts to reduce the impact of a disease or injury that has already occurred. This is done by detecting and treating disease or injury as soon as possible to halt or slow its progress, encouraging personal strategies to prevent re-injury or recurrence (e.g., dietary behaviors).
Surrogate disease marker: A biomarker of effect that predicts clinical benefit (or harm, or lack of benefit or harm) based on epidemiologic, therapeutic, pathophysiologic, or other scientific evidence that is qualified for its intended purposes. Also known as a surrogate marker, surrogate endpoint, or surrogate disease outcome marker.
Synthesis of evidence: An evaluation of a body of evidence collected in a systematic manner and using quantitative and qualitative synthesis strategies. Standards for methods to synthesize the evidence include the use of consistent language to characterize the level of certainty in the estimates of the effect and the use of criteria to evaluate the body of evidence (i.e., risk of bias, consistency, precision, directness, and publication bias), including specific criteria for evaluating bodies of evidence of observational studies (i.e., dose-response association, plausible confounding, and size of the effect).
Systematic error (also known as bias): A type of error that results in measurements that consistently depart from the true value in the same direction. It affects the sample mean as well as percentiles and can result in incorrect estimates and conclusions. In contrast to random error, data affected by systematic error are biased, and this type of error cannot be reduced or eliminated by taking repeat measures.
Systematic review: A scientific investigation that focuses on a specific question and that uses explicit, planned scientific methods to identify, select,
assess, and summarize the findings of similar but separate studies. It may or may not include a quantitative synthesis (meta-analysis) of the results from separate studies.
Systematic review team: A group of experts contracted specifically to conduct a systematic review.
Technical Expert Panel: A group of subject-matter experts who serve as consultants to the systematic review team in scientific matters related to the questions of interest.
Tolerable Upper Intake Level (UL): The highest usual daily nutrient intake level that is likely to pose no risk of adverse effects to nearly all healthy individuals in the specified life-stage and sex group.
Uncertainty: Lack or incompleteness of information. Quantitative uncertainty analysis attempts to analyze and describe the degree to which a calculated value may differ from the true value; it is sometimes expressed as probability distributions. Uncertainty depends on the quality, quantity, and relevance of data and on the applicability and relevance of models and assumptions.
Uncertainty factor (UF): In toxicology, one of several factors used in calculating the reference dose from experimental data. The UF is intended to account for (1) the variation in sensitivity among humans, (2) the uncertainty in extrapolating from one population to another, (3) the uncertainty in extrapolating data obtained in a study that covers less than the full life of the exposed animal or human, and (4) the uncertainty in using Lowest-Observed-Adverse-Effect Level data rather than No-Observed-Adverse-Effect Level data.
Utilization analysis: Contextual analysis based on the specific use proposed and the applicability of available evidence to this use. This includes a determination of whether the validation and qualification conducted provide sufficient support for the use proposed.
Validation of a biomarker: The action of checking or proving the accuracy of some measure. Validity can sometimes be established by conducting controlled human feeding studies in a population of interest. Each participant is provided a diet over a defined time period, and potential biomarkers in pertinent biofluids (e.g., urine or serum/plasma) are examined for correlation with actual intake of the nutrient or food substance of interest. Biomarkers meeting criteria (e.g., correlation ≥0.6) may provide useful
objective measures of intake in the population from which feeding study participants were drawn.
Validation of a self-reported dietary intake method: A process to establish validity by comparing the self-reported measurement with an objective measure of intake (e.g., quantitative recovery biomarkers such as doubly labeled water assessment of short-term energy intake, or urinary nitrogen assessment of protein intake). It should be noted that objective intake measures, such as quantitative recovery biomarkers, are not available for all nutrients or food substances.
Variability: True differences in attributes due to heterogeneity or diversity. Variability is usually not reducible by further measurement or study, although it can be better characterized. Two important sources of variability are biological variability (inter-individual differences, i.e., attributable to genetic differences and influenced by environmental factors) and analytical variability (i.e., associated with analysis of dietary component).
