Review of Dietary Reference Intakes for Selected Nutrients

Challenges and Implications for Federal Food and Nutrition Policy

Contractor and Cooperator Report No. 28 February 2007

By Barbara Devaney, Mary Kay Crepinsek, Ken Fortson, and Lisa Quay, Mathematica Policy Research, Inc.

Abstract

Dietary Reference Intakes (DRIs) are the most recent set of nutrient-based reference values, which, together with recommended dietary assessment methods, are being used to update estimates of nutrient adequacy of population subgroups. Recent estimates suggest both dramatic dietary deficiencies and excesses for selected nutrients among some subgroups. This report takes a critical look at the studies and methods used to set DRIs. The findings show that errors in dietary recall data—either underreporting or overreporting of intakes—may partially explain the inadequacies and excessive intakes. In addition, the lack of sensitive, specific biochemical markers has resulted in DRIs for selected nutrients to be based on less than optimal data. Because the DRIs are used by food and nutrition assistance programs to set nutritional objectives, establish program benefits, and evaluate program outcomes, it is important to understand the issues involved in deriving the DRIs and how to interpret the results of dietary assessments.

This study was conducted by Mathematica Policy Research, Inc., under a cooperative research contract with USDA’s Economic Research Service (ERS) Food and Nutrition Assistance Research Program (FANRP): contract number 43-3K06-06-3114 (ERS project representative: Elizabeth Frazao). The views expressed are those of the authors and not necessarily those of ERS or USDA. Contents

Chapter Page

I INTRODUCTION...... 1

BACKGROUND...... 1

OVERVIEW OF REPORT ...... 3

II NUTRIENT REQUIREMENTS AND DIETARY ASSESSMENT METHODS...... 5

NUTRIENT REQUIREMENTS...... 5

ENERGY REQUIREMENTS ...... 8

DIETARY ASSESSMENT METHODS ...... 8

What Proportion of a Population Subgroup has Nutrient Intakes that Do Not Meet Nutrient Requirements? ...... 9 What Proportion of a Population Subgroup is at Risk of Excessive Intake Levels?...... 10

SUMMARY ...... 10

III ESTIMATED ENERGY REQUIREMENTS FOR INFANTS AND YOUNG CHILDREN...... 11

BACKGROUND...... 12

REVIEW OF STUDIES ASSESSING USUAL ENERGY INTAKES ...... 13

RE-ESTIMATION OF THE TOTAL ENERGY EXPENDITURE EQUATIONS...... 16

Methods ...... 17 Results ...... 18

DISCUSSION...... 21

IV REVIEW OF STUDIES USED TO SET THE DIETARY REFERENCE INTAKES FOR SELECTED NUTRIENTS ...... 23

ZINC ...... 24

Studies Assessing Usual Zinc Intakes...... 24 Method and Data Used to Derive the UL for Zinc ...... 26 Discussion...... 28

VITAMIN A...... 31

Studies Assessing Usual Preformed Vitamin A Intake ...... 32 Methods and Data Used to Derive the UL for Vitamin A...... 34 Discussion...... 35

MAGNESIUM...... 37

Studies Assessing Usual Magnesium Intake ...... 38 Method and Data Used to Derive the EAR for Magnesium ...... 38 Discussion...... 45

VITAMIN E...... 47

Studies Assessing Usual Vitamin E Intake ...... 48 Methods and Data Used to Derive the EAR for Vitamin E...... 51 Discussion...... 54

FIBER...... 57

Studies Assessing Usual Intake of Dietary Fiber ...... 57 Method and Data Used to Derive the AI for Fiber ...... 58 Discussion...... 62

POTASSIUM ...... 63

Studies Assessing Usual Potassium Intake...... 64 Method and Data Used to Derive the AI for Potassium...... 64 Discussion...... 69

V CONCLUSIONS...... 71

STUDY FINDINGS AND RESEARCH NEEDS...... 72

CONCLUDING DISCUSSION...... 77

REFERENCES...... 79 Contents Tables

Table Page

II.1 Dietary Reference Intakes...... 6

III.1 Estimated Energy Requirement (EER) for Boys and Girls ...... 13

III.2 Studies Assessing Usual Energy Intake of Infants and Young Children...... 15

III.3 Total Energy Expenditures and Estimated Energy Requirements—Fixed Effects Models ...... 19

III.4 Total Energy Expenditures and Estimated Energy Requirements—OLS Models ...... 20

IV.1 Studies Assessing the Zinc Intake of Infants and Young Children...... 25

IV.2 Derivation of the Tolerable Upper Limit (UL) for Zinc for Infants and Young Children...... 27

IV.3 Studies Assessing the Preformed Vitamin A Intake of Infants and Young Children...... 33

IV.4 Derivation of the Tolerable Upper Limit (UL) for Preformed Vitamin A for Infants and Young Children ...... 34

IV.5 Studies Assessing the Magnesium Intake of Older Children and Adults...... 39

IV.6 Derivation of the Estimated Average Requirement (EAR) for Magnesium for Children and Adults ...... 42

IV.7 Studies Assessing the Vitamin E Intake of Children and Adults ...... 49

IV.8 Derivation of the Estimated Average Requirement (EAR) for Vitamin E for Children and Adults ...... 53

IV.9 Studies Assessing the Dietary Fiber Intake of Children and Adults ...... 58

IV.10 Derivation of the Average Intake (AI) for Total Fiber...... 60

IV.11 Studies Assessing the Potassium Intake of Children and Adults...... 65

IV.12 Derivation of the Average Intake (AI) for Potassium...... 67

V.1 Re-Examination of the DRIs for Selected Nutrients: Study Findings and Research Needs...... 73

Figures

Figure Page

IV.1 Vitamin E (α-tocopherol) Content of Fats and Oils ...... 56

C HAPTER I

I NTRODUCTION

ood and nutrition assistance programs use nutrient reference standards to establish nutritional objectives, set benefit levels, and evaluate program outcomes and Feffectiveness. Nutrient reference standards are critical to the Food Stamp Program— the largest of all food and nutrition assistance programs, at an annual cost of $27 billion in 2005—through their role in the Thrifty Food Plan, a food plan designed to meet nutrient standards at a minimal cost and used to set program benefits. The National School Lunch Program underwent a major nutritional overhaul under the Healthy Meals for Healthy Americans Act of 1994 based on dietary assessments that showed that American children were consuming excessive amounts of fat, saturated fat, cholesterol, and sodium relative to dietary standards. The Special Supplemental Nutrition Program for Women, Infants and Children (WIC) designs its food packages to provide nutrients found to be lacking in the diets of low-income populations. More recently, the Institute of Medicine report on revising the WIC food packages used results from dietary assessment studies in proposing revisions to existing food packages (Institute of Medicine (IOM) 2006).

This report examines a set of nutrient reference standards, called the Dietary Reference Intakes, for selected nutrients—food energy, zinc, preformed vitamin A, magnesium, vitamin E, fiber, and potassium. These nutrients are those that have been highlighted in recent dietary assessment studies indicating potential concern about either inadequate or excessive intakes.

BACKGROUND Over the past decade, our knowledge about human nutrient requirements has increased significantly, resulting in a set of new nutrient reference standards called the Dietary Reference Intakes (DRIs) (Institute of Medicine 1997, 1998, 2000b, 2001, 2002/2005, 2005). The DRIs cover more nutrients and dietary constituents than did the previous Recommended Dietary Allowances. In addition, where data are available, the DRIs are based on a reduction in the risk of chronic disease rather than merely the absence of signs of deficiency. 2

The development of the DRIs was accompanied by two additional IOM reports that provide guidance on methods for using the DRIs for dietary assessment and planning (Institute of Medicine 2000a, 2003). In recent years, several studies using the recommended dietary assessment methods have become available, allowing researchers and policy makers to take a new look at which nutrients may be of concern—or potential concern—because of either inadequate or excessive intake levels. Many of these studies consistently point to several nutrients of potential concern:

• Estimated energy intakes exceed energy requirements for infants and children. In several studies of the nutrient intakes of young children, mean energy intakes exceed mean estimated energy requirements. This finding is observed for infants and toddlers in the Feeding Infants and Toddlers Study; for infants and toddlers participating in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) from the Continuing Survey of Food Intakes by Individuals (CSFII); and for other subgroups of children 4 to 8 years of age in the CSFII.

• High proportions of infants and children have usual intakes above Tolerable Upper Intake Levels for zinc and vitamin A. Data from the CSFII show that almost 90 percent of non-breastfeeding WIC infants and more than half of WIC children have usual intakes of zinc above the Tolerable Upper Intake Level. For vitamin A, the proportion with usual intakes above the Tolerable Upper Intake Level is between 38 and 56 percent for non- breastfeeding WIC infants and about 25 percent for WIC children.

• All subgroups of the population have a high prevalence of inadequacy of magnesium and vitamin E. Estimates of the prevalence of inadequate intakes of magnesium and vitamin E range from about 50 percent for young children to almost 100 percent for some subgroups of adult women.

• Fiber and potassium intakes are very low relative to DRI standards. For children 2 years of age and over and for all adult subgroups, mean usual intakes of fiber and potassium are far below the Adequate Intakes defined in the DRIs. For most groups, even the 90th percentile of usual intake is less than the Adequate Intake level.

These empirical findings are striking. They imply either dramatic dietary deficiencies among some population subgroups, excessive intakes of some nutrients, limitations of dietary assessment studies, or shortcomings with the DRIs for some nutrients. It is important to understand which interpretation is most valid. If nutrient deficiencies and/or excesses do exist, these findings have important implications for food assistance and nutrition programs—from designing programs that achieve nutrient and food objectives to assessing program benefits and costs. If limitations of dietary assessment studies—such as over- or under-reporting of dietary intakes—explain the results, then concerns about inadequate or excessive nutrient intakes are allayed but important questions could be raised about the validity and usefulness of dietary recall data. Or if shortcomings in the DRIs,

Chapter I: Introduction 3

rather than real dietary inadequacies or excesses, contribute to the study findings, then efforts could be directed to addressing the issues associated with the DRIs.

One important issue associated with these dietary assessment results concerns the nature of the DRIs. As described above, the DRIs were established with the goal of reducing the risk of chronic disease, not simply eliminating signs of deficiency. As such, it may be difficult to observe or measure any adverse health impact in the short term (particularly among certain age groups), even if the long-term health impact is important.

A second possible methodological problem associated with the recent set of dietary assessment studies includes misreporting of intakes from 24-hour dietary recalls. A fairly extensive literature acknowledges possible underreporting of intakes by adults, especially adolescent females and adult women (Mertz et al. 1991; Johansson et al. 1998; Schoeller 2002). For infants and young children, some recent studies suggest that intakes may be overreported (Devaney et al. 2004; Institute of Medicine 2006). While it is likely that underreporting of intakes by adults and overreporting of intakes by young children may explain some of the surprising findings, the magnitude of some of the inadequacies and excesses identified in this report cannot be explained solely by biases in 24-hour dietary recall data collection methods.

A third methodological issue is that many of the recent dietary assessment studies used 24-hour dietary recall data from the CSFII, which did not include intakes from dietary supplements. Thus, findings may overestimate the prevalence of inadequate intakes and underestimate the prevalence of excessive intakes. However, other data sets do include the nutrient contribution of dietary supplements, and many of the surprising results are also found in these studies.

A final methodological issue, and the one considered in the following chapters, is whether the methods used to set some of the DRIs need to be examined more closely. Since the publication of the new DRIs and the methods for their use in dietary assessment, researchers have tended to take the DRIs as given and to interpret the results of dietary assessment studies in a straightforward manner. That is, a high prevalence of inadequacy implies nutrient deficiencies and a high prevalence of excessive intakes implies risk of nutrient toxicity.

OVERVIEW OF REPORT This report reviews and discusses the methods and studies used to set relevant DRIs for food energy, zinc, vitamin A, magnesium, vitamin E, fiber, and potassium. It presents findings from two basic analytic tasks:

1. An in-depth analysis of the underlying models used to calculate the EERs for infants and young children

2. A review and discussion of the literature and methods used to set the DRIs for zinc, preformed vitamin A, magnesium, vitamin E, fiber, and potassium

Chapter I: Introduction 4

This review of models and methods used to set the DRIs is not intended to identify errors or problems with the DRIs. Rather, it is intended to add to our understanding of which nutrients are of concern and why, and to help policy makers and the public health community determine whether there are dietary concerns that need to be incorporated into the design of food and nutrition assistance programs and the provision of dietary guidance.

The organization of this report is as follows: Chapter II provides additional background information on nutrient requirements and dietary assessment methods; Chapter III examines estimates of energy requirements for infants and toddlers; Chapter IV describes and discusses the methods and studies used to set the DRIs for the other nutrients; and the final chapter summarizes the main findings and discusses research needs.

Chapter I: Introduction C HAPTER II

N UTRIENT R EQUIREMENTS AND D IETARY A SSESSMENT M ETHODS

s knowledge of the relationship between diet and long-term health status has increased over the past several decades, so has our understanding of the nutrients Arequired for optimal growth and development, as well as for reduced risk of chronic health conditions. Building on this improved knowledge base, the recently developed dietary reference intakes (DRIs) represent our best understanding of the nutrient requirements of individuals. In turn, dietary assessment studies use data on nutrient intakes to determine whether diets provide enough nutrients to meet the requirements without being excessive.

During the development of the new DRIs, it became clear that guidance on how to interpret and use them would be important for researchers, policy makers, and dietary professionals. As a result, the Institute of Medicine (IOM) established a Subcommittee on the Interpretation and Uses of the DRIs, which produced two volumes on how to use the DRIs in dietary assessment and planning (Institute of Medicine 2000a, 2003). Several recent studies have used methods recommended by the IOM to assess the adequacy of diets consumed by specific population subgroups using the DRIs. Overall, this emerging literature has been extremely useful for producing more reliable and precise estimates of the prevalence of inadequacy and for identifying nutrients and dietary components where there are concerns about excessive intakes. Previous dietary assessment studies, based on the old RDAs and inappropriate assessment methods, had findings that were either incorrect or misinterpreted.

This chapter provides background information on the DRIs and dietary assessment methods. It focuses first on nutrient requirements, as summarized by the DRIs, and then discusses the dietary assessment methods used to determine nutrient adequacy.

NUTRIENT REQUIREMENTS The IOM Committee on the Scientific Evaluation of Dietary Reference Intakes defined nutrient requirements as “the lowest continuing intake level of a nutrient that will maintain a defined level of nutriture in an individual.” To develop the DRIs, the committee used data from observational studies (case reports, cross-sectional, cohort, and case-control studies) and experimental studies (randomized and nonrandomized treatment or prevention trials 6

and controlled dose-response, balance, turnover, and depletion-repletion studies). In the absence of human studies, selected animal studies were also considered. The primary sources of data were studies published in the peer-reviewed literature. The quality of the studies was evaluated on the basis of study design and power; methods of measuring intake and indicators of adequacy; and potential biases, nutrient interactions, and confounding factors. Data were often sparse or came from studies that were limited in their ability to provide the information needed by the committee. For example, the existing data on many nutrients did not provide a basis for setting specific requirements for different age and gender subgroups. In general, there was a lack of information relating the effects of inadequate intake to indicators of health status (Institute of Medicine 2001).

The DRIs for vitamins and minerals include four reference standards—the Estimated Average Requirement, the Recommended Dietary Allowance, the Adequate Intake, and the Tolerable Upper Intake Level, as defined in Table II.1. All DRIs pertain to usual intake—an individual’s average daily nutrient intake over time. In general, the DRIs are intended to apply to healthy individuals with diets similar to those consumed in the United States and Canada (Institute of Medicine 2001).

Table II.1. Dietary Reference Intakes

Estimated Average Requirement The usual intake level estimated to meet the requirements of half the healthy individuals in a life stage and gender group. At this level of intake, the other half of the healthy individuals in the specified group would not have their needs met.

Recommended Dietary Allowance Usual intake level that is sufficient to meet the nutrient requirements of nearly all healthy individuals in a particular life stage and gender group (97.5 percent of the individuals in a group).

Adequate Intake Usual intake level based on experimentally derived intake levels or approximations of observed mean nutrient intakes by a group (or groups) of apparently healthy people who are maintaining a defined nutritional state or criterion of adequacy—used when an EAR and RDA cannot be determined.

Tolerable Upper Intake Level Highest level of usual nutrient intake that is likely to pose no risk of adverse health effects to almost all individuals in the specified life stage group. As intake increases above the UL, the risk of adverse effects increases. Source: Institute of Medicine 2000a.

Estimated Average Requirement (EAR). The general method for developing the EARs was to review the scientific evidence available on nutrient function, absorption, and metabolism; the clinical effects of inadequate nutrient intake; potential functional, biochemical, or other indicators of nutrient status; and factors affecting the nutrient requirement (such as nutrient-nutrient interactions). A criterion of nutritional adequacy was then chosen for each nutrient and, in some cases, for individual life-stage groups. Because

Chapter II: Nutrient Requirements and Dietary Assessment Methods 7

of a paucity of data on children’s requirements, EARs for children were often extrapolated from adult EARs.

Recommended Dietary Allowance (RDA). If nutrient requirements were determined to be normally distributed, the RDA was defined as the EAR plus two standard deviations of the EAR. When data on the variability in requirements were not available, a coefficient of variation of 10 percent was assumed. The RDA was then calculated as 120 percent of the EAR (EAR + 2 (0.10*EAR)).

Adequate Intake (AI). If the information available to the committee was not sufficient to determine an EAR (and thus an RDA), an AI was set for the nutrient. AIs were based on experimentally derived or observed levels of intake by groups of healthy people. For young infants, the AI equals the average amount of the nutrient in human milk for exclusively breastfed, full-term infants. Various data sources were used to determine the AIs for adults—intake data from a single experiment, estimated dietary intakes in a healthy population, or data from several sources, each of which alone did not provide a reliable estimate of an EAR.

Tolerable Upper Intake Level (UL). The need for establishing ULs arose primarily in response to the increased use of dietary supplements and fortified foods. For most nutrients, ULs apply to total intake from food, water, and supplements. If adverse health effects have only been associated with intake from supplements or forms of the nutrient used in food fortification, the UL may apply to only those sources. Adverse effects were defined as “any significant alteration in the structure or function of the human organism, or impairment of a physiologically important function that could lead to a health effect that is adverse” (World Health Organization 1996). Adverse nutrient-nutrient interactions were also considered in setting the UL.

A risk assessment model was developed and used to establish the ULs.1,2 This model involves four steps. The first is hazard identification, which is a comprehensive review of data on adverse health effects caused by excessive intake of the nutrient. Step two is dose- response assessment. Dose-response assessment involves selecting a data set, identifying a critical endpoint with its associated level(s) of nutrient intake, and assessing the extent of uncertainty, resulting in an estimate of the UL for each life stage group. Steps three and four are intake assessment and risk characterization, respectively. These steps entail estimating distributions of usual total daily intake (or intake from supplements only) of the nutrient and estimating the proportion of the population with nutrient intakes that exceed the UL.

1The subcommittee considered the possibility of developing a mathematical model to determine the ULs for each nutrient. Because of the paucity of data on levels of intake associated with adverse effects, uncertainties associated with extrapolating from clinical studies to the healthy population, and scientific judgments that would be required, they concluded that this approach would not be consistent with acceptable risk assessment practices. 2A comparable international model for establishing ULs was recently developed by participants in a workshop convened jointly by the Food and Agriculture Organization and World Health Organization (2006).

Chapter II: Nutrient Requirements and Dietary Assessment Methods 8

The dose-response assessment, which results in an estimate of the UL, depends on toxicological concepts often used in assessing the risk of exposures to chemicals:

• No-observed-adverse-effect level (NOAEL) is the highest usual intake of a nutrient at which no adverse effects have been observed in individuals or groups.

• Lowest-observed-adverse-effect level (LOAEL) is the lowest usual intake level of a nutrient at which an adverse effect has been identified. When the data are not available to reveal the NOAEL, the LOAEL is used to set the UL.

• An uncertainty factor (UF) is applied to the NOAEL and LOAEL to account for inter-individual variation in sensitivity, extrapolation from animal studies, or lack of data on the consequences of long-term excessive intake.

The UL is calculated by dividing the NOAEL or LOAEL by the final uncertainty factor, which combines all potential sources of uncertainty for the nutrient. For some nutrients, data were not sufficient to estimate a UL reliably. The absence of a UL does not imply that the nutrient does not have a tolerable upper intake level. Rather, it indicates available evidence is not sufficient to permit estimation of a UL. When no data were available to determine the NOAEL or LOAEL for a particular life stage group, the UL was usually extrapolated from data for other age groups, based on known differences in body weight.

ENERGY REQUIREMENTS In the case of food energy, nutrient requirements are expressed in terms of estimated energy requirements (EERs) (Institute of Medicine 2002/2005). An adult EER is the usual intake level needed to balance energy expenditures in a healthy adult of a given age, gender, weight, height, and level of physical activity. In children, the EER is defined as the sum of the dietary energy intake predicted to maintain energy balance for an individual’s age, weight, height, and physical activity level, plus an allowance for normal growth and development, called Energy Deposition.

Data on total energy expenditures were used to estimate EERs for age and gender subgroups. For most age and gender subgroups, estimated EERs for individuals within the group depend on weight, height, and physical activity level. For infants and young children up to age 3, however, the total energy expenditure equations, and thus the EERs, depend only on weight in kilograms.

DIETARY ASSESSMENT METHODS To assess the nutrient adequacy of population subgroups, dietary assessment studies generally address two main questions:

1. What proportion of a population subgroup has nutrient intakes that do not meet nutrient requirements?

Chapter II: Nutrient Requirements and Dietary Assessment Methods 9

2. What proportion is at risk of excessive intake levels?

For both questions, the usual intake of a nutrient—as opposed to intake on a given day—is the relevant construct, since an individual’s health depends on long-run or usual dietary patterns. Usual intake seldom, if ever, can be observed. Rather, dietary recalls provide data on observed nutrient intakes over some specified period of time. Observed daily intake measures individual usual intake with error. That is, nutrient intake varies from individual to individual in the group, but it also varies from day to day for a given individual. This day-to-day variability is “noise,” as what is of most interest is the individual-to- individual variability in usual nutrient intake. Because for most nutrients, the day-to-day variability in intakes can be larger than the individual-to-individual variability, it is very important to “remove” the effect of this additional variability when estimating the distribution of usual intakes.

In recent years, most dietary assessment studies have used a method developed by researchers at Iowa State University (ISU) to produce estimates of usual intake distributions. The method is based on a simple additive measurement error model that permits adjusting the data for the presence of day-to-day variability (Nusser et al. 1996). It is known as the ISU method for estimating usual nutrient intake distributions, and has been widely adopted by the nutrition community (see, for example, Beaton 1994; Carriquiry 1999; Institute of Medicine 2000a).

What Proportion of a Population Subgroup has Nutrient Intakes that Do Not Meet Nutrient Requirements? An exact estimate of the prevalence of nutrient inadequacy is impractical because the requirement for a nutrient is seldom observed. Typically the only information available is summary measures of the distribution of nutrient requirements—the EAR, RDA, and measures of variation in nutrient requirements.

It is possible to show, however, that the proportion of individuals in a group whose nutrient intakes do not meet requirements can be approximated, if both the specific EAR for the appropriate age-gender subgroup and a reliable estimate of the distribution of nutrient intakes are available. It has been shown that, under certain assumptions, the proportion with intakes less than the EAR is an estimate of the proportion of a group whose intakes do not meet requirements (Beaton 1994; Carriquiry 1999; Institute of Medicine 2000a). The approach, known as the EAR cut-point method, produces a reliable estimate of the prevalence of nutrient inadequacy in a group.

For nutrients with an AI, only limited inferences can be made regarding the prevalence of inadequacy. If mean intake levels are equal to or exceed the AI, it is likely that the prevalence of inadequacy is low; but if mean intakes are less than the AI, no conclusions can be drawn about the prevalence of inadequacy (Institute of Medicine 2000a). In practice, for nutrients with an AI, dietary assessment studies present estimates of mean intakes and various percentiles of the intake distributions and make qualitative conclusions about adequacy.

Chapter II: Nutrient Requirements and Dietary Assessment Methods 10

In the case of energy, requirements are expressed in terms of EERs. Since populations maintaining their body weight should have intake and EER distributions with roughly equal mean values, dietary assessment studies often compare the mean intake of food energy with the mean EER for each subgroup to assess reported energy adequacy from dietary recall data.

What Proportion of a Population Subgroup is at Risk of Excessive Intake Levels? To estimate the proportion of each subgroup at risk of excessive intake levels, dietary assessment studies calculate the percentage with intakes exceeding the UL. Because ULs have not been established for all nutrients, this research question can be addressed only for those nutrients with ULs. Some ULs refer to intakes from supplements and fortified foods, and others to intakes from foods, beverages, and supplements.

SUMMARY Recent dietary assessment studies have used the methods described above to determine the proportion of individuals with inadequate or excessive usual nutrient intake. As discussed in Chapter I, many of these studies have found several subgroups with unexpectedly high proportions with intakes of certain nutrients that exceed or fall below the established DRIs. The following chapters examine the development of the estimated energy requirements for children and youth, as well as the methods used to set the DRIs for a selected group of nutrients, in an effort to better understand these findings and to determine whether they signal important public health concerns.

Chapter II: Nutrient Requirements and Dietary Assessment Methods C HAPTER III

E STIMATED E NERGY R EQUIREMENTS FOR I NFANTS AND Y OUNG C HILDREN

ietary assessment studies use data on energy intakes and compare usual intakes with energy requirements to assess whether diets provide enough energy without being Dexcessive. For infants and young children, the results of recent analyses of dietary intakes show that mean usual energy intakes exceed mean Estimated Energy Requirements (EERs). This finding is observed for infants and toddlers in the Feeding Infants and Toddlers Study, for infants and toddlers participating in the Continuing Survey of Food Intakes by Individuals (CSFII), and for other subgroups of children 4 to 8 years of age in the CSFII (Institute of Medicine 2006, 2004; Devaney et al. 2005, 2004).

Four possible explanations could potentially account for the excess of reported energy intakes over requirements:

1. Infants and young children consume more energy than required. Although overconsumption of food energy is consistent with the increasing prevalence of overweight and obesity among children, the discrepancy between mean usual intake and mean EER is too large to account for increases in the rate of overweight children. 2. Parents and caregivers overreport the amount of foods and beverages that infants and young children consume. If this is true, dietary assessment studies would lead to an overestimate of energy intakes. 3. Parents underreport children’s body weight. As children’s weights are the key determinant of their EERs, underreporting body weights will also understate their EERs. 4. EERs for young children are too low. The EERs presented in the macronutrient report for children 0 through 36 months of age are about 20 percent lower than the 1985 World Health Organization (WHO) estimates of energy requirements of young children.

12

This chapter examines the fourth possibility. Specifically, for young children 0 through 36 months of age, this chapter examines the sensitivity of the EERs to alternative specifications of the total energy expenditure equation presented in the macronutrient report (Institute of Medicine 2002/2005). The chapter first presents background information on energy requirements and recent estimates of EERs developed by the macronutrient panel. Next, it briefly summarizes studies of energy intake, documenting the energy imbalance reported in these studies. Estimates of alternative specifications for total energy expenditures are then presented. Finally, a concluding section summarizes the results.

The results of this re-analysis suggest that the EERs for young children do not appear to be too low. In fact, many of the alternative specifications produced estimates of total energy expenditure, and EERs, that were lower than those reported in the macronutrient report.

BACKGROUND People need energy to live. Energy is necessary for the functions of the human body— respiration, circulation, physical work, and maintenance of body temperature (Institute of Medicine 2002/2005). People consume energy through intakes of food and beverages, and they expend energy through the activities of daily living. Energy balance occurs when energy intakes equal energy expenditures. Imbalances between energy intakes and energy expenditures lead to body weight gains or losses.

A person’s energy requirement is the usual intake level necessary to achieve energy balance in a healthy adult of a given age, gender, weight, height, and physical activity level (Institute of Medicine 2002/2005). For adults who are not pregnant or lactating, energy requirements equal total energy expenditures. For infants and young children and for pregnant or lactating adults, energy requirements equal total energy expenditures plus the energy needed for growth, called energy deposition.

Total energy expenditure (TEE) has several components (Institute of Medicine 2002/2005; Food and Agriculture Organization 2004):

• Basal Energy Expenditure (BEE). Derived from extrapolating the basal metabolic rate (BMR) to a 24-hour period. The BMR is defined as the rate of energy expenditure that occurs in the postabsorptive state, which occurs after an overnight fast of 12 to 14 hours and when a person is resting comfortably, supine, awake, and motionless in a thermoneutral environment.

• Thermic Effect of Food (TEF). The increase in energy expenditure above the BMR to eat and process (that is, digest, transport, metabolize, and store) food.

• Physical Activity. Every bodily movement that requires energy expenditure. Physical activity is usually the second-largest component of daily energy expenditure (after BEE), and the most variable across individuals.

Chapter III: Estimated Energy Requirements for Infants and Young Children 13

• Thermoregulation. The ability of an individual to keep his or her body temperature within certain limits, even when the surrounding temperature differs.

TEE is the sum of BEE, TEF, physical activity, and thermoregulation (Institute of Medicine 2002/2005). The macronutrient panel measured TEE using the doubly labeled water method, which measures the average daily energy expenditure of free-living people over a period of days (typically, 10 to 14 days). The technique involves a subject’s ingestion of a dose of water enriched with an isotope of hydrogen and an isotope of oxygen; then researchers determine the disappearance of both isotopes as their concentrations decline (Schoeller et al. 1986). The doubly labeled water method is generally considered the “gold standard” for measuring energy expenditures and is the basis for the most recent energy requirements set by the IOM macronutrient panel and the WHO. Direct measurement of TEE through the doubly labeled water method accounts for the difference between recent estimates of estimated energy requirements and previous estimates (such as the 1985 WHO estimates), which generally relied on either dietary intake data or a factorial approach (Food and Agricultural Organization and WHO 2006).

Using doubly labeled water method data, the macronutrient panel estimated regression equations of TEE for age and gender subgroups. For most adult subgroups, energy requirement is equivalent to TEE. For infants, young children, and adolescents, energy requirements include TEE plus energy deposition (ED). The energy needed for growth is estimated to decline from more than a quarter of total energy requirements at three months of age to less than five percent at 12 months of age and older (Food and Agriculture Organization 2004). Based on the TEE equations and estimates of ED, Table III.1 presents estimates of EERs for infants and young children at selected ages.

Table III.1. Estimated Energy Requirement (EER) for Boys and Girls Boys Girls Age TEE ED EER TEE ED EER (mos.) (kcal/d) (kcal/d) (TEE+ED) (kcal/d) (kcal/d) (TEE+ED) 3 434 138 572 389 132 521 6 603 42 645 541 52 593 12 817 27 844 745 23 768 18 941 20 961 879 20 899 24 1,030 20 1,050 977 20 997 30 1,101 20 1,121 1,057 20 1,077 Source: Institute of Medicine 2002/2005, Tables 5-16 and 5-17.

REVIEW OF STUDIES ASSESSING USUAL ENERGY INTAKES One underlying principle of assessing energy intakes and expenditures is energy balance. Over a period of time, energy intakes equal energy expenditures to maintain stable body weight. If a person’s energy balance is negative over time—intakes lower than expenditures—then that person will take energy from his or her reserves and lose body

Chapter III: Estimated Energy Requirements for Infants and Young Children 14 weight. Conversely, if the energy balance is positive over a period of time—intakes higher than expenditures—then excess energy intakes are added to reserves and the person gains body weight.

Since the macronutrient panel published its report on energy requirements, several studies have used 24-hour dietary recall data to compare reported energy intakes with EERs. These studies found that, for most adolescent and adult subgroups, mean usual energy intake was less than the mean EER (Devaney et al. 2005; Institute of Medicine 2006). This result is generally considered implausible, because such a negative energy balance would imply weight loss in these subgroups and the exact opposite pattern of weight gain has been observed. In light of the substantial difference between EER and intake—coupled with the fact that adults and adolescents are not losing weight but actually gaining weight—a likely explanation is that adults and adolescents underreport their food and beverage intakes (Schoeller 2002; Johansson et al. 1998; Mertz et al. 1991).

For young children, however, the findings of studies assessing energy intakes indicate a positive energy balance. As Table III.2 shows, several studies using replicate observations from 24-hour dietary recall data have found that mean usual energy intakes of infants and young children exceeded the mean EER. In the Feeding Infants and Toddlers Study, the positive energy balance increased with the age of the study respondents. Mean usual energy intake was 10 percent higher than the mean EER for infants 4 to 6 months of age, 23 percent higher for infants 7 to 12 months of age, and 31 percent higher for toddlers 12 to 24 months of age (Devaney et al. 2004). Mean usual energy intake was also higher than mean EER for subgroups of young children, including Hispanic and non-Hispanic infants and toddlers and WIC participants (Briefel et al. 2006b; Ponza et al. 2004; Institute of Medicine 2006, 2004; Devaney et al. 2005).

As mentioned earlier, four possible explanations could account for the positive energy balance reported in analyses of usual energy intakes of infants and young children. First, infants and young children could be consuming more energy than they need. This possibility is consistent with empirical evidence showing the increasing prevalence of overweight among children. However, the discrepancy between mean usual intake and mean EER is too large to be consistent with increases in the prevalence of overweight. For example, the mean energy intake for toddlers 1 to 2 years of age in the Feeding Infants and Toddlers Study was 1,220 kcal/d, compared with a mean EER of only 931 kcal/d (Devaney et al. 2004). This imbalance of almost 300 kcal/d would be projected to lead to an excess weight gain of at least 1 lb. every two weeks, or at least 25 lbs. over a year. Such excessive weight gain is far greater than the weight gain observed for toddlers over time.

Second, parents may be overreporting the intakes of infants and young children. Although most dietary recall studies provide visual aids to help parents or caregivers accurately report the quantities of foods and beverages consumed, respondents may underestimate the amounts spilled, spit up, or otherwise left uneaten. In addition, parents may have an unconscious desire to describe their child as a “good eater,” which could also

Chapter III: Estimated Energy Requirements for Infants and Young Children 15

Table III.2. Studies Assessing Usual Energy Intake of Infants and Young Children Reference Data Set Key Results for Energy Intake Briefel et al. 2006 FITS 2002 Infants 4 - 5 months: mean usual energy intake was 9% higher than the mean EER for Hispanic (H) and non-Hispanic (NH) infants. Infants 6 - 11 months: mean usual energy intake was 17% higher than the mean EER for H, 22% higher for NH. Toddlers 12 - 24 months: mean usual energy intake was 36% higher than the mean EER for H, 31% higher for NH.

Institute of Medicine CSFII 1994 - Non-breastfed WIC infants and children: 2006 1996, 1998 0 - 3 months: mean usual energy intake was 21% higher than the mean EER. 4 - 5 months: mean usual energy intake was 29% higher than the mean EER. 6 - 11 months: mean usual energy intake was 32% higher than the mean EER. 12 - 23 months: mean usual energy intake was 37% higher than the mean EER. 2 through 4 years: mean usual energy intake was 24% higher than the mean EER for low-active children and 14% higher than the mean EER for active children.

Devaney et al. 2005 CSFII 1994 - WIC infants < 1 year: mean usual energy intake was 22% higher than the mean 1996, 1998 EER. WIC toddlers 1-3 years: mean usual energy intake was 27% higher than the mean EER.

Devaney et al. 2004 FITS 2002 Infants 4 - 6 months: mean usual energy intake was 10% higher than the mean EER. Infants 7 - 12 months: mean usual energy intake was 23% higher than the mean EER. Toddlers 12 - 24 months: mean usual energy intake was 31% higher than the mean EER.

Institute of Medicine CSFII 1994 - Non-breastfed WIC-income-eligible infants and children: 2004 1996, 1998 < 1 year: mean usual energy intake was 30% higher than the mean EER. 1 through 4 years: mean usual energy intake was 25% higher than the mean EER for low-active children and 17% higher than the mean EER for active children.

Ponza et al. 2004 FITS 2002 Infants 7 - 12 months who participated in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC): mean usual energy intake was 32% higher than the mean EER. WIC toddlers 12 - 24 months: mean usual energy intake was 40% higher than the mean EER.

CSFII = Continuing Survey of Food Intake by Individuals FITS = Feeding Infants and Toddlers Study NHANES = National Health and Nutrition Examination Survey

Chapter III: Estimated Energy Requirements for Infants and Young Children

16

lead to overreporting of intakes. (This is in stark contrast to the general finding of underreporting of intakes among adults.)

Third, parents may be underreporting children’s weights. Such mistakes could be prevalent if, for example, many parents do not know their child’s exact current weight but instead report their weight based on past measurements. This would be especially likely if parents rely on measurements during doctor visits and check-ups. As a consequence, EERs, which increase linearly with body weight, will also be understated. The understatement may not be trivial, either: if body weight is underreported by 1 kg (about 2.2 pounds), EER will be underestimated by approximately 70 kcal/d.

Fourth, energy requirements may be underestimated. The EERs for energy presented in the macronutrient report are generally lower than previous estimates of energy requirements. The TEE estimates are approximately 80 percent of the 1985 WHO recommendations for energy intake of infants and toddlers. Those estimates, however, were based on energy intakes, not on estimates of TEE from doubly labeled water techniques, and they included an extra five percent allowance for presumed underreporting of intakes (Institute of Medicine 2002/2005). Recent WHO estimates of energy requirements, which use doubly labeled water methods, are similar in magnitude to those developed by the IOM macronutrient panel (Food and Agriculture Organization 2004).

RE-ESTIMATION OF THE TOTAL ENERGY EXPENDITURE EQUATIONS Given the discrepancy observed between reported energy intakes and mean EERs of infants and young children, it is useful to examine in more detail the estimates of TEE to determine how sensitive the requirement estimates are to model specification. The macronutrient report summarizes the vast literature that examines the factors associated with total energy requirements of young children and concludes that energy requirements of children 0 through 2 years vary by age, gender, and feeding mode. The final specification of the TEE equation, however, uses only weight as the predictor of energy expenditures for young children. The panel finds that adding additional covariates beyond weight— covariates such as gender, age, height, and squares of age, weight, and height—does not improve the predictive power of the TEE equation (Institute of Medicine 2002/2005). The TEE equation for young children 0 through 2 years of age is

(IOM) TEE (kcal/d) = -100 + 89*weight of the child (kg) .

The doubly labeled water data set for infants and young children used to estimate the TEE equation reported in the macronutrient report is included in Appendix Table I-1 of the macronutrient report (Institute of Medicine 2002/2005). This data set includes doubly labeled water data for 71 individuals 0 through 2 years of age, with repeated measurements on each child as he or she ages (for a total of 320 observations). In addition to TEE calculations, the data set includes information on each individual’s age, height, weight, body mass index, gender, and feeding type.

Chapter III: Estimated Energy Requirements for Infants and Young Children 17

Methods The doubly labeled water data set is used to estimate regression equations for TEE with additional covariates included in the regression. The additional covariates include a set of

covariates Ci that do not vary over time (such as gender) and covariates Xit that do vary with time (such as age, age-square, and height): =+ββ′′ + β ++ηε (3.1) TEEit0 X X it C C i i it .

Note that, because characteristics such as an infant’s gender do not change over time, C is not indexed by t. The error term has two components, each of which has a mean of 0: an η individual component that varies across infants but not over time ( i) and an error term that ε varies both over time and across infants ( it). The individual-specific component captures any characteristics that are correlated with TEE but unobservable. If these unobservable characteristics are also correlated with the covariates, accounting for them can potentially improve the accuracy of our estimates.

As in the macronutrient report, the initial analysis estimates fixed effects models that use the repeated observations on individual TEEs. Such models help isolate the effect of observable characteristics that vary over time, including height, weight, and age. The fixed effects model also accounts for unobservable individual characteristics by focusing on how the dependent and independent variables change over time. Taking the mean of equation (3.1) for each individual gives

=+ββ′′ + β ++ηε (3.2) TEEi 0 X XCiCiii.

Subtracting (3.2) from (3.1) yields

=−+−β ′ εε (3.3) (TEEit – TEEi ) X ()()XXit i it i ,

η where the time-invariant terms Ci and i difference out of the equation. Because fixed individual variables difference out of equation (3.3), it is not possible to determine the effects that characteristics such as gender have on energy expenditures. To estimate the effects of time-invariant factors such as gender, the analysis also estimates Ordinary Least Squares (OLS) regression equations, as depicted by equation (3.1).

To assess the predictive power of the alternative model specifications, the root mean square error of the model, the F-statistic for adding covariates beyond weight, and the R- square are reported. TEE is then estimated for boys and girls of selected ages using the coefficients of the regression equations together with median weight and height for boys and girls at each age according to published data. Adding an allowance for ED yields the EERs.

Chapter III: Estimated Energy Requirements for Infants and Young Children 18

Results Table III.3 presents the results of estimating alternative fixed effects model specifications of the TEE equations. The first column of the table shows the estimates presented in the macronutrient report. Alternative specification (1) is the attempted replication of the IOM results, and the remaining columns show estimates that include additional covariates in the TEE equations. Overall, the fixed effects results are consistent with the findings of the TEE equation presented in the macronutrient report, which indicates that body weight alone is the best predictor of energy expenditures and energy requirements. Although specification (4) in Table III.3 has a slightly lower mean square error than the specification in the macronutrient report (108 versus 109), the difference is small, and the F-statistic for the addition of covariates beyond age is not statistically significant.

The bottom panel of Table III.3 presents EERs based on the alternative model specifications for TEE, published data on standard reference heights and weights, and estimates of energy deposition. Regardless of the model specification, EERs for infants and boys and girls up to 18 months of age are similar. However, for older children, especially at 30 months of age, EERs based on the more inclusive specifications—with age and age- square as covariates—are lower than EERs from the simpler specifications.

A drawback to fixed effects models is that they do not separately identify the importance of time-invariant individual characteristics (such as gender); individual characteristics are collectively represented by the fixed effect for that person. Such characteristics may be important predictors in the model and would help in determining whether, for example, boys and girls have different energy requirements. Further, unobservable individual characteristics do not appear to be important determinants of TEE.1

In this context, OLS models are a more appropriate specification. Not surprisingly, the OLS model of TEE as a function of infants’ weight alone, reported in column (1) of Table III.4, is very similar to the macronutrient report.2 Height also does not provide additional explanatory power (column 2) nor does a linear term for age (column 3). However, this latter result may be a misspecification: when a quadratic function of age is included in column (4), both age and its square are highly significant at the one percent level. A female indicator variable is marginally significant in columns (5) – (8).

1 η Estimates of the fixed effects model indicate that the variance of the individual effects ( i) is very small ε relative to the variance of it; that is, TEE does not vary much across individuals beyond what is explained with η ε ε observable characteristics. This suggests that treating ( i + it) as the error term in (3.1) rather than it alone has η little effect on the parameter estimates in an OLS regression. In addition, since i does not vary over individuals, there is less concern that these combined error terms will be correlated for repeated observations of the same infant. Thus, a random effects estimation approach is not necessary. 2The estimates reported in Table III.4 are clustered by infant to account for the fact that most individuals show up in the data multiple times, but as there is no evidence of individual-specific effects, this makes little difference.

Chapter III: Estimated Energy Requirements for Infants and Young Children 19

Table III.3. Total Energy Expenditures and Estimated Energy Requirements—Fixed Effects Models

(IOM) (1) (2) (3) (4) (5) TEE Regression Results

Intercept -100 -101** -116 -66 505 -8 (56) (35) (155) (302) (401) (89) Weight (kilograms) 89** 89** 87** 87** 77** 64** (3) (4) (20) (20) (21) (18) Height (meters) 46 -47 -1037 (449) (653) (802) Age (months) 1.0 32* 18.1 (5.8) (16.0) (11) Age squared -0.6* -.42 (0.3) (.25)

F-test: Covariates beyond kg .92 .98 .26 .25 Root MSE 109 109 109 109 108 108 R-squared .74 .74 .74 .74 .74 .75

Estimated Energy Requirements

6-month girl 593 589 589 590 605 596 12-month girl 768 764 763 763 793 777 18-month girl 899 894 893 894 924 903 24-month girl 997 991 991 994 994 976 30-month girl 1,077 1,071 1,071 1,076 1,012 1,006

6-month boy 645 641 640 640 631 631 12-month boy 844 839 837 836 841 832 18-month boy 961 956 954 955 961 948 24-month boy 1,050 1,044 1,043 1,045 1,026 1,015 30-month boy 1,121 1,115 1,115 1,119 1,040 1,038

Notes: Doubly labeled water data used to predict energy expenditure include 320 total observations of 71 infants (Institute of Medicine (IOM), 2002/2005). TEE and EER measured in kcal/d. Standard errors in parentheses, clustered by individual. Reported F-test p-value tests the inclusion of the covariates for that specification excepting weight and an intercept term. Estimated energy requirements are based on associated total energy expenditure model plus published energy deposition allowance (IOM 2002/2005, pp. 169-170) using median weight and height for girls and boys at each age (IOM 2002/2005, pp. 132-135).

* indicates statistically significant at the five percent level. ** indicates statistically significant at the one percent level.

Chapter III: Estimated Energy Requirements for Infants and Young Children Table III.4. Total Energy Expenditures and Estimated Energy Requirements—OLS Models

(IOM) (1) (2) (3) (4) (5) (6) (7) (8) (9)

TEE Regression Results 20

Chapter III:Estimated EnergyRequire Intercept -100** -92** -209* -38 110 -78** -202* 6 160 -12 (56) (27) (90) (175) (192) (29) (91) (169) (180) (39) Weight (kilograms) 89** 88** 74** 76** 74** 88** 73** 76** 73** 67** (3) (3) (11) (11) (11) (3) (11) (11) (10) (7) Height (meters) 325 8 -308 344 -37 -365 (245) (377) (406) (241) (364) (387) Age (months) 3.6 19.9** 4.4 21.2** 17.1** (3.5) (7.5) (3.4) (7.0) (5.5) Age squared -0.4* -0.5* -0.4* (0.2) (0.2) (0.2) Female -21 -22 -24 -25* -24

ments for Infantsand Young Children (14) (13) (13) (12) (13)

F-test: Covariates beyond kg .19 .27 .03 .13 .09 .08 .00 .00 Root MSE 109 110 110 110 109 110 109 109 108 108 R-squared .74 .74 .74 .74 .75 .74 .74 .74 .75 .75

Estimated Energy Requirements

6-month girl 593 591 589 591 596 583 581 583 587 585 12-month girl 768 763 758 760 782 755 750 751 774 769 18-month girl 899 892 888 894 910 884 879 886 903 896 24-month girl 997 988 987 1000 984 980 979 994 976 970 30-month girl 1,077 1,067 1,070 1,091 1,012 1,059 1,062 1,086 1,005 1,002

6-month boy 645 642 637 635 632 655 650 649 647 646 12-month boy 844 837 827 825 840 850 841 839 855 851 18-month boy 961 953 945 947 957 966 958 962 973 967 24-month boy 1,050 1,040 1,036 1,046 1,024 1,054 1,050 1,063 1,041 1,035 30-month boy 1,121 1,110 1,111 1,129 1,046 1,124 1,124 1,148 1,063 1,060

Notes: Doubly labeled water data used to predict energy expenditure include 320 total observations of 71 infants (Institute of Medicine (IOM), 2002/2005). TEE and EER measured in kcal/d. Standard errors in parentheses, clustered by individual. Reported F-test p-value tests the inclusion of the covariates for that specification excepting weight and an intercept term. Estimated energy requirements are based on associated total energy expenditure model plus published energy deposition allowance (IOM 2002/2005, pp. 169-170) using median weight and height for girls and boys at each age (IOM 2002/2005, pp. 132-135). * indicates statistically significant at the five percent level. ** indicates statistically significant at the one percent level.

21

The preferred TEE specification includes weight, age, age squared, and gender (column 9) but excludes height. This specification has the minimum root mean square error of the nine models. An F-test strongly prefers this model to the specification in column (1) that was used for the macronutrient report. Each of the covariates is individually statistically significant at the five percent level as well, with the lone exception of gender, which nonetheless has a p-value of .055.

Using the same specification as used in the macronutrient report (column 1), the EERs for young children are very similar to the DRI estimates. With the preferred specification in column (9), EERs for girls and boys 6- to 18-months of age are also very similar to DRI estimates. However, the EERs for girls and boys 24 months of age (970 kcal/d and 1035 kcal/d, respectively) are slightly lower than the DRI estimates for this age. Extrapolating to children 30 months of age, as done in the macronutrient report, yields EERs that are 7.0 percent lower for girls and 5.4 percent lower for boys than the published EERs. These predictions, however, extend beyond the age range of the data set, which only includes observations on infants and children 0 though 25 months of age.

DISCUSSION Although the exact TEE model specifications that perform best here differ from the macronutrient report, the resulting EERs are very similar, and there is no evidence that misspecifying the TEE model has understated energy requirements. The analysis presented in this chapter indicates that other characteristics beyond body weight have explanatory power in the TEE model, including age and gender. Nonetheless, neither the inclusion of these factors nor a different estimation strategy (OLS rather than fixed effects) drastically changes the EER predictions.

The statistical model in this chapter focuses on estimating TEE, and ED is taken as known in order to compute EER. As ED contributes to growth, it is especially important for young children. In fact, estimating ED is itself a very challenging task that has not been conclusively accomplished. The estimates in the macronutrient report are based on the work of Butte et al. (2000), who estimated ED by analyzing healthy infants’ growth and changes in body composition. Because their methods require close, intensive study of each individual participant, they are necessarily restricted to a small sample (76 infants). Although there is no specific documented reason to suggest that their study sample is not representative, the small sample size nonetheless raises concerns about how well their results generalize to the national population.

Regardless, ED is a very small fraction of EER, and any errors in estimating ED would not explain the observed gap between infants’ energy requirements and their intakes. For children 12 to 24 months of age, for example, true ED would have to be 15 times greater than current estimates to explain the difference between mean energy intake and mean EER. Even if ED estimates are imprecise, the estimation error would have to be implausibly large to affect the EERs.

Chapter III: Estimated Energy Requirements for Infants and Young Children 22

The finding that the EERs estimated here are similar to those in the macronutrient report suggests that other explanations drive the large difference between energy requirements and intakes. One possibility is that intakes actually do exceed requirements by a substantial margin, but as discussed earlier, infants’ observed weight gains over time are not of sufficient magnitude to explain the difference. Instead, either overreporting of children’s energy intakes or underreporting of children’s weights—or some combination of the two factors—is most likely responsible for the disparity.

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Table IV.1. Studies Assessing the Zinc Intake of Non-breastfeeding Infants and Young Children

Supplements Reference Data Set Key Results Included?

Arsenault and Brown 2003 CSFII No Infants age 0 - 6 months : 92% had usual zinc intakes above 1994-1996, 1998 the UL. Infants age 7 - 12 months : 86% had usual zinc intakes above the UL. Children age 1 - 3 years : 51% had usual zinc intakes above the UL. Children age 4 - 5 years : 3% had usual zinc intakes above the UL.

Devaney et al. 2005 CSFII No WIC children and income-eligible non-participants age 1 - 3 years: 1994-1996, 1998 60% had usual zinc intakes above the UL. Children age 4 - 8 years from vulnerable subgroups: More than 10% had usual zinc intakes above the UL.

Institute of Medicine 2006 CSFII No WIC infants and children: 1994-1996, 1998 0 - 3.9 months: 86% had usual zinc intakes above the UL. 4 - 5.9 months: 97% had usual zinc intakes above the UL. 6 - 11.9 months: 88% had usual zinc intakes above the UL. 1 - 1.9 years: 56% had usual zinc intakes above the UL. 2 - 4.9 years: 58% had usual zinc intakes above the UL.

Moshfegh et al. 2005 NHANES No Children age 1 - 3 years: 69% had usual zinc intakes above 2001-2002 the UL. Children age 4 - 8 years : 22% had usual zinc intakes above the UL.

Devaney et al. 2004 FITS 2002 Yes Toddlers age 12 - 24 months: 43% had usual zinc intakes above the UL.

Briefel et al. 2006a FITS 2002 Yes Supplement Users: Includes Infants age 6 - 11 months : 60% had usual zinc intakes above breastfed and the UL. non-breastfed Toddlers age 12 - 24 months : 68% had usual zinc intakes infants above the UL. Supplement Non-Users: Infants age 6 - 11 months : 59% had usual zinc intakes above the UL. Infants age 12 - 24 months : 38% had usual zinc intakes above the UL.

Briefel et al. 2006b FITS 2002 Yes Hispanic toddlers age 12 - 24 months: 47% had usual zinc intakes above the UL. Non-Hispanic toddlers age 12 - 24 months: 40% had usual zinc intakes above the UL.

IV. Review of Studies Used to Set the Dietary Reference Intakes for Selected Nutrients



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Table IV.3. Studies Assessing the Preformed Vitamin A Intake of Non-breastfeeding Infants and Young Children

Supplements Reference Data Set Key Results Included?

Institute of Medicine 2006 CSFII No WIC infants and children: 1994-1996, 1998 0 - 3 months : 38% had usual intakes of preformed vitamin A above the UL. 4 - 5 months : 56% had usual intakes of preformed vitamin A above the UL. 6 - 11 months : 43% had usual intakes of preformed vitamin A above the UL. 1 - 1.9 years : 25% had usual intakes of preformed vitamin A above the UL. 2 - 4.9 years : 16% had usual intakes of preformed vitamin A above the UL.

Moshfegh et al. 2005 NHANES No Children age 1 - 3 years: 12% had usual intakes of 2001-2002 preformed vitamin A above the UL.

Devaney et al. 2004 FITS 2002 Yes Toddlers age 12 to 24 months: 35% had usual intakes of preformed vitamin A above the UL.

Ponza et al. 2004 FITS 2002 Yes WIC toddlers age 12 - 24 months: 40% had usual intakes of preformed vitamin A above the UL. WIC non-participant toddlers age 12 - 24 months: 34% had usual intakes of preformed vitamin A above the UL.

Briefel et al. 2006a FITS 2002 Yes Toddlers age 12 - 24 months (supplement users): 97% had usual intakes of preformed vitamin A above the UL. Toddlers age 12 - 24 months (supplement non-users): 15% had usual intakes of preformed vitamin A above the UL.

Briefel et al. 2006b FITS 2002 Yes Hispanic toddlers age 12 - 24 months: 46% had usual intakes of preformed vitamin A above the UL. Non-Hispanic toddlers age 12 - 24 months: 35% had usual intakes of preformed vitamin A above the UL.

CSFII = Continuing Survey of Food Intake by Individuals FITS = Feeding Infants and Toddlers Study NHANES = National Health and Nutrition Examination Survey

IV. Review of Studies Used to Set the Dietary Reference Intakes for Selected Nutrients 

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Table IV.4. Derivation of the Tolerable Upper Limit (UL) for Preformed Vitamin A for Infants and Young Children

Life Stage Group ULa Method Used to Derive UL

Infants 0-12 mos: Risk assessment, based on critical adverse effects of bulging fontanel and skeletal 600 mcg/day abnormalities due to excess preformed vitamin A. No data to identify NOAEL. LOAEL calculated by averaging the lowest doses of 5,500-6,750 mcg/day of vitamin A from four case reports of hypervitaminosis A in infants 2.5 to 5.5 months old (LOAEL = 6,460 mcg/day, rounded to 6,000 mcg/day). UF set at 10 considering uncertainty of extrapolating from a LOAEL to NOAEL and interindividual variability. UL = LOAEL/UF = 6,000/10 = 600 mcg/day of preformed vitamin A.

Young children 1-3 years: Limited data to identify NOAEL or LOAEL. UL extrapolated from UL for adults, 600 mcg/day based on relative body weight:

ULchild = ULadult x Weightchild/Weightadult = 3,000 mcg/day x (68.5 kg/13 kg) = 600 mcg/day of preformed vitamin A (rounded).

a As preformed vitamin A. NOAEL = No-Observed-Adverse-Effect Level LOAEL = Lowest-Observed-Adverse-Effect Level UF = Uncertainty factor

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Table IV.5. Studies Assessing the Magnesium Intake of Older Children and Adults

Supplements Reference Data Set Key Results Included?

Suitor and Gleason 2002 CSFII No Female children age 9 - 13 years: 33% had magnesium intakes 1994-1996 below the EAR. Male children age 9 - 13 years : 16% had magnesium intakes below the EAR. Female adolescents age 14 - 18 years: 89% had magnesium intakes below the EAR. Male adolescents age 14 - 18 years: 62% had magnesium intakes below the EAR.

Foote et al. 2004 CSFII No Male adults over 18 years of age : mean probability of adequacy 1994-1996 for magnesium was 36%. day 1 data only Female adults over 18 years of age : mean probability of adequacy for magnesium was 34%.

Devaney et al. 2005 CSFII No Most adolescent and adult subgroups have inadequate 1994-1996, 1998 intakes of magnesium. Female adolescents: 90% had magnesium intakes below the EAR. Older adults over 60 years of age: Between 70% and 75% had magnesium intakes below the EAR. Low-income individuals: high proportions of low-income individuals above 9 years of age had magnesium intakes below the EAR. FSP and WIC participants: high proportions of FSP and WIC participants over 9 years of age had magnesium intakes below the EAR.

Institute of Medicine 2006 CSFII No Non-breastfeeding, postpartum adolescent and adult women 14 - 44 1994-1996, 1998 years of age : 88% had magnesium intakes below the EAR for women age 19 - 30 years.

Moshfegh et al. 2005 NHANES No Female children age 9 - 13 years: 44% had magnesium intakes 2001-2002 below the EAR. Male children age 9 - 13 years: 14% had magnesium intakes below the EAR. Female adolescents age 14 - 18 years: 91% had magnesium intakes below the EAR. Male adolescents age 14 - 18 years: 7 8% had magnesium intakes below the EAR. Female adults over 18 years of age: 67% had magnesium intakes below the EAR. Male adults over 18 years of age: 64% had magnesium intakes below the EAR.

Gillis and Gillis 2005 Hamilton No Non-obese and obese children age 5 - 13 years: Over 25% of both Children's non-obese and obese children had magnesium intakes below Exercise and the EAR. Nutrition Ctr.

CSFII = Continuing Survey of Food Intake by Individuals; NHANES = National Health and Nutrition Examination Survey

IV. Review of Studies Used to Set the Dietary Reference Intakes for Selected Nutrients 

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Table IV.6. Derivation of the Estimated Average Requirement (EAR) for Magnesium for Children and Adults

Life Stage Group EAR Method Used to Derive EAR

Young children 1 - 3 years: EARs were based on one magnesium balance study of children 7 to 9 65 mg/day years of age and data from five balance studies of older children and 4 - 8 years: adolescents 10 to 14 years of age, extrapolating based on relative body 110 mg/day weight. Assumed that a positive magnesium balance of 8 to 10 mg/day would result in adequate tissue accretion of magnesium in children 1 to 8 years of age, and that magnesium requirements do not differ by gender. An EAR of 5 mg/kg/day was set for this age group.

Older children 9 - 13 years: EAR was based on three magnesium balance studies of children and 200 mg/day young adolescents 10 to 14 years of age. Assumed that a positive magnesium balance of 8 to 10 mg/day would result in adequate tissue accretion of magnesium in children 9 to 13 years of age, and that magnesium requirements do not differ by gender. An EAR of 5 mg/kg/day was set for this age group.

Adolescents Boys 14 - 18 years: EARs were based on six magnesium balance studies of children and 340 mg/day young adolescents 10 to 14 years of age. Assumed that adolescents Girls 14 - 18 years: would require an additional magnesium intake of 0.3 mg/kg/day to 300 mg/day maintain an adequate positive magnesium balance of 8 mg/day, and that magnesium requirements do not differ by gender. An EAR of 5.3 mg/kg/day was set for this age group.

Adults Men 19 - 30 years: EAR for adult women was based on two magnesium balance studies; 330 mg/day EAR for adult men was based on eight magnesium balance studies. Women 19 - 30 years: Assumed that a zero magnesium balance is adequate for adults over 19 255 mg/day years of age, and that a positive balance is preferred over a negative Men 31 years and balance over time. Also assumed a decline in renal functioning for older: women over 30 years of age, and increased fiber intake for men over 30 350 mg/day years of age. No balance data available for women over 50 years of age Women 31 years and and men over 70 years of age. older: 265 mg/day

IV. Review of Studies Used to Set the Dietary Reference Intakes for Selected Nutrients



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Supplements Reference Data Set Key Results Included?

Suitor and Gleason 2002 CSFII No Female children age 6 - 8 years: 68% had usual vitamin E 1994-1996 intakes below the EAR. Male children age 6 - 8 years: 48% had usual vitamin E intakes below the EAR. Female children age 9 - 13 years: 85% had usual vitamin E intakes below the EAR. Male children age 9 - 13 years: 70% had usual vitamin E intakes below the EAR. Female adolescents age 14 - 18 years: 99% had usual vitamin E intakes below the EAR. Male adolescents age 14 - 18 years: 84% had usual vitamin E intakes below the EAR.

Foote et al. 2004 CSFII No Female adults over 18 years of age: mean probability of 1994-1996 adequacy for vitamin E was 7%. day 1 data only Male adults over 18 years of age: mean probability of adequacy for vitamin E was 14%. Maras et al. 2004 CSFII 1994-1996, with α- No Female adults over 19 years of age: 97 - 98% had usual tocopherol values from vitamin E intakes below the EAR. USDA National Male adults over 19 years of age: 90 - 95% had usual Nutrient Database for vitamin E intakes below the EAR. Standard Reference 15

Devaney et al. 2005 CSFII No FSP participants age 4 - 8 years: 42% had usual vitamin 1994-1996 E intakes below the EAR. FSP eligible nonparticipants age 4 - 8 years: 57% had usual vitamin E intakes below the EAR. Female adolescents age 14 - 18 years: 100% had usual vitamin E intakes below the EAR. Older adult females 60 - 70 years: 95% had usual vitamin E intakes below the EAR. Older adult males age 60 - 70 years: 78% had usual vitamin E intakes below the EAR. Low-income males over 71 years of age: 95% had usual vitamin E intakes below the EAR. Non-low-income males over 71 years of age: 77% had usual vitamin E intakes below the EAR.

Institute of Medicine 2006 CSFII No WIC children age 1 - 1.9 years: 55% had usual vitamin E 1994-1996, 1998 intakes below the EAR. WIC children age 2 - 4.9 years: 47% had usual vitamin E intakes below the EAR. Non-breastfeeding, postpartum adolescent and adult women age 14 - 44 years: 99.8% had usual vitamin E intakes below the EAR. a Vitamin E measured as α -tocopherol equivalents, unless otherwise noted. CSFII = Continuing Survey of Food Intake by Individuals FITS = Feeding Infants and Toddlers Study NHANES = National Health and Nutrition Examination Survey

IV. Review of Studies Used to Set the Dietary Reference Intakes for Selected Nutrients 50

Supplements Reference Data Set Key Results Included?

Ahuja et al. 2004 NHANES 1999-2000, No Children age 1 - 3 years: 81% had usual vitamin E with values for vitamin E intakes below the EAR. as α -tocopherol Children age 4 - 8 years: 75% had usual vitamin E intakes below the EAR. Female children age 9 - 13 years: 97% had usual vitamin E intakes below the EAR. Male children age 9 - 13 years: 91% had usual vitamin E intakes below the EAR. Female adolescents age 14 - 18 years: 99.6% had usual vitamin E intakes below the EAR. Male adolescents age 14 - 18 years: 92% had usual vitamin E intakes below the EAR. Female adults over 18 years of age: 96% had usual vitamin E intakes below the EAR. Male adults over 18 years of age: 90% had usual vitamin E intakes below the EAR.

Moshfegh et al. 2005 NHANES 2001-2002, No Children age 1 - 3 years: 80% had usual vitamin E with values for vitamin E intakes below the EAR. as α -tocopherol Children age 4 - 8 years: 80% had usual vitamin E intakes below the EAR. Female children age 9 – 13 years: 95% had usual vitamin E intakes below the EAR. Male children age 9 - 13 years: 97% had usual vitamin E intakes below the EAR. Female adolescents age 14 - 18 years: > 97% had usual vitamin E intakes below the EAR. Male adolescents age 14 - 18 years: > 97% had usual vitamin E intakes below the EAR. Female adults over 18 years of age: 97% had usual vitamin E intakes below the EAR. Male adults over 18 years of age: 89% had usual vitamin E intakes below the EAR.

Devaney et al. 2004 FITS 2002 Yes Toddlers age 12 - 24 months: 58% had usual vitamin E intakes below the EAR.

Briefel et al. 2006a FITS 2002 Yes Toddlers age 12 - 24 months (supplement users): 9% had usual vitamin E intakes below the EAR. Toddlers age 12 - 24 months (supplement non-users): 65% had usual vitamin E intakes below the EAR.

Briefel et al. 2006b FITS 2002 Yes Hispanic toddlers age 12 - 24 months: 39% had usual vitamin E intakes below the EAR. Non-Hispanic toddlers age 12 - 24 months: 50% had usual vitamin E intakes below the EAR. a Vitamin E measured as α -tocopherol equivalents, unless otherwise noted. CSFII = Continuing Survey of Food Intake by Individuals FITS = Feeding Infants and Toddlers Study NHANES = National Health and Nutrition Examination Survey

IV. Review of Studies Used to Set the Dietary Reference Intakes for Selected Nutrients



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C ONCLUSIONS

iven the importance of nutrient reference standards to the design of food and nutrition assistance programs and policy, it is critical to examine carefully the DRIs Gand findings from dietary assessment studies to determine whether these programs are meeting their nutritional objectives. Moreover, understanding the DRIs is important for applications of the group planning framework, which is based on findings from dietary assessment studies and nutritional goals related to the DRIs (Institute of Medicine 2003). This study provides an in-depth examination of the models and methods used to set the DRIs for food energy and six selected nutrients—zinc, vitamin A, magnesium, vitamin E, fiber, and potassium. It originated in response to the results of recent dietary assessment studies that indicate some substantial inadequacies or excesses in intakes of these nutrients, seemingly unaccompanied by adverse health effects.

Earlier efforts to prioritize nutrients of public health concern required evidence of accompanying biochemical, clinical, or anthropometric adverse health effects. However, given that the DRIs incorporate the goal of reducing the risk of chronic disease (where data are available), rather than simply preventing deficiency, it is possible that short-term measures of biochemical, clinical or anthropometric adverse health effects may not be present even though the long-term health impact may still be important. Nonetheless, some findings from dietary assessment studies suggest dramatic dietary concerns that are not widely acknowledged by the nutrition research and policy community.

Of particular importance for the design and evaluation of food and nutrition assistance programs is the extent to which problems identified in dietary assessment studies represent important public health concerns or are the result of methodological shortcomings in either dietary assessment methods or the DRIs. Three scenarios are possible in interpreting findings of dietary assessment studies:

1. Some DRIs are flawed. In the case of flawed DRI values, results of dietary assessment studies should be interpreted cautiously, and policymakers may want to delay any policy changes or recommendations. A process for revising the DRI based on updated scientific evidence might be the priority. 72

2. The DRI values have a sound scientific basis, but the dietary recall data have limitations. If a probable explanation of dietary assessment concerns is the quality of the dietary recall data—for example, problems measuring vitamin E intakes—caution may also be advised in interpreting the results of the dietary recall studies, and efforts might be directed to improving the quality of the dietary data. 3. Both the DRIs and dietary recall data are considered scientifically sound. When there is confidence in both the DRI values and dietary recall data, dietary problems identified may indicate a real dietary concern, and policy considerations might be warranted—for example, restricting the amount of vitamin A in dietary supplements.

STUDY FINDINGS AND RESEARCH NEEDS This review of the methods and studies underlying the DRIs suggests several issues to consider in interpreting the results of dietary assessment studies (Table V.1). Two general issues apply to all of the nutrients summarized in the table. First, errors in dietary recall data—either underreporting of intakes by adults or overreporting of intakes by young children—partially, but not fully, explain both the inadequacies and excessive intake findings summarized in the table. Second, the lack of sensitive and specific biochemical markers of inadequacy or toxicity for the nutrients in Table V.1 (with the exception of food energy) has resulted in DRIs for these selected nutrients to be based on studies or indicators that are less than optimal.

Food Energy. Recent analyses of usual energy intakes have found that mean usual intake exceeds mean EER for infants and young children by a substantial margin. In a re- analysis of doubly labeled water data measuring TEE, alternative specifications of TEE equations for infants and young children did not produce estimates of EERs that differed substantially from those presented in the IOM macronutrient report. The analysis indicates that other characteristics beyond body weight are significant predictors of TEE. Nonetheless, neither the inclusion of these factors nor a different estimation strategy materially changes the EER predictions.

The finding that the EERs estimated here are similar to those in the IOM report suggests that other explanations drive the large difference between energy requirements and intakes. One possibility would be that intakes truly do exceed requirements by a substantial margin. However, the magnitude of the difference between reported intakes and requirements suggests that this cannot be the only factor. Instead, the reason for the disparity is most likely (1) overreporting of children’s energy intakes, (2) underreporting of children’s weights, or (3) some combination of these two factors.

Zinc. Several studies have found that a high percentage of non-breastfeeding infants and young children have usual intakes of zinc that exceed the UL. The zinc ULs for infants and young children were set to prevent copper deficiency. Yet despite a very high prevalence of usual intakes above the UL, only one documented case of copper deficiency due to excessive zinc consumption has been reported for young children.

V. Conclusions 73

Table V.1. Review of the DRIs for Selected Nutrients: Study Findings and Research Needs Results of Dietary Nutrient Subgroup Assessment Studies Issues for Consideration Food Infants and Mean usual intake > Overconsumption of food and beverages Energy young children EER by substantial Overreporting of consumption margin Underreporting of body weight Zinc Infants and High prevalence of Lack of data on adverse effects of excessive zinc intake young children usual intake > UL Extrapolating the UL upward from the value for very young infants rather than downward from the value for adults Narrow margin between RDA and UL UL for zinc refers to intakes from all foods and supplements, yet adverse effects reported from supplements only Certain fortified foods and dietary supplements for children contain high levels of zinc UL for zinc does not take into account copper intake Overreporting of energy intakes may result in overestimates of zinc intake Preformed Infants and High prevalence of UF used to set the UL for infants is high, but infants and Vitamin A young children usual intake > UL children may be more susceptible to toxic effects Chronic hypervitaminosis A can go unnoticed Certain fortified foods and dietary supplements for children contain high levels of preformed vitamin A Overreporting of energy intakes may result in overestimates of preformed vitamin A intake Magnesium Older children High prevalence of Limitations of balance data in determining magnesium and adults usual intake < EAR requirements Other indicators of magnesium status may improve the accuracy of the EARs Nutrient interactions may affect magnesium requirements Underreporting of energy intakes for adults may result in underestimates of magnesium intakes Vitamin E Children and High prevalence of Lack of dose-response data adults usual intake < EAR Criterion of adequacy used to set EAR may not be a biomarker of vitamin E status Requirements vary based on amount of polyunsaturated fat consumed Current methods of dietary assessment underestimate vitamin E intake Vitamin E values in nutrient databases are highly variable or have been imputed Underreporting of energy intakes for adults may result in underestimates of vitamin E intakes Fiber Children and Mean usual intake Studies used to determine AI based on dietary fiber, yet AI set adults far less than AI for total fiber Effects of fiber may differ between children and adults AI for fiber depends on energy intakes, which are subject to underreporting or overreporting Potassium Children and Mean usual intake Potassium requirements may differ by gender adults far less than AI Effects of potassium may differ between children and adults Lack of dose-response data Effects of potassium on health outcomes may be confounded by other dietary factors

Chapter V: Conclusions 74

The in-depth review and analysis of the methods and studies used to set the UL for zinc suggested several issues to consider: (1) lack of data on the adverse effects of excessive zinc consumption in infants and young children; (2) differences in the ULs when extrapolating upward from the infant value versus extrapolating downward from an adult value; (3) the narrow margin between recommended zinc intake levels and the ULs; and (4) the application of the UL to naturally occurring zinc from food, despite no evidence of adverse effects.

The apparent problem of high zinc intake may be related to the consumption of zinc- fortified foods, particularly infant formula, infant cereals, and ready-to-eat breakfast cereals, some of which contain an amount of zinc that exceeds the UL for this age group. In addition, if parents overreport energy intakes of infants and young children, it seems plausible that the proportions of these subgroups with zinc intakes above the UL are overestimated. With infant formula ranking as the most important source of food energy for infants and ready-to-eat cereals fortified with zinc an important source of food energy for young children, it is likely that zinc intake is also overreported.

To strengthen the basis upon which to re-evaluate the UL for zinc for infants and young children, research is needed to identify (1) improved biomarkers of zinc and copper status, (2) intake levels and sources of zinc associated with adverse effects, and (3) the feasibility of defining a zinc UL that takes into account copper intake. In the meantime, zinc fortification practices and levels of zinc in children’s dietary supplements might be re- evaluated, given their high content of zinc relative to the UL. The potential benefits of adding copper to zinc-fortified ready-to-eat cereals, common practice for infant formulas, could also be explored.

Preformed Vitamin A. Recent dietary assessment studies have shown that substantial proportions of non-breastfeeding infants and young children have intakes of preformed vitamin A above the UL. Although overreporting of intakes likely plays a role, several issues emerged in reviewing the methods used to set the ULs for preformed vitamin A. One is the possibility that the UF of 10 used to derive the UL for infants was set too conservatively, given the empirical findings used to determine the LOAEL and the reversibility of the critical adverse effect (bulging fontanel) on which it is based. The UL for young children was extrapolated from the UL for adults and resulted in a value that is the same as the UL for infants, even though the reference body weight for young children is considerably greater than for infants.

On the other hand, conservatism in setting the UL for preformed vitamin A for infants and children may be warranted. Infants and children are more susceptible to the adverse effects of excess vitamin A than adults, and some infants and young children experience toxicity at levels of preformed vitamin A intake between the UL and LOAEL. Cases of chronic hypervitaminosis A can go unnoticed. While the critical adverse effect for infants (bulging fontanel) is reversible, other adverse effects may be irreversible and little is known about the long-term effects of excessive vitamin A intake on young children.

Dietary supplements and several foods commonly consumed by young children contain large amounts of preformed vitamin A. Data from NHANES III show that about three- quarters of children 1 to 3 years of age who were taking supplements exceeded the UL for

V. Conclusions 75

preformed vitamin A from supplements alone. Daily multivitamins in the dose typically recommended for young children contain an amount of preformed vitamin A in excess of the UL. If the current ULs are accurate, providing supplemental preformed vitamin A may put healthy young children at risk of vitamin A toxicity unnecessarily.

It would be useful to consider the possibility of extending the assessment of vitamin A status (plasma retinyl esters) in NHANES to infants and children under 4 years of age. This may shed light on whether young children are experiencing subclinical or unreported vitamin A toxicity at current levels of preformed vitamin A intake. As with zinc, it might be useful to reevaluate the levels of preformed vitamin A in children’s dietary supplements and fortified foods.

Magnesium. Studies of usual intakes of magnesium suggest that high proportions of older children, adolescents, and adults consume inadequate amounts of this essential nutrient. These results were found for most age and gender subgroups; however, there is a lack of evidence of widespread magnesium deficiency in the general public. The EARs for magnesium were determined on the basis of available balance study findings for subgroups of children and adults.

There are several issues to consider when reviewing the derivation of the EARs for magnesium. In addition to a lack of balance data for multiple age and gender sub-groups, some of the balance studies that were available had significant limitations. More important, however, balance studies may be problematic when used to determine nutrient requirements because they may inaccurately assess nutrient retention. By overestimating intake and underestimating output, the values for nutrient requirements derived from balance studies may be inflated.

New evidence on magnesium requirements based on other potential indicators of magnesium status might be useful for assessing whether the current derivation of the EAR for magnesium is appropriate. Currently, however, it is unclear whether the other indicators of magnesium status discussed in Chapter IV provide more accurate estimates of magnesium status. Furthermore, to accurately estimate average magnesium requirements, it may be important to consider the effects of other nutrients that affect magnesium absorption.

Vitamin E. The diets of nearly all of the U.S. population do not meet current estimates of vitamin E requirements. This can be attributed in part to (1) limitations of the data used to set the EAR, and (2) problems with the assessment of vitamin E intake. The EARs for vitamin E for all age and gender groups were based on one study in adult males that is now more than 40 years old. While it was a long-term experimental study, the subjects were fed large amounts of polyunsaturated fats to increase their vitamin E requirements, and the tests used to determine adequacy were conducted outside the body and have not been correlated with vitamin E deficiency.

Current methods of dietary assessment also tend to underestimate vitamin E intake. Four general sources of error in dietary recalls result in underreporting of vitamin E intakes: (1) disproportionate underreporting of foods with high levels of dietary fat, which also are important contributors of vitamin E; (2) difficulty collecting reliable data on the amounts of

V. Conclusions 76

fats and oils used in food preparation; (3) use of default coding procedures because of lack of information on the specific types of fats and oils consumed; and (4) highly variable and imputed data on vitamin E values in nutrient databases.

Additional research is needed to determine what levels of vitamin E intake promote optimal health across the life span. Vitamin E deficiency is rare, and the challenges to better defining physiologic requirements are great. However, the IOM panel noted that several experimental studies of the effect of various amounts of vitamin E on the reduction of chronic diseases were in progress while the DRIs were being developed. An updated review of results from these studies may provide additional evidence on which to base the DRIs for vitamin E in the future. One question is whether the level of evidence currently available for vitamin E may be more appropriately used to set an AI. Another question is whether the nutrition research community might give high priority to improvements in dietary assessment methodologies with respect to (1) data on fat intake and (2) obtaining additional food composition data for vitamin E.

Fiber. The large gap between current dietary fiber intakes and the AI for fiber implies that most Americans do not consume enough fiber. The AI for fiber—14 g of total fiber per 1,000 kcal per day—was determined on the basis of studies that found an association between high intakes of dietary fiber and significant reductions in CHD risk among adults. The average dietary fiber intake that was associated with maximal CHD risk reduction in these studies was 14 g per 1,000 kcal per day. Since the AI includes both dietary and functional fiber, an even larger share of individuals is not consuming the amount of dietary fiber considered optimal according to the findings of these studies. Overall, little is known about the exact relationship between total fiber (dietary fiber plus functional fiber) and heart disease, diabetes, cancer, or other chronic health conditions that affect the health of a large share of the U.S. population.

One important issue is whether CHD risk is an appropriate criterion for determining recommended fiber intakes for all life stage groups. The AI for fiber was based on studies in adults between the ages of 37 and 75 years, and data were not available to determine whether fiber needs relative to total energy differ for younger adults or children. Because the risk for most chronic degenerative diseases increases with age, it is possible that the optimal intake of fiber as a function of energy intake is lower for younger adults and children. The method used to set the AI may also have overstated the optimal fiber intake for people who consume less than the median energy intake for their age-gender group.

The review suggests that the current recommendation for fiber intake could be revisited and that our understanding of the relationship between total fiber and health outcomes for children, adolescents, and adults would benefit from further research. In particular, additional dose-response data are needed to ascertain the level of fiber intake required to promote normal laxation in children. This would enable the amelioration of constipation to be explored as an alternative endpoint to the reduction of CHD risk for determining recommended fiber intakes for children. In the meantime, researchers and practitioners may want to individualize their estimates of fiber needs by using actual energy intakes (and 14 g

V. Conclusions 77

per 1,000 kcal), rather than the AIs for an entire life-stage group. Finally, studies that assess total fiber intakes would be useful in making comparisons to the current AI for fiber.

Potassium. Studies that have assessed the usual intake of potassium in the U.S. population suggest that most children, adolescents, and adults have intakes of potassium that fall far below the AI. While widespread evidence of potassium deficiency is lacking, habitually low levels of intake could play a role in the prevalence of certain chronic health conditions that have been tied to potassium intake such as salt sensitivity, high blood pressure, and kidney stones.

The relationship between potassium and health outcomes also requires further study. More research is needed to better understand the effects of potassium on health outcomes, independent of its correlation with potential confounding factors, and whether these effects vary between children and adults. Studies are also needed to determine whether optimal potassium intake differs among various subgroups (for example, by gender) and to establish levels of potassium intake that would be best for most people. To this end, dose-response trials would be useful in determining the effect of multiple levels of intake on various health outcomes.

CONCLUDING DISCUSSION Development of the DRIs was an intensive effort to advance our knowledge and documentation of nutrient requirements. This effort spanned more than a decade and involved IOM panels of experts who reviewed and synthesized the scientific research and data on nutrient function and absorption, effects of inadequate or excessive intakes, potential indicators of inadequate or excessive intakes, and other factors that may influence requirements. In many instances, available data were often sparse or drawn from studies with significant limitations, and only limited evidence was available to guide the development of specific DRIs. The panels often pieced together many data sources and studies to produce a synthesis that represented their best knowledge of the human requirements for nutrients. Thus, although governed by scientific rationale, informed judgments were often required in setting these nutrient reference values.

Policymakers, nutrition and public health researchers, and the professional dietetics community need to understand the issues involved in deriving the DRIs and how to interpret the results of studies assessing nutrient adequacy using the DRIs. This study is a first attempt to undertake such a critical look and to identify and document the factors that explain the study results.

V. Conclusions

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