Distinguishing Betweem Two Different Kinds of Consumer Nutrition Knowledge

ABSTRACT - In measures of consumer nutrition knowledge, a distinction was proposed between general nutrition knowledge items and health-food-related items. The former address relatively uncontroversial nutrition facts while the latter deal with popular beliefs about health food products in addition to the factual information. Data from a survey of 601 consumers suggested that the association between health-food-related knowledge and nutrition behavior could be accounted for by health food attitudes as measured by Fishbein operationalizations; this was not the case for general nutrition items. Previous measures of consumer nutrition knowledge have not distinguished between the two types of knowledge items.

Citation:

Joel Saegert and Eleanor A. Young (1982) ,"Distinguishing Betweem Two Different Kinds of Consumer Nutrition Knowledge", in NA - Advances in Consumer Research Volume 09, eds. Andrew Mitchell, Ann Abor, MI : Association for Consumer Research, Pages: 342-347.

Advances in Consumer Research Volume 9, 1982      Pages 342-347

DISTINGUISHING BETWEEM TWO DIFFERENT KINDS OF CONSUMER NUTRITION KNOWLEDGE

Joel Saegert, The University of Texas at San Antonio

Eleanor A. Young, The University of Texas Health Science Center at San Antonio

[This study was funded by Grant No. 5901-0410-9-0303-0, Office of Competitive Grants, US Department of Agriculture. The authors thank Patti Deiter, Ernest Bromley and Frank Bridges for help in data collection and analysis.]

ABSTRACT -

In measures of consumer nutrition knowledge, a distinction was proposed between general nutrition knowledge items and health-food-related items. The former address relatively uncontroversial nutrition facts while the latter deal with popular beliefs about health food products in addition to the factual information. Data from a survey of 601 consumers suggested that the association between health-food-related knowledge and nutrition behavior could be accounted for by health food attitudes as measured by Fishbein operationalizations; this was not the case for general nutrition items. Previous measures of consumer nutrition knowledge have not distinguished between the two types of knowledge items.

INTRODUCTION

Consumer behavior analysts have recently attempted to measure consumers' level of nutrition knowledge for comparisons with a number of behavioral variables. For example, the US Food and Drug Administration (1973, 1975) looked for relationships between knowledge and behaviors such as the use of nutrition labeling and the use of health food products. knower recently, Rudell (1979) investigated the effect of nutrition knowledge and consumer information acquisition and processing through use of the "cognitive response" technique. Other recent examples of research using the nutrition knowledge construct include Jacoby, Chestnut and Silverman (1977), Grotkowski and Sims (1978) and Yetley and Roderuck (1980).

As with any hypothetical construct, providing a valid and reliable operational definition for nutrition knowledge is problematical. Typically, this issue has been addressed through true-false or multiple choice tests made up of items concerning such information as what foods contain certain nutrients and what function the nutrients play in human health. (See Olson and Sims, 1980, for some suggested alternative methods of knowledge assessment through monitoring of cognitive responses.) In addition to the usual problems of validity and reliability the topic of nutrition information is quite controversial today with many consumers espousing beliefs about health foods and nutrition supplements which are questioned by professionals in the health care field (e.g., Bruch, 1974). In developing a nutrition knowledge assessment scale to include in a battery of instruments designed to investigate health food consumption, it became evident to the present authors that many items found on published nutrition knowledge tests dealt with ideas often professed by health food enthusiasts but which are denied or qualified by health professionals. For such items, it is difficult to know whether an "incorrect" response reflects a genuine lack of awareness of a particular nutrition fact or is an expression of the attitudes and opinions which are so adamantly espoused by health food proponents. Thus, a case can be made for differentiating between at least two different kinds of nutrition knowledge scale items: 1) those which deal with issues concerning popular health food beliefs, and 2) those which deal with factual nutritional information unrelated to popular health food beliefs.

An example of these two types of items will help clarify the distinction. An item such as "Fruits like oranges and grapefruit are rich in vitamin C" would seem to be relatively uncontroversial and does not conflict with tenets of health food enthusiasts. On the other hand, an item such as "Man made vitamins are just as good as natural vitamins", while technically correct according to nutrition professionals (e.g., Fusillo and Beloian, 1977), is clearly related to popular attitudes about health food products and categorically denied by their proponents.

For purposes of the present discussion, the two types of items will be labeled "health-food-related" knowledge and "general" knowledge. From a practical standpoint, the implications of acknowledging the two different kinds of items seem to be important in formulating a scale to measure the hypothetical construct of nutrition knowledge. If the two types are not separated, as they have not been in numerous studies which have used nutrition knowledge instruments, a consumer's knowledge score may reflect a combination of awareness of medically-based nutrition facts and his/her opinions or attitudes about nutrition based on popular health food beliefs. These latter beliefs may or may not be consistent with the findings of nutrition research.

From a theoretical standpoint, the two-types of items are less easy to distinguish. A recent discussion of nutrition knowledge structures by Olson and Sims (1980) has considered the problem from the background of the popular Fishbein model of attitudes and behavior. These authors discuss cognitive knowledge structures as being made up of beliefs, attitudes and behavioral intentions. In the present context 9 it is tempting to postulate that the "knowledge" reflected by a "general" nutrition scale item corresponds to a "belief" in the Fishbein model. In another discussion of nutrition attitudes, Sims (1981) promotes this view by citing Fishbein's definition of a belief as "the probability that a particular relationship exits between the object of belief and some other object, concept or goal." This would seem to fit such a knowledge scale item as "Oranges contain vitamin C."

Developing this line of argument further, a health food related item might be said to contain an attitudinal component reflecting a person's affective feelings over and above his/her factual knowledge. This seems possible for an item like "Natural vitamins are superior to synthetic." However, this distinction does not correspond in simple fashion to conventional operationalizations of Fishbein constructs. The Fishbein model typically defines two attitude components: 1) the belief that a given behavior will result in a given outcome and 2) a positive or negative feeling or evaluation of that outcome (cf. Ryan and Bonfield, 1980). While it might be said that consumer knowledge in the present context could be represented by the "belief about outcomes" component of the Fishbein model, the evaluation component seems irrelevant to the distinction between "general" and "health food related" knowledge. Thus, the Fishbein model does not seem to be applicable to a case where cognitive knowledge is assessed in terms of whether or not the consumer's belief is supported by the researcher's a Priori assumptions

From a behavioral standpoint, it may be argued that a consumer's behavior will be based on what he/she believes to be true, regardless of whether the belief is "correct." On the other hand, much consumer research attempts to assess the level of consumer knowledge in the population prior to the implementation of consumer information campaigns. The distinction between "general" vs "health-food-related" (popular) knowledge would seem to be important in any case where consumer's knowledge of facts, as specified a priori by the investigator, is required.

The purpose of the present paper is to provide empirical Justification for separation of general vs health-food-related nutrition knowledge. It is argued that health-food-related knowledge basically reflects attitudes toward health food products and behaviors while general knowledge of nutrition information does not. Thus, if an independent measure of health food attitudes is made, this variable should be closely related to performance on a health-food-related knowledge scale. On the other hand, general knowledge scale performance should be relatively independent of health food attitudes.

Previous Studies of Nutrition Knowledge and Nutrition Behavior

The degree to which nutrition knowledge predicts desirable nutrition behaviors has been the subject of a number of recent studies. For example, Jacoby, et al. (1977) found college student respondents to have a low level of performance on a 19-item knowledge test and a correspondingly low level of selection of nutrition information in an information acquisition task. Another study by Sims and Morris (1974) found low to moderate associations between nutrition status (presumably a reflection of nutrition practices) and family nutrition knowledge, assessed on a 35-item test. However, Sims (1978) later found that knowledge of nutrition had positive correlations with desirable intake of four nutrients by lactating mothers (r's between .52 and .41). In the present study, it was of interest to separate consumers' knowledge as measured by general and health-food-related items and to assess the degree to which the two types of nutrition knowledge predict the nutrition behavior of health food use. While this behavior may not be considered "desirable" by health professionals, it is nonetheless a consumer behavior which suggests strong "involvement" in the consumption process and hence can be predicted to be associated with knowledge level.

Numerous treatises on health food consumption (e.g. Rynearson, 1974) have argued that such consumers are the victims of nutrition misinformation, implying low nutrition knowledge. However, studies in the nutrition literature appear to be contradictory concerning the relationship between health food advocacy and nutrition knowledge. For example, Grotkowski and Sims (1978) reported negative correlations between health food interest statements and nutrition knowledge scores. On the other hand, an FDA study (1973) found that consumer households with high nutrition knowledge were more likely to be health food (vitamin) consumers than were low knowledge households (59% vs 43%). Such contradictory findings can possibly be explained by the distinction between general and health-food-related test items in knowledge measurement instruments; that is, some of the knowledge scales may have included health food items while others did not, hence confounding the measurement of knowledge, per se. Thus, in the present study, the relationship between nutrition knowledge and health food consumption was further investigated.

METHOD

Measurement Instruments Used in the Study

Nutrition Knowledge. Two sets of items were constructed to measure health-food-related and general knowledge respectively. For the health-food-related scale, 13 of the total 18 items were taken from a study conducted for the FDA in 1972. These items deal with popular health foot issues such as the safety of the food supply and the efficacy of nutrition supplements. The five additional items in this scale were made up by the present authors to reflect knowledge about other health food related issues not addressed by the original 13 items. The general nutrition items were developed from information tested in another FDA research program (FDA, 1973, 1975). This 16-item scale deals with the nutrient content of certain foods and the degree of difficulty of obtaining nutrients in the diet. For both knowledge subscales, the items were similar to those found in at least a dozen published reports of attempts to measure nutrition knowledge. Response alternatives for all of the items included "true", "false", or "don't know"; however, credit was assigned only for items marked correctly true or false.

Health Food Attitudes and Social Norms. Scales to measure attitudes toward health foods were patterned after recently proposed operationalizations of the Fishbein method of summing across the products of beliefs [As discussed in the introduction, it is clear that "beliefs" as a cognitive knowledge component (Olson & Sims, 1980) and "beliefs about outcomes" as operationalized by Oliver and Berger (1979) are not corresponding constructs. In the Fishbein variable discussed herein, beliefs are one of the two components of attitude, in this case, attitude toward health foods. In Olson and Sims, "beliefs" appear to be isomorphic to "concepts", implying factual information.] and evaluations about outcomes (Oliver and Berger, 1979). [The authors thank Dr. Richard Oliver for providing examples of Fishbein scales.]

The belief scale consisted of agreement or disagreement with statements about benefits attributed to health food practices measured on a bipolar 5-point scale (Example: "Taking vitamin supplements will result in better overall health"). The second scale was an evaluation of proposed outcomes of these same health food practices (Example: "Missing some nutrients in my diet"). This was measured on a bipolar 5-point scale ranging from "good" to "bad". The health food attitude scale was the sum of the products of 10 practices on these measures.

The social norm variable was similarly assessed. Social influencers of health food practices (e.g., family doctor, spouse, etc.) were identified on a 3-point scale from "never" to "always tries to influence me." This value was multiplied times a similar scale which measured the respondents motivation to comply with the influencer, again on a 3-point scale. The social norm variable was then the sum of the product of 8 such pairs.

General Nutrition Concern. This variable was designed to be an overall index of the degree to which respondents were concerned about nutrition. Most of the 17 items on the scale were taken from a study designed to profile "nutrition-conscious" consumers conducted by Needham, Harper and Steers (Wells, 1978). (Example: "It is important for the food that I eat to have high nutritional value".) Respondents indicated agreement or disagreement on a 6-point scale.

Health Food Use Index. Since products marketed with such health food claims as "natural" or "without preservatives" are so pervasive in our culture today, and since vitamin products are so universally consumed, it is difficult to devise a clear operational definition of "health food" for use in identifying consumption. In the present study, respondents were simply asked Questions about their use of a number of specific health food products; an index of health food use was constructed by summing points for each product. Points were assigned as follows:

TABLE

Table 1 shows statistical data from the present study for the six variables described above. The values in the "Possible Range" column for the first five variables reflect possible maxima and minima for the rating scales or products of rating scales; however, in the case of the health food index, the actual range is given. Alpha coefficients are modest but acceptable by standards suggested by Nunnally (1967, p. 226).

TABLE 1

MEANS, STANDARD DEVIATIONS, POSSIBLE RANGES AND CRONBACH ALPHA COEFFICIENTS FOR SCALES IN THE STUDY

Sample and Procedure

The survey instruments were administered as part of a larger study of health food attitudes and behavior. The sample was selected using systematic random area probability sampling. Twenty census tracts were randomly chosen in each of three Texas cities: Houston, Dallas and San Antonio. To insure adequate representation in the sample of lower income and ethnic minority consumers, sampling of tracts was stratified on the basis of income level (: below the median) and minority composition (; of blacks and hispanics) Streets were randomly selected for each tract and interviews were conducted at households along both sides of the street between designated cross streets. Ten interviews per tract were thus completed.

A total of 601 interviews (approximately 200 per city) were conducted. In each case, the first adult contacted in each residence approached by the interviewer was interviewed. Of 1761 households who responded to the interviewer's knock, 67: were ineligible or refused to be interviewed. Reasons for ineligibility were "no adult present" or "respondent could not read English". Thus, the 601 interviews which were conducted constitute a completion rate of 33% of households contacted. Interviews lasted approximately 45 minutes. About half of the interviewers were graduate students specifically trained to conduct the interviews and- half were employees of professional field interview firms.

RESULTS

The mean probability of a correct response to items on the two nutrition knowledge scales was .30 for the health-food-related scale and .53 for the general nutrition scale. This difference was significant by paried-comparisons t-test, t = 25.4, d: = 600, p < .001. The overall level of performance on the general scale is comparable to the calculated probability correct for items on scales reported by other researchers for samples roughly similar to that of the present study. For example, the following response probabilities have been found: .51 (Yetley and Roderuck, 1980); .54 (Eppright, Fox, Fryer, Lamkin and Vivian, 1970); .52 (Jacoby, et al., 1977); .63 (Rudell, 1979). Since "incorrect responses" on health-food-related items indicate agreement with popular health food arguments, the lower performance on the health-food-related scale can be taken to reflect a high degree of belief in the efficiency of health food products by the general public.

Table 2 shows Pearson product-moment correlation coefficients between health-food-related and general nutrition knowledge items, health food attitudes and health food social norms, general nutrition concern and the health food use index, as well as the demographic measures of age, income 9 education and minority status (minority vs. non-minority; minority included blacks and hispanics). The latter three variables were dichotomized as follows: income-less than $15,000 annual income=O, more than $15,000=19 education-no college=O, at least some college=1; minority status-minority=O 9 non-minority-1. Roughly half of the sample was represented by each of the subgroups for each variable.

The degree of association between the two knowledge scores was small but significantly different from zero. Correlation of the two knowledge variables with the demographic variables showed association between incomeS education, and minority status for general nutrition knowledge 9 but only for income for the health-food-related scale. Thus, general nutrition knowledge seems to be related to socioeconomic status, more so than health-food-related knowledge.

TABLE 2

CORRELATION COEFFICIENTS FOR THE HEALTH-FOOD-RELATED AND GENERAL NUTRITION KNOWLEDGE SCALES

The two knowledge scales both correlated significantly with health food attitudes but the correlation was negative for the health-food-related knowledge scale. This reflects the fact that agreement with a health food statement constitutes incorrect information from a knowledge standpoint. The positive correlation between the general nutrition knowledge instrument and attitudes indicates that individuals with positive attitudes toward health foods also have higher levels of overall nutrition knowledge. This finding argues against the notion proposed by some nutrition researchers that health food advocates are lower than non-advocates in nutrition knowledge per se (e.g., Bruch, 1974; Rynearson, 1974) and supports findings by some researchers that health food advocates are more knowledgeable (FDA, 1973).

A similar result was observed for the health food use index; both nutrition knowledge scales correlated significantly with use; again, the health-food-related scale correlation was negative while the general scale correlation was positive. That is, low health-food-related knowledge, and high general knowledge are associated with high use of health food products.

Finally, the social influence variable did not correlate with either of the two knowledge variables. This is consistent with the low associations between the social norm variable and attitudes and behaviors found in other recent consumer behavior studies using Fishbein scales (e.g., Ryan and Bonfield, 1980).

To assess the degree to which health-food-related and general nutrition knowledge predicted the nutrition behavior of health food use, a multiple regression analysis was performed. Variables were grouped into sets and entered hierarchically to see what effect progressive adjustment for antecedent variables would have on the prediction of the dependent variable (Cohen and Cohen, 1975, p. 127). The first set consisted of the four demographic variables, to allow adjustment for socioeconomic status. Set 2 was the general nutrition concern index, alone, which adjusted for overall nutrition interest. The two knowledge variables were then entered as set 3 to see if they would predict behavior when general nutrition attitudes and demographic background were controlled. Finally, the two Fishbein variables, health food attitudes and health food social norms were entered as set 4. Specifically, based on the assumption that the health-food-related measure is not independent of health food attitudes, it was predicted that adding the attitudes toward health foods variable to the regression equation would attenuate the effect of the health-food-related knowledge scale but would not affect the general nutrition scale.

As can be seen from Table 3, both education level and the minority status variable were significant predictors of health food use while income and age level were not. The education result is consistent with earlier studies (FDA, 1973; Rhee and Stubbs, 1976) showing greater health food use associated with higher education levels; the minority status result (higher usage for non-minorities) is inconsistent, however, with a study of Mexican Americans which did not find an association between health food use and ethnicity when income and education level were adjusted statistically (Saegert, Young and Saegert, 1977). The age result suggests that health food behavior is not necessarily positively associated with age, as reported by Jalso. Burns and Rivers (1970).

TABLE 3

SETWISE REGRESSION ANALYSIS WITH HEALTH FOOD USE INDEX AS THE DEPENDENT VARIABLE (VALUES PRESENTED ARE STANDARDIZED REGRESSION BETA COEFFICIENTS)

Adding the overall nutrition concern variable improved the prediction equation considerably. This supports the findings by Sims (1978) and Grotkowski and Sims (1978) that statements such as "nutrition is important" are associated with nutrition behaviors.

Both of the knowledge scales were significant predictors of health food use with the health-food-related scale being negatively associated (low scores on "health-food-related" items associated with high health food use) and the general nutrition knowledge scale being positively associated, as previously indicated by the zero-order correlations. Of principal interest, however, is the finding that the health-food-related scale beta weight was no longer significant when the two Fishbein items were included in the equation. It is assumed that this result can be attributed to overlap in variance accounted for between the health food attitude scale and the health-food-related nutrition knowledge scale. The general knowledge scale, however, remains a significant predictor. In all, 24 per cent of the variability in health food use was accounted for by all the variables in the equation. This is comparable to the amount of variability explained in similar studies predicting nutrition behaviors (e.g., Sims, 1978; Grotkowski and Sims, 1978; Rudell, 1979).

DISCUSSION

American consumers today generally seem to have heightened awareness of nutrition. This suggests that consumer knowledge of nutrition information will become of increasing interest to food manufacturers, retailers, public policy makers and nutrition educators. For example, a 1977 special report by the Marketing Science Institute (Quelch and Clayton, 1977) found that respondents from a wide range of nutrition interest groups (farmers, food manufacturers, retailers, etc.) rated "nutrition education material" to be a top requirement of the food industry to address nutritional well-being of consumers (the average agreement was over 90%). It is doubtful that assessment of the effectiveness of providing such materials can be carried out without valid and reliable measures of nutrition knowledge.

While no claims can be made in the present study that appropriate validation procedures have been carried out in the development of the two knowledge scales, the differences in respondents' scores for the two scales and the inability of the health-food-related scale to predict nutrition behavior over and above health food attitudes, indicates that nutrition knowledge scales used heretofore may have failed to separate out two important components of nutrition cognitive knowledge, i.e., general information (true awareness of nutrition facts) and popular health food beliefs (evaluations based on health food lore). One implication of this result is that previous attempts to measure knowledge may be qualified to the extent that they did not separate out general information from health food beliefs. This may explain discrepancies in the results reported as well as account for low associations between knowledge and behavioral variables.

A second important implication of the present results deals with health food consumption. The data from this and other studies indicate that health food users are better educated, of higher socioeconomic status overall and have higher nutrition knowledge compared to non-users of health food products. The finding of positive correlations between health food use and knowledge as measured by the general nutrition scale make it particularly clear that users do not suffer from lack of nutrition information as implied by nutrition educators (e.g. Bruch, 1974; Rynearson, 1974). The low scores the consumers made on the health-food-related scale can be accounted for by the widespread belief in the efficacy of health foods, an attitude seemingly held independently of high general knowledge of nutrition.

Nutritionists who have looked for explanations for health food behaviors have often resorted to psychological variables (e.g. Schafer and Yetley, 1975), although little empirical evidence has been forthcoming. It can be said that it will be of interest to the food marketing industry, against whom many health food beliefs are aimed, to determine the reasons behind health food behavior. This will require considerable study using personality indices and other social-psychological scales as predictor variables.

Although a number of researchers have attempted to standardize a general nutrition knowledge scale, none to date has effectively distinguished among different types of nutrition knowledge (e.g. desirable cooking procedures, kinds of nutrients needed, necessity of supplements, etc.) or has successfully distinguished between knowledge per se and knowledge reflective of popular health food attitudes. -Future work in the development of nutrition knowledge subscales should rely on standard procedures for establishing measurement indices such as factor analysis and the multitrait-multimethod matrix. Until such work is forthcoming, a meaningful operational definition of the knowledge construct, independent of health food attitudes, is unavailable.

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