ASSESSMENT OF NUTRITIONAL STATUS

ASSESSMENT OF NUTRITIONAL STATUS. Nutritional status is the balance between the intake of nutrients by an organism and the expenditure of these in the processes of growth, reproduction, and health maintenance. Because this process is highly complex and quite individualized, nutritional status assessment can be directed at a wide variety of aspects of nutriture. These range from nutrient levels in the body, to the products of their metabolism, and to the functional processes they regulate. Nutritional status can be measured for individuals as well as for populations. Accurate measurement of individual nutritional status is required in clinical practice. Population measures are more important in research. They can be used to describe nutritional status of the group, to identify populations or population segments at risk for nutrition-related health consequences, and to evaluate interventions.

The choice of nutritional status assessment method must be made mindful of the level at which one wants information, as well as of the validity and reliability of the method. All methods have error. All methods produce imperfect measures that are indirect approximations of the process. Whatever method is chosen for assessment of nutritional status, the data obtained must be compared with reference data to produce an indicator of nutritional status. The quality of the available reference data is, therefore, another factor that affects the assessment data.

Ideal methods are sensitive and specific. Unfortunately, it is difficult to achieve both in the assessment of nutritional status. Sensitivity refers to the ability of a technique to correctly identify those affected by a condition (for example, undernutrition) as having that condition. Specificity refers to the ability of a technique to correctly classify normal individuals as having normal nutritional status. Body mass index (wt/[ht]²) is a global measure of nutritional status that illustrates the difference between these two constructs. Most persons who consume insufficient energy have low body mass index, so the measure is sensitive. However, there are other causes of low body mass index, including genetics and disease, so body mass index is not specific to nutritional status.

The assessment of nutritional status is commonly summarized by the mnemonic "ABCD," which stands for anthropometric measurement, biochemical or laboratory tests, clinical indicators, and dietary assessment. This review will focus on anthropometric and dietary techniques.

Anthropometric Approaches to Nutritional Status Assessment

Anthropometric approaches are, for the most part, relatively noninvasive methods that assess the size or body composition of an individual. For adults, body weight and height are used to evaluate overall nutritional status and to classify individuals as at healthy or nonhealthy weights. In the United States of America and other industrialized countries, the emphasis for unhealthy weight is over-weight and obesity. The standards for these have changed over time. The most recent classification is to use body mass index (BMI, in kg/m²) (Kuczmarski and Flegal, 2000). BMI, regardless of age or population, is normal at 18.5 to 25.0 kg/m², overweight at 25.0 to 29.9 kg/m², and obese at over 30.0 kg/m² (USDA & USDHHS, 2000). In general BMI greater than 30 is assumed to be due to excessive adiposity.

In children, growth charts have been developed to allow researchers and clinicians to assess weight-and height-for-age, as well as weight-for-height. For children, low height-for-age is considered stunting, while low weight-for-height indicates wasting. In addition to weight and height, measures of mid-arm circumference and skinfold measured over the triceps muscle at the mid-arm are used to estimate fat and muscle mass. Anthropometric measures of nutritional status can be compromised by other health conditions. For example, edema characteristic of some forms of malnutrition and other disease states can conceal wasting by increasing body weight. Head circumference can be used in children 36 months and younger to monitor brain growth in the presence of malnutrition. Brain growth is better spared than either height or weight during malnutrition.

To interpret anthropometric data, they must be compared with reference data. The choice of the appropriate reference has been discussed by Johnston and Ouyang. Because well-nourished children in all populations follow similar patterns of growth, reference data need not come from the same population as the children of interest. It is of greater importance that reference data be based on well-defined, large samples, collected in populations that are healthy and adequately nourished. Reference growth charts (Kuczmarski et al., 2002) have been compiled from cross-sectional data collected from population surveys of U.S. children. These have been adopted as international standards by the World Health Organization.

Choosing a Dietary Approach to Nutritional Status Assessment

Several techniques exist for collecting dietary data with which to estimate nutritional status. Because these techniques vary in cost for data collection, burden on the respondent, and which aspects of diet they are designed to measure, it is important to clearly articulate the goals of dietary assessment of nutritional status before choosing an assessment strategy.

The primary consideration in choosing a dietary assessment method is the specific type of data needed. Is the research intended to document intake of "foods" or of "nutrients"? If the answer is foods, the method must take account of the population's foodways. These include variability in food intake patterns (for example, day-today, seasonal, ritual cycles); differences in food consumption by sex, age, and ethnicity; and what items the population considers to be legitimate "food." If the objective is to measure nutrient intake, the method must take into account several additional factors: food preparation techniques, including the addition of condiments and the effects of the technique on nutrient composition of the food; sources of error in the determination of amounts of foods consumed; differentiation distribution of nutrients among foods; and the contribution of "non-food" consumption (such as betel nut, laundry starch, and vitamin and mineral supplements) to total nutrient consumption.

Another important consideration is the time period the data are intended to represent. If the period is a relatively discrete one, it may be possible to document diet quite precisely. However, if the interest is in measuring "usual" diet, the methods must allow this abstract concept to be estimated statistically.

Population measures of dietary status can be derived either from data describing the entire population or population sub-group, or from data describing samples of individuals. Population-wide data include food availability figures, which allow the assessment of food balance—the amount of food produced or imported by a population less that exported or used as nonhuman food. Such measures are necessarily crude, as they do not measure consumption directly. Another approach to measuring dietary status of groups has been to focus on the household. Indirect data on household food intake can be derived from records of foods brought into the household or from pantry inventories. Because of variations in intrahouse-hold distribution of foods, such techniques cannot be used to estimate individual intakes.

By far the most precise way of measuring dietary intake is to gather data on individuals. These methods depend on identifying a period of time for which data are needed, measuring food quantities consumed, and then translating these into nutrient amounts, either through direct chemical analysis or (more commonly) using food composition tables.

Common Methods for Dietary Data Collection

The most valid, or accurate, dietary methods are prospective methods. These involve keeping records of foods consumed over the period of time of interest. This can be done by individuals themselves, or by others observing them. Sometimes the foods are weighed before eating and then plate waste is weighed and subtracted. A similar method is to prepare two duplicate meals; one is consumed by the subject and the other is analyzed for nutrient content. Another method is the dietary record, in which the subject records estimated amounts of foods consumed. In any case, these methods are highly reactive because individuals may alter usual behavior to make their diet more socially desirable or to simplify the process of record keeping.

Recall methods are the most widely used type of dietary data collection method. They are less reactive, but also less accurate than record methods. Twenty-four hour recalls, in which the previous day's intake is queried in detail (for instance, foods, amounts, preparation techniques, condiments) are easiest for individuals to complete. The data reported are converted from foods to nutrients with the use of food composition tables. Because a single day is not representative of usual intake, multiple twenty-four hour recalls are frequently used. These multiple recalls can be thought of as sampling from an individual's ongoing food behavior. The number necessary to reliably measure diet depends on the nutrient of interest. Nutrients widely distributed in food (such as carbohydrates) require fewer days than nutrients not widely distributed (such as cholesterol). The number of recalls needed also depends on the nature of the diet. In societies where day-to-day and season-to-season food intake varies, more days are needed than where diets are more monotonous.

The semiquantitative food frequency is a recall method in which an individual summarizes the diet to produce a measure of usual intake. For a list of foods commonly eaten, the individual estimates how frequently the food has been eaten in the time period in question (often, one year) and in what amount. Food composition tables are then used to estimate the usual daily intake. This method combines low burden on the individual with low cost. It has been widely used and studied, as it is the foremost method used in nutritional epidemiology. Research has examined how best to formulate a list of foods, how to present the foods to the subject, and whether portion sizes should be included.

Because the act of estimating frequency of intake is assumed to be based on cognitive processes, research has examined how best to maximize reliability and validity of food frequency data by focusing on the cognitive tasks experienced in the course of completing a food frequency questionnaire. This includes questions such as whether a long list of individual foods should be presented (for example, skim milk, 2 percent milk, whole milk) or whether foods should be nested (for example, questions about the presence or absence of milk in the diet separated from the variety of milk). The results of these analyses have been mixed but suggest that incorporation of formatting changes based on cognitive theory will enhance the accuracy of reporting.

There has also been recent discussion of the actual task of summarizing and estimating intake experienced by the subject. The traditional explanation that persons completing a food frequency questionnaire actually retrieve and integrate past behavior to achieve an average dietary intake has been challenged by arguments that persons answer food frequency questionnaires in terms of a composite image of themselves and their diet, rather than a statistical estimate. If the latter is the case, one might expect that attempts to minimize error will reach a threshold of error that is unlikely to be crossed without a major conceptual shift in dietary data collection techniques for nutritional status assessment.

See also Caloric Intake; Dietary Assessment; Food Consumption Surveys; Nutrition.

BIBLIOGRAPHY

Beaton, G. H., J. Milner, P. Corey, V. McGuire, M. Cousins, E. Stewart, M. de Ramos, D. Hewitt, P. V. Grambsch, N. Kassim, and J. A. Little. "Sources of Variance in 24-hour Dietary Recall Data: Implications for Nutrition Study Design and Interpretation." American Journal of Clinical Nutrition 32 (1979): 2546–2549.

Buzzard, Marilyn. "24-Hour Recall and Food Record Methods." In Nutritional Epidemiology, 2d ed., edited by Walter Willett. Oxford: Oxford University Press, 1998.

Drewnowski, Adam. "Diet Image: A New Perspective on the Food-Frequency Questionnaire." Nutrition Reviews 59 (2001): 370–372.

Dwyer, Johanna. "Dietary Assessment." In Modern Nutrition in Health and Disease, 9th ed., edited by Maurice E. Shils, James A. Olson, Moshe Shike, and A. Catherine Ross. Baltimore: Williams and Wilkins, 1999.

Johnston, Francis E. "Reference Data for Physical Growth in Nutritional Anthropology." In Training Manual in Nutritional Anthropology, edited by Sara A. Quandt and Cheryl Ritenbaugh. American Anthropological Association, Special Publication no. 20, 1986.

Johnston, Francis E., and Z. Ouyang. "Choosing Appropriate Reference Data for the Anthropometric Assessment of Nutritional Status." In Anthropometric Assessment of NutritionalStatus, edited by John H. Himes. New York: Wiley-Liss, 1991.

Kuczmarski, Robert J., and Katherine M. Flegal. "Criteria for Definition of Overweight in Transition: Background and Recommendations for the United States." American Journal of Clinical Nutrition 72 (2000): 1074–1081.

Kuczmarski, Robert J., C. L. Ogden, and S. S. Guo. 2000 CDC Growth Charts for the United States: Methods and Development. National Center for Health Statistics. Vital Health Statistics 11 (246), 2002.

Quandt, Sara A. "Intracultural Variation in American Infant Diet: Patterns in Diversity and Consequence for Research Design." American Behavioral Scientist 31 (1987): 250–265.

Thompson, F. E., A. F. Subar, C. C. Brown, A. F. Smith, C. O. Sharbaugh, J. B. Jobe, B. Mittl, J. T. Gibson, and R. G. Ziegler. "Cognitive Research Enhances Accuracy of Food Frequency Questionnaire Reports: Results of an Experimental Validation Study." Journal of the American Dietetic Association 102 (2002): 212–225.

U.S. Department of Agriculture and U.S. Department of Health and Human Services. Nutrition and Your Health: Dietary Guidelines for Americans. Washington, D.C.: U.S. Government Printing Office, 2000. Home and Garden Bulletin No. 232.

Willett, Walter. Nutritional Epidemiology, 2d ed. Oxford: Oxford University Press, 1998.

Sara A. Quandt