Symposium

The Importance of Context in Choosing Nutritional Indicators12 HABICHT3 AND DAVID L. PELLETIER4

3Diuision of Nutritional Sciences, Sauage Hall, Cornell University, Ithaca, NY 14853 "Corne// Food and Nutrition Policy Program, Division of Nutritional Sciences, Sauage Hall, Cornell university,

Ithaca, NY 14853

cause of the failure to recognize that the definition of the best indicator depends entirely on the purpose for which it is intended. This paper considers indicator applications in a broader conceptual framework than has been the case to date and illustrates how this broader conceptual ization affects the choice of indicators in the most common applications. Because this review focuses on indicators of nutri tional deficiency, and not of excess or of imbalance, the examples in this paper are drawn from consider ations of food or nutrient insufficiency. However, all the considerations pertain equally to indicators of en ergy and nutrient excess and other dietary inadequa cies. For succinctness, we call energy a nutrient, even though that is biochemically incorrect,- and we refer the reader elsewhere for background on the indicator characteristics of sensitivity, specificity, positive pre dictive value (1), and of reliability and its components, precision and dependability (2).At the editor's bidding we have tried to restrict our references to our own work.

ABSTRACT Nutritional indicators are used to screen, diagnose, and evaluate interventions in individuals. They are also used in populations to ascertain and place under surveillance the magnitude of nutritional prob lems, their location and causes, and to evaluate the impact of programs and policies. Nutritional indicators are also used for research to make inferences about biological and social mechanisms affecting or being af fected by nutrition. All these activities include mea surements of nutritional indicators, but the choice of indicators, their measurements, analyses, and the need for other data can be very different for inferences from research, for patient management, for making public policy, or for planning or evaluating programs. There is no best indicator, best measure of an indicator, or best analysis of an indicator in a generic sense. The definition of "best" depends ultimately on what is most appropriate for the decision that must be made. This paper gives examples. J. Hutr. 120:1519-1524,1990. INDEXING KEY WORDS:

•decision making •risk factors •nutrition •data collection

social justice

' Presented as part of a conference, "Nutrition Monitoring and Nutrition Status Assessment", at the first fall meeting of the Amer

There has been extensive research, and at times, lively debate in the literature related to the identifi cation of nutritional indicators. Much of this literature reflects a desire to identify an indicator that is, in some sense, the "best" indicator of nutritional status with reference to a given nutrient of concern. Measures of nutritional determinants or conse quences are used in applied settings at the individual level (as in patient diagnosis, screening, and monitor ing) or at the population level for setting policy, in program evaluation, and in nutritional surveillance. It is in these applications that these nutritional vari ables are referred to as nutritional "indicators." Un fortunately, much of the development and use of nu tritional indicators has fallen short of its potential be

0022-3166/90

S3.00 ©1990 American Institute of Nutrition.

ican Institute of Nutrition, Charleston, South Carolina, December 8-10, 1989. The conference was supported in part by cooperative agreement HPU880004-02-1 with the DHHS Office of Disease Pre vention and Health Promotion, the USDA Human Nutrition In formation Service, the DHHS National Center for Health Statistics, and the International Life Sciences Institute-Nutrition Foundation. 1 The Planning Committee for the meeting consisted of Drs. Helen A. Guthrie, Roy J. Martin, Linda D. Meyers, James A. Olson, Catherine E. Woteki, and Richard G. Allison (ex-officio). The sym posium papers were edited by a committee consisting of Dr. James Allen Olson (coordinator), Dept. of Biochemistry & Biophysics, Iowa State University, Ames, IA; Dr. Cathy C. Campbell, Division of Nutritional Sciences, Cornell University, Ithaca, NY; Dr. Roy J. Martin, Dept. of Foods &.Nutrition, University of Georgia, Athens, GA; and Dr. Catherine E. Woteki, Food & Nutrition Board, National Academy of Sciences, Washington, DC.

Received 10 December 1989. Accepted 11 July 1990.

151?

Downloaded from https://academic.oup.com/jn/article-abstract/120/suppl_11/1519/4738643 by University of Glasgow user on 09 September 2018

JEAN-PIERRE

1520

HABICHT

AND PELLETIER

OBJECTIVES FOR SELECTION OF NUTRITIONAL INDICATORS

TABLE 1 Informational

content

of indicators

to meet objectives

Informational content

ObjectiveIndicate Prevent malnutrition Treat malnutrition Treat consequences Evaluate treatment Research (used as an outcome variable) Promote equity Nutrition education

risk1

benefit to intervention Indicate harm2Predict from interventionResponsiveness or determinantIndicate

normalcy

X X

1Refers to the risk of future malnutrition or its consequences. 2 Refers to harm caused by past malnutrition.

X

X X X

Downloaded from https://academic.oup.com/jn/article-abstract/120/suppl_11/1519/4738643 by University of Glasgow user on 09 September 2018

Nutritional indicators have been classified histori cally as biochemical, clinical, anthropométrie,and di etary, and this is appropriate when considering the human resources and facilities necessary to use these indicators. However, this classification reveals little about the usefulness of indicators to meet the objec tives that they are to serve. This is better achieved by classifying indicators according to what they reveal— harm or risk of present harm, risk of future harm, benefit from an intervention, response to that inter vention, or some idea about "normality." Some of these concepts have recently been applied to the as sessment of malnutrition in women (3) and are ex tended and elaborated on below for the more general case of malnutrition in populations. Table 1 presents some objectives for which nutri tional indicators are used. Some kinds of indicators are more useful in meeting some objectives than oth ers. Although the objectives are not mutually exclu sive, the indicator requirements for meeting one ob jective may be incompatible with meeting others. If the objective is to identify persons or populations to prevent malnutrition, the indicator must be a good indicator of risk of future malnutrition. In dealing with individuals, this indicator is usually not the nu tritional status of the individual, which usually changes too late for preventive intervention. Thus, measures of predisposing socioeconomic and dietary factors, or reflections of such factors such as a mother's or sibling's nutritional status, are often used. On the other hand, indicators of nutritional status of sentinel individuals are useful in populations; for instance, to trigger famine prevention on the basis of wasting (4). Not only must the indicator be a good indicator of risk, but it must also predict benefit, i.e., that the in

tervention will, in fact, prevent malnutrition. In Gua temala it was found that maternal height was a good predictor of small size in the second year of life stature, but this indicator was useless as a predictor of benefit in growth from infant supplementation. A mother's thinness or socioeconomic status were much better indicators (5). If the objective is to identify persons or populations who are presently malnourished so as to prevent the consequences of malnutrition, the usual best choice is an indicator of nutritional status. It is also important that the indicator be a good predictor of response to the intervention. In an example given below about the effect of supplementation on birthweight, both pop ulations had energy intakes considerably less than the recommended energy intakes, but the activity levels were very different. One population was thin and the other was not. Therefore, energy intake was a poor measure of deficiency, and thus, a poor predictor of benefit from a nutritional intervention, whereas mea sures of thinness would have been more appropriate. If the objective is to identify persons or populations who already suffer the consequences of malnutrition, to institute non-nutritional interventions to remedy the harm, one may screen on the consequences so long as the remedy is effective in overcoming harm from nutritional and non-nutritional causes. For instance, psychological stimulation may be beneficial for slowly developing children whatever the cause. When, how ever, the relative contribution of nutrition to the harm is important in deciding on action, then many of these "functional" indicators lack enough specificity to be useful. For the evaluation of individual treatment, program outcomes, or research, an outcome indicator must have the potential to respond to a nutritional inter vention or determinant in a fashion that can be identified with good statistical power. Usually these

1521

NUTRITIONAL INDICATORS: CONTEXT TABLE 2

Responsiveness of anthropométrie indicators to proteinenergy supplementation from birth to 3 y of age1

Indicator

Response (d)

Standard deviation (SD)

Responsivensss d/SD

AttainedWeight, kgHeight, cmArm cmTriceps circumference, mmSubscapular skinfold, skinfold, mm0.92.3.35.1501.33.9.901.11.1.69.59.39.14.00 1In children who would otherwise

have a deficit of 4.5 kg of

weight at age 3 and who consumed 15% of their energy and 26% of their protein from the supplement (7).

that is not per se an indicator issue. More importantly, some indicators are slower to respond than others. In iron nutrition, the hemoglobin content of red blood cells does not change once the cell is mature. The turnover of these mature cells takes months, so that one generally sets 3 mo as a minimum duration of an iron supplementation field trial to ascertain its effect on anemia. Free erythrocyte protoporphyrin, on the other hand, responds more quickly to iron repletion. Another less commonly understood example is that low birthweight in malnourished populations is due to both malnutrition during pregnancy and to small maternal stature, which is a consequence of malnu trition during childhood and adolescence. Thus, an in tervention to fully normalize birthweight patterns in a malnourished population must last 30-40 y, and an evaluation of such an intervention must take this lag into account. 4) Age-specificity of response is important for some indicators. Thus, stunting in response to diarrhea is greater at younger ages (10). Response to supplemen tation is not quite so predictable (11) because it de pends on other factors affecting nutrient balance, such as diarrhea and home diet. A criterion of the success of this conference would be the emergence over the next few years of a listing of responsiveness of all the indicators of nutritional status discussed here based on interventions in both clinical and field settings. For a given indicator, re sponsiveness will be better for monitoring change within individuals than it is for monitoring population changes through cross-sectional surveys, because the SDs are different even though the expected change may be the same. However, this can be compensated for by increasing sample sizes. This responsiveness data is essential for deciding on the usefulness of response indicators and for calculating sample sizes (6) in plan ning surveys and studies.

Downloaded from https://academic.oup.com/jn/article-abstract/120/suppl_11/1519/4738643 by University of Glasgow user on 09 September 2018

indicators are measures of dysfunctions caused by in adequate nutrient supply to the cells, or they are mea sures of nutrient content or stores in the body. Such measures of nutrient availability in the body are in dicators of nutritional status. Measures of the harmful consequences of malnutrition (usually called "func tional" consequences) can also be considered indica tors of nutritional status. Determinants of this nutri tional status, such as dietary intake or diarrhea, by contrast, are nutritional indicators but are not indi cators of nutritional status. Responsiveness of an indicator may be calculated as d/SD, the difference (d) expected from an interven tion over the standard deviation (SD) within compar ison groups. That ratio is simply the standardized dif ference or Z-score. This measure of responsiveness combined with sample size is directly related to sta tistical power (6). For instance, responsiveness divided by the square root of the sum of the sample sizes of two comparison groups is a t-test. The larger the SD, the less responsive the indicator for a given change. This is more likely with indicators that are affected by many other factors besides nutri tion. Thus most functional indicators of nutritional status are unresponsive because their SDs are large due to the many other factors influencing them besides nutrition. Table 2 presents the responsivenesses of some an thropométrie indicators to protein-energy supple mentation in a field study. A wide range of indicators is presented elsewhere (8) with a closely related but less comprehensive index of responsiveness. Such a table must present information on the following fac tors that affect responsiveness: 1) The degree of the deficiency. A classic example of not taking this factor into account was the confu sion in interpreting the response in birthweight to en ergy supplementation among the thin, undernourished women in Guatemala in contrast to no response among heavy, even obese women in Harlem, NY. 2) The dose of the intervention. Some indication of dose is necessary even though this is difficult to stan dardize because there is often ambiguity about which component of the intervention is responsible for the effect, as in the study described in Table 2—isit pro tein or energy or both? Where there is no ambiguity as to that dose, it would appear that the calculation of responsiveness should use d' instead of d (response), where d' = d/dose. For instance, calculating d' for weight in Table 2 results in a responsiveness of .046/ percent energy intake. That has not been done in Table 2 because the response to the dose depends on the de ficiency and, in fact, in this population the deficiency was severe enough and the range of the dose broad enough so that one can see that the dose response is not linear (9). 3) The duration of the intervention. Often duration is important to achieve an adequate dose response, but

1522

HABICHT

AND PELLETIER

represent completely equitable standards of diet. At tempts at defining "hunger" (15) and "food insecur ity", and then finding appropriate feasible indicators to measure these realities (16) is more promising. In developed countries these indicators will probably turn out not to include the classical nutritional indi cators, such as the nutrients in the diet or growth measures, but will include perceptions about food availability, and behaviors that respond to those per ceptions. Once nutritional indicators of equity are es tablished, the appropriate nutritional indicators may be usefully judged against normative standards. Similarly, the WHO/NCHS medians of stature pro vide an excellent bench mark by which to judge nu tritional adequacy of populations in developing coun tries, because the genetic variation in stature up to 7 y of age is negligible compared with that caused by inequitable availability of food and sanitary environ ment (17). Normative standards are also useful for ed ucation. The normative WHO/NCHS growth stan dards are used in "growth monitoring" to educate and motivate mothers to promote good growth in their children by providing them with good nutrition (18). The RDAs are used in nutrition education in the United States, although there is some question about how realistic are such standards. They are by design in excess of any biological needs and are probably in excess of palatability and financial feasibility for much of the population. CHARACTERISTICS OF NUTRITIONAL INDICATORS FOR DIFFERENT APPLICATIONS Meeting the objectives listed in Table 1 ultimately requires making decisions to intervene, and these de cisions are made on the basis of certain kinds of data collecting and interpretive activities listed in Table 3 under "applications." The same activity can be con ducted but to meet different objectives. Thus, one may screen children to prevent malnutrition or to promote equity. The activity is the same although the indicators measured may be different. There is symmetry in Table 3 between the activities for decisions about individuals and for those about populations. Screening of individuals and targeting of populations for interventions are similar activities in that they determine who will receive an intervention. The only difference is that indicators of past harm are poor indicators to target preventive interventions for individuals, but may be good proxies for present and future harm in populations. Thus, infant mortality and stunting data are particularly useful for population targeting. This needs to be emphasized because it is occasionally misinterpreted in policy circles that in dicators of past nutritional status are not useful for such purposes.

Downloaded from https://academic.oup.com/jn/article-abstract/120/suppl_11/1519/4738643 by University of Glasgow user on 09 September 2018

To improve the plausibility that the intervention caused the final outcome in nutritional status, other indicators of independent, confounding, or mediating nutritional determinants also need to be measured (e.g., dietary intake). Although not pertinent to the choice of indicators, it can never be repeated enough that measurement, however well done on the appropriate indicators, is never sufficient to show a cause-effect relationship. An appropriate experimental design is essential (12). This is particularly important when other factors affect the indicator besides nutrition that, for instance, is particularly the case for functional indicators. For most objectives for which indicators of nutri tional status are used in populations, normative in dicators are poor indicators of harm, risk, or benefit. A normative indicator is a measure that is judged rel ative to the distribution of its values in healthy pop ulations, which constitutes a standard, for example the World Health Organization/National Center for Health Statistics (WHO/NCHS) standards for growth. These standards give percentiles of likelihood (e.g., the 5th percentile) of being healthy (specificity distri bution), but give no information as to the likelihood of being malnourished (positive predictive value) if an individual falls below the cut-off percentile (e.g., the 5th) because the positive predictive value will vary from population to population (1). So, for individuals, normative standards have no intrinsic meaning relative to physiological malnutrition. Their meaning is pop ulation-specific depending on the prevalence of mal nutrition in that population. On the other hand, there are techniques to estimate proportions of a population that lie outside the healthy population (13) to make prevalence estimates of the unhealthy. Some normative standards are determined on other bases, such as a standard of decent food or the Rec ommended Daily Allowances (RDAs). These standards give no insights even to specificity, much less to sen sitivity or positive predictive value for identifying malnourished individuals, or for coming to any bio logical insights about populations. A recent new pro cedure (14) permits dietary information to be used as an indicator of risk in populations, but this procedure requires knowledge about the distribution of human requirements and is otherwise not related to the RDAs (which cannot be used for this purpose). The RDAs are, however, the only criteria available for judging equity and they are appropriate for this purpose. Normative standards of an appropriate and decent diet, which are reliable, available, and accessible, should be a minimum criterion of equity in developed countries. These standards should, of course, not be based solely on biological considerations and will vary across cultures. Such standards exist in the United States, for instance the USDA regulations about WIC or the School Lunch program, although they have not been formulated so explicitly and therefore do not

NUTRITIONAL

INDICATORS:

1523

CONTEXT

TABLE 3 Necessary

indicator

Only related to nutrient content of the body Applications

Categorical

for applications

Also related to risk, harm, benefit, or response1 Linear

Categorical

Temporal relationship for indicator of harm Past

X X X

X X X

X X X X

X X X

Present

Future

X X X

X X

X X X X

See Table 1.

Similarly, diagnosis in individuals and populations are both concerned with identifying the causes of harm or of future harm. However, there is a conceptual dif ference between what one seeks in making a diagnosis in individuals than in populations, which has impor tant implications for the non-nutritional variables collected. In individuals, the major emphasis is to ex clude diagnoses other than malnutrition, so the vari ables collected relate to these other possibilities. This is conceptually no different than screening. In popu lations, previous or concurrent assessment already identifies malnutrition as a problem. The diagnostic step is to elucidate its causes, such as unstable food sources and inadequate income, high prices of necess ities, and inadequate education, so as to deal with them in setting policy and in planning programs. These causes are more distal than those of concern to clini cians and entail different data needs. Monitoring has similar purposes for both individ uals and populations; to see whether the evolution of nutrition is proceeding satisfactorily and to predict its future evolution. The indicators used are often the same in individuals and in populations, but in the lat ter case indicators of past harm (e.g., attained height as a measure of past stunting) can be usefully compared over time, which is generally not a concern in clinical nutrition. In Table 3 we have differentiated between the use of categorical (usually dichotomous) and con tinuous variables. The choice between a dichotomous and continuous variable depends on the decision to be made from the data. One consideration is whether the decision is based on classifying individuals as mal nourished, or on statistical tests of differences using continuous measures. In general, for screening and diagnosis in the indi vidual or for the traditional method of counting the malnourished in a population, one is making a di chotomous choice on the basis of a cut-off value. In such a case, the sensitivity-specificity characteristics

of that value are more important than any other char acteristics (1) once a cut-off value is chosen. For use in the individual, the selection of that value depends not only on the biology and epidemiology of the relationship between the indicator and the nutri tional deficiency, but also on the relative costs of falsenegative and false-positive diagnoses and the resources at hand for the intervention. These are quite different considerations than in choosing the cut-off point to count the malnourished in a population where only the prevalence of malnutrition itself, coupled to the sensitivity-specificity information, determines the best cut-off for targeting interventions to that population or for monitoring changes in prevalence (19). Here "best" is defined relative to statistical power to iden tify a change. Unfortunately these best cutoffs often do not correspond to the conventional ones, so that statistical tests must be done with one set of cut-off points whereas another set is used for presentational purposes. However, for most such decisions and for research, counting the malnourished is usually statistically less powerful than using a continuous indicator of nutri tion if such is available. Of course, dichotomous data (e.g., proportion of malnourished using conventional cut-offs) need to be presented to be understood by most public policy decision makers. Not only must the indicator be continuous but it must also be linearly related to the underlying nutri tion or to the nutritional risks or consequences of con cern. Many continuous nutritional indicators do not show this linearity. For instance, the relative dose re sponse (RDR) is curvilinearly related to vitamin A liver stores in humans (20). This does not impair its value as a classifying measure, but some other expression will be required to obtain linearity. Promising candi dates all include in the denominator the dose induced change in serum vitamin A, a measure that is in the numerator of the RDR.

Downloaded from https://academic.oup.com/jn/article-abstract/120/suppl_11/1519/4738643 by University of Glasgow user on 09 September 2018

For individuals Screening Diagnosis Monitoring For populations Assessment Targeting Diagnose causes Monitoring

Linear

characteristics

1524

HABICHT

AND PELLETIER

SUMMARY

Nutritional indicators are required and used by a diverse group of professionals—researchers, planners, and policy makers within and outside public health, program managers, and clinical practitioners. The range of objectives to which indicators are applied is correspondingly diverse. This paper has attempted to show that nutritional indicators have a variety of at tributes and that the attributes of crucial importance for one set of objectives and applications may be ir relevant for another. The close link between the con text within which indicators are used and the criteria on which indicators should be chosen is generally not well appreciated by various categories of users. The result has often been misapplication or misinterpre tation of indicators for policy making, clinical practice, research, and evaluation. This situation is likely to continue until the assumed existence of universally best indicators is replaced by more careful consider ation of the purpose for which they are needed in each case.

LITERATURE

CITED

1. HABICHT,J-P., MEYERS,L. D. & BROWNIE,C. (1982) Indicators for identifying and counting the improperly nourished. Am. ]. Clin. ÑutÃ-.35: 1241-1254. 2. MARKS, G. C., HABICHT, J-P. & MUELLER, W. H. (1989) Reliability, dependability, and precision of anthropométrie measurements. The Second National Health and Nutrition Ex amination Survey 1976-1980. Am. /. Epidemial. 130: 578-587. 3. RASMUSSEN, K. M. & HABICHT,J-P. (1989) Malnutrition among women: indicators to estimate prevalence. Food Nutr. Bull. 11 (4): 29-37.

4. BROOKS,R. M., HABICHT,J-P. & WILLIAMSON, D. F. (1990) Timely Warning and Intervention Systems (TW1S) for Periodic

Food Consumption Shortages: Experience from Indonesia. Cor nell International Nutrition Monograph Series, No. 22, in press. 5. ROTHE, G. E. (1988) Determinants of response to supplemen tation in malnourished Guatemalan children. M. S. thesis, Cor nell University, Ithaca, NY.