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Food intake and food-related attitudes of older women: Implications for nutrition education
RESEARCH ARTICLE
Food Intake and Food-Related Attitudes of Older Women: Implications for Nutrition Education MARILYN MEDAUGH-ABERNETHy l AND MARIE T. FANELLI-KuCZMARSKI 2 IFramingham State College, Home Economics Department, Framingham, Massachusetts 01701 and 2Department of Nutrition and Dietetics, University of Delaware, Newark, Delaware 19716
ABSTRACT The objective of this study was to investigate the relationship between food-related attitudes and food consumption in 36 older women during a four-day period. The subjects were white, 65 years or older, literate, lived independently, and perceived themselves as healthy. Attitudes toward food consumed were measured by the semantic differential technique. The participants scored 10 attitudes toward food consumed and also completed a food consumption record. Foods were categorized into one of seven food groups: milk; meat; eggs; grains; fruit; vegetables; sugars, sweets, and beverages. Among the questions this study attempted to answer were: Do older women consume foods because they are easy to prepare, are low in calories, and/or are economical? Foodrelated attitudes varied according to the food group and to the amount consumed. Spearman rank correlations showed significant relationships between certain attitudes and certain food groups consumed such as eat infrequently !frequently and unhealthful/healthful to eat with the milk and fruit groups. Stepwise multiple regressions found significant associations between certain attitudes such as dislike/love eating and eat infrequently!frequently and the milk and fruit groups. Nutri·tion educators may be able to use findings in this study to improve eating patterns based on food-related attitudes of the elderly. (JNE 26:3-9, 1994)
INTRODUCTION A nutrition education program is more effective when it is based on a comprehensive needs assessment dealing with socioeconomic factors, food consumption patterns, and nutrition knowledge and attitudes (1,2). Among the newer areas of study in nutrition education research are attitudes towards foods that affect food consumption patterns. Many
Address for correspondence: Marilyn Abernethy, 3 Lands End Way, Ashland, MA 01721; (508) 881-2625. <© 1994 SOCIETY FOR NUTRITION EDUCATION
health professionals believe that to better understand the factors that influence actual food consumption practices, attitudes need to be studied with innovative approaches (3-5). At present there are a limited number of instruments to measure attitudes in older persons, and these instruments vary with the type of attitudes measured (6-10). Understanding attitudinal influences on food behavior may clarify the psychological underpinnings of the eating patterns of older adults and may help in designing effective nutrition education programs. As nutrition practitioners have realized, however, most people do not eat food for its nutritional content; they may eat a particular food for its sensory appeal, its satiety, or its symbolism. Food selection is based upon a complex interaction of a variety of factors both external and internal to that individual. The external factors are usually demographic, environmental, and socioeconomic, and are relatively easy to determine. However, internal factors such as values, attitudes, and beliefs toward food are more difficult to measure objectively (3). These influences of beliefs, attitudes, and values on an older adult's food intake are now better documented (6,10) than they have been in the past, when available data were limited and based on a few attitudinal statements, inference from dietary behaviors, anecdotal evidence, or speculation (11,12). Current research suggests that attitudes may playa larger role in food selection than previously considered, perhaps even a greater role than external factors (9,10). The term attitude is not defined uniformly by psychologists. At present there are more than 30 definitions used by researchers in the field of attitude study (12). In this study, the following operational definition of attitude is used: "an enduring, learned predisposition to behave in a consistent way toward a given class of objects" (13). The objectives of the present study were: 1) to develop semantic differential scales to systematically quantify attitudes of older women toward food they consumed; and 2) to evaluate the association between the measured attitudes and foods eaten.
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Medaugh-Abernethy and Fanelli-Kuczmarski/INTAKE AND ATTITUDES
METHODS
Sample selection. Participants in this study needed to meet all of the following eligibility criteria: white, female, 65 years of age or older, minimum of a seventh grade education, independent living, and self-perceived good health. These criteria were established to provide a group of relatively homogeneous participants who would be able to carry out the necessary tasks for individual data collection and to control for extraneous variables that could confound the study results. The study was advertised in the community newspaper advertisements by contacting senior groups. Prospective participants were contacted by telephone and given a brief description of the study; questions were answered and a personal interview was scheduled. Of the 37 women contacted, 36 agreed to participate in the study. All procedures used were approved by the Institutional Review Board on Use of Human Subjects prior to the initiation of this study. The mean age of the 36 participants was 72.5 years, range: 65-88 years. Among this group, 14 were 65-69 years of age, 9 were 70--74 years; 9 were 75-79 years, and 4 were 80 y'ears and older. Of the total, 83.3% (n = 30) had completed 13 years or more of education, and 6 had 7-12 years of education. Fourteen were married, 12 were widowed, five were single, and five were divorced or legally separated. Fifty percent (n = 18) of the participants lived alone, 38.9% (n = 14) with a spouse, and 11.1% (n = 4) lived with either a friend or relative(s). Training of participants. At the first interview a nutrition needs-assessment questionnaire for older adults was administered (16). Then a training session consisting of two separate visits was scheduled to ensure accurate data collection. During the first visit the study was explained in detail, sample meal was recorded, measuring utensils and food models were demonstrated by a registered dietician, and problems that often interfere with diet record keeping were discussed. Also, at this time, participants received instruction on how to use a data collection notebook containing forms for recording food intake and attitudes, paper food models from the National Dairy Council, and food measurement techniques. During the second visit the records were checked, any errors in recording were corrected, and questions answered. At this time an appointment was made to retrieve the data collection notebook after completion of all four days' records. Upon collection, these records were reviewed for errors and completeness.
a
Diet record. To obtain accurate dietary data reflecting their usual food intake, participants were instructed to record all food and beverage items consumed over a fourday period (three weekdays, one weekend day). Each food item eaten was recorded on a separate page that contained the ten attitudinal scales. The information recorded for each
food item included its name, date and time eaten, preparation method, and amount eaten. Combination foods such as sandwiches and casseroles were not separated into individual ingredients. Instead they were recorded as a single food. An eating episode was defined as consumption of food separated by at least one hour from the previous intake of food.
Attitudinal scales. Semantic differential scales were used to measure attitudes toward food. These scales are pairs of bipolar opposites in the form of adjectives designed to measure the evaluative response to an object. The first step in the development of these attitudinal scales was to create a list of words descriptive of why older adults choose the foods they eat. In this part of the study, 25 additional older women were contacted from senior groups in the community and agreed to be interviewed. At the first interview a 24-hour diet recall was done, after which the participant was asked to briefly describe why she chose to eat each food item. Then she was asked to imagine a meal of her favorite foods and again to describe why she chose each food. Finally, she was asked what foods she disliked and why. Based on all of these interviews, a total of 90 words or phrases were listed, after duplications were eliminated. This list was circulated among three nutrition professionals who added 10 words. To attain a workable number of adjectives and to prevent age bias, the list was then given to 100 adults aged 65 years or older to solicit their opinions on each word or phrase. They were instructed to delete those words or phrases that did not describe their reasons for choosing foods they ate. Of the total, 97 evaluated the list completely. Three persons did not complete the activity and their opinions were not included in the tally. None of the participants who evaluated the word list served as participants in the actual diet record study, since they might have biased the study results. The solicited opinions were scored as tallies, and less discriminating words or phrases were eliminated. The remaining words or phrases were grouped into distinct topic areas that could be formed into specific attitudes. Then topic areas that were either too specific or had meanings that were too general were deleted. If more than one word or phrase appeared under an accepted topic, a single word or term was identified to incorporate all of the ideas. As the tallied results were examined, certain words or phrases appeared to be more useful than others having a similar tally pattern. Words or phrases that did not reflect attitudes well were eliminated in favor of those that had broader meanings, and could readily be developed into semantic differential scales. For example, under the topic "ease of preparation," the phrases "challenging to prepare" and "simple to prepare" could be easily scaled on a bipolar scale and were retained, but under the topic "taste and texture," words such as "tangy" or "strong taste" would not be relevant to an attitude study and, hence, were deleted. A committee of nutrition
Journal of Nutrition Education Volume 26 Number 1
professionals and a psychologist reviewed and modified the list prior to its administration to the study participants. Ten semantic differential scales were developed. The committee of reviewers considered this number adequate to gather information but not so great as to overwhelm the participants. Seven-point bipolar scales were established for eight of the attitudes, whereas the remaining two, calories and roughage, used unipolar scales (Table 1).
Data analysis. The foods from the four-day diet records were originally coded into ten food groups, and the amounts eaten were recorded in grams. The food groupings are those used in Nationwide Food Consumption Surveys (17) and consist of the following: milk and milk products; meat, poultry, fish, and mixtures; eggs, egg mixtures, and substitutes; dry legumes, nuts, and seeds; grain products; fruits; vegetables; fats, oils, and salad dressings; sugar, sweets, and beverages; and food items with no nutritive values (e.g., noncaloric sweeteners). The means for the attitude rating scores were calculated so that each participant would be weighted equally in the four-;day average of attitudes regardless of the amount of food consumed by each. Student's t-test, part of the Statistical Analysis System (18), was used to determine whether the mean attitudes for the food groups were significantly different from zero. The unipolar and the bipolar scales were rescaled from the one through seven numbered Likert Scales, so that the results were comparable. The formula used was: for bipolar scales: y-4 = score; and for unipolar scales: (y-1)/2, where y = score on scaled item and 0 = neutral point. This shift rearranged the bipolar scales so zero was associated with the neutral point (representing a neutral attitude toward food) and +3 becomes the maximum positive rating and -3 the maximum negative rating. The unipolar scales were also changed because they did not have a neutral midpoint. Spearman rank correlations were used to calculate the relationship between mean attitudes and amounts of food eaten in each food group (18). A forward stepwise multiple regression (18) was also employed to describe the relationship between the dependent variables (i.e., amounts offood consumed within each food group) and independent variables (i.e., the ten attitudes). Only participants who ate one or more items in the food group were included in the multiple regression model for that group. A probability value ofless than 0.05 was considered statistically significant for all analyses.
RESULTS
Attitude rating scores. The mean ± SEM for the ten attitudes are shown in Table 1. These attitude means are for all food groups eaten by all 36 participants. The attitudes that received the scores in descending order are: provides
January. February 1994
5
roughage, simple to prepare, fast to prepare, and like eating. These attitudes were significantly different from the neutral point. Reviewing the individual rating scales showed that a few participants ate foods they disliked because they felt it was "good" or "healthy" for them, but these were infrequent and did not affect the mean scores of the group. The participants' rating about the roughage content of foods eaten was closest to "provides very small amounts of roughage eaten." This rating could be an indication that these women did not know about the roughage content of their diets or that they felt their diets contained inadequate amounts of roughage.
Food groups. Attitudes (mean and SEM) toward each food group are shown in Table 2. To generate a reliable statistic each food group having more than 24 respondents was analyzed using the Student's t-test. The following groups did not contain enough participants to warrant further statistical analysis: dry legumes, nuts, and seeds; fats, oils, and salad dressings; and non-nutritive food items. All of the means (62 of 70) of the scores on the attitude scales using t-tests differed significantly (p ::;; .01) from the neutral point for the following: milk - relaxing/stimulating food; meat - eat infrequently !frequently; egg - relaxing/stimulating food; and sugar, sweets, and beverages - unhealthful/healthful to eat and poor/good food buy. Spearman rank correlations were used to analyze the relationships between the attitude scores and the weight in grams of the food consumed within each of the food groups (Table 3). For milk products four Spearman rank correlation coefficients were statistically significant, including "eat infrequently / eat frequently" and "unhealthful/healthful to eat" and "provides calories." The higher the milk product consumption, the more the participants viewed milk products as healthful and low in calories. Also, what they actually consumed matched what they thought they consumed. There was a significant association between high egg consumption and viewing eggs as stimulating rather than relaxing and more caloric than not, according to Spearman rank correlation coefficients. The lower the consumption of eggs, the more they were seen as relaxing and less caloric. There was a significant positive correlation between fruit consumption and the attitudes" eat infrequently!frequently" and "unhealthful/healthful to eat." Results of the Spearman rank correlations for the attitudes for sugar, sweets, and beverages group indicated that one correlation was statistically significant: "feel bad/good after eating." Neither the grain nor the vegetable group had statistically significant correlations between amounts of foods eaten and ratings on the 10 attitude scales. This finding could be explained partially because grains and many vegetables were eaten in combination with other food items.
6
Medaugh-Abernethy and Fanelli-Kuczmarski/INTAKE AND ATTITUDES
Table 1.
Semantic differential scales of attitudes (X
-3
-2
± SEM)
-1
related to all foods eaten by older women (n = 36).
+1.3±0.4 +1 1
0
+2
+3
1---------1---------1---------1---------1---------1---------1 Dislike intensely
Dislike eating this
Dislike eating
Neither love nor
Like eating
Like eating this
Love eating
eating this
food very much
this food
dislike eating
this food
food very much
this food
-3
-2
-1
+1.6 ± 0.6 0
+1
+2
1
+3
1---------1---------1---------1---------1---------1---------1 Extremely
Very challenging
Challenging to
Neither
Simple to
Very simple to
Extremely simple
challenging to
to prepare
prepare
challenging nor
prepare
prepare
to prepare
prepare
simple to prepare +0.2 ± 0.3
-3
-2
-1
0
Extremely
Very relaxing
Relaxing
1
+1
+2
+3
1---------1---------1---------1---------1---------1---------1 Neither relaxing
-3
Stimulating
Very stimulating
nor stimulating
relaxing
-2
-1
0
Eat extremely
Eat very
Eat infrequently
infrequently
infrequently
Extemely stimulating
1.0 ± 0.5 +1
+2
+3
1---------1---------1---------1---------1---------1---------1 Neither eat
Eat fairly often
Eat often
Eat frequently
frequently nor infreqently
-3
-2
-1
0
1.0 ± 0.3 +1
+2
+3
1---------1---------1---------1---------1---------1----------1 Extremely
Very unhealthful
Unhealthful to
Neither healthful to Healthful to eat
Very healthful
Extremely
unhealthful to eat
to eat
eat
eat nor unhealthful
to eat
healthful to eat
-3
-2
-1
Poor food buy
+0.7 ± 0.4 0
+1
+2
+3
1---------1---------1---------1---------1---------1---------1 Extremely poor
Very poor food
food buy
buy
-3
-2
-1
Feel bad after
Feel very
Feel uncomfort-
uncomfortable
able after eating
Neither a good
Good food buy
nor bad food buy
+0.7 ± 0.5 0
+1
Very good food
Extremely good
buy
food buy
+2
+3
1---------1---------1---------1---------1---------1---------1 eating
Feel neither good
Feel good after
Feel very good
Feel extremely
nor bad after
eating
after eating
good after eating
eating
after eating
+1.4±0.7 -3
-2
-1
0
+1
1
+2
+3
1---------1---------1---------1---------1---------1---------1 Extremely time
Very time
Time consuming
Neither fast nor
consuming to
consuming to
to prepare
time consuming
prepare
prepare
0.0
0.5
Fast to prepare
Very fast to
Extremely fast
prepare
to prepare
to prepare
+1.2 ± 0.3 1.0 1
1.5
2.0
2.5
3.0
1---------1---------1---------1---------1---------1---------1 No opinion
Provides no
Provides very
Provides some
Provides
calories
few calories
calories
moderate amounts calories
Provides many
Provides too many calories
of calories
+1.7±0.2 0.0
0.5
1.0
1
1.5
2.0
2.5
3.0
I-~-------I---------I---------I---------I---------I---------1
No opinion
Provides no
Provides
Provides very
Provides small
Provides
roughage
extremely small
small amounts of
amounts of
moderate amounts amounts of
amounts of
roughage
roughage
of roughage
roughage
Provides large roughage
Journal of Nutrition Education Volume 26 Number 1 Table 2.
January. February 1994
7
Attitudes (X ± SEM) toward the selected food groups. X±SEM
Attitude Dislike/love eating
Challenging/simple to prepare
Relaxing/stimulating food
Eat infrequently/frequently
Unhealthful/healthful to eat
Poor/good food buy
Provides roughage
Provides calories
Feel bad/good after eating
Time consuming/fast to prepare
Milk
Meat
1.46
1.29
±0.10
±0.07
Egg
Grain
Fruit
Vegetables
Sweets
1.15
1.28
1.45
1.29
1.24
±0.10
±0.08
±0.09
±0.08
±0.10
1.66
0.94
0.39
1.59
1.84
1.23
1.97
±0.16
±0.08
±0.15
±0.12
±0.14
±0.11
±0.11
0.03
0.16
0.08
0.16
0.30
0.14
0.42
±0.08
±0.06
±0.08
±0.05
±0.06
±0.06
±0.09
0.91
0.03
0.60
0.89
0.98
0.78
1.72
±0.18
±0.15
±0.19
±0.12
±0.12
±0.13
±0.13
1.23
1.04
1.15
0.94
1.35
1.28
0.08
±0.09
±0.07
±0.09
±0.08
±0.08
±0.08
±0.07
0.81
0.72
1.07
0.63
0.89
1.02
±0.11
±0.08
±0.15
±0.09
±0.10
±0.08
-0.005 ±0.10
0.85
1.19
0.84
1.58
1.13
1.74
0.55
±0.07
±0.09
±0.10
±0.08
±0.09
±0.08
±0.02
2.10
2.01
1.01
1.98
1.73
1.67
1.08
±0.07
±0.05
±0.05
±0.04
±0.05
±0.05
±0.07
0.68
0.71
0.63
0.65
0.83
0.64
0.77
±0.09
±0.87
±0.13
±0.97
±0.09
±0.09
±0.08
1.66
0.66
1.32
1.45
1.68
±0.16
±0.11
±0.16
±0.14
±0.19
Also these foods were eaten so frequently that the participants may have become so "adaptively habituated" to the foods in both of these groups that they may not have evoked strong meanings for the participants. In physiological psychology, adaptive habituation is a well-documented phenomenon that causes a "diminuation of responses to repetitive stimulation" (19). Multiple regression analyses were conducted to determine the best subset of independent variables (attitudes) for describing the relationship between these and the dependent variables (amount by weight consumed of a food group). These stepwise multiple regression equations, or models, showed two or more of the ten attitude scales used in this study to be predictive of the amount consumed within all but one (sugar, sweets, and beverages) of the food groups. For example, the milk group had four associated attitudes that entered into the regression equation: dislike/like eating, relaxing/stimulating food, eat infrequently/frequently,
0.8 ±0.14
1.89 ±0.13
and unhealthful/healthful to eat. These four attitudes accounted for approximately 56% of the variance in the amount of foods consumed (in grams) from the milk group in the four-day period. Multiple regression analysis indicated that food group attitudes were found to account for a significant proportion of the variance for the milk, egg, fruit, and grain groups. These relationships between attitude scales and amount (by weight) consumed are not only statistically significant (i.e., they are not occurring by random chance variations), they are also meaningful. These models account for from 19 to 56% of the variance in the data collected in this study and include from two to five of the ten attitude scales. The multiple regression models included seven of the ten attitudes (i.e., dislike/loving eating, relaxing/ stimulating, eat infrequentlylfrequently, unhealthful/healthful to eat, challenging/simple to prepare, provides roughage, and provides calories) to account for proportions of the variance in the
Medaugh-Abernethy and Fanelli-KuczmarskilINTAKE AND ATTITUDES
8
Table 3.
Spearman rank correlations between attitude scale scores and amounts of food consumed from selected food groups. Spearman Correlations
Attitude
Dislike/love eating
Milk
Egg
Grain
Fruit
Vegetables
Sweets
-0.17
-0.11
-0.03
0.16
0.27
-0.26
0.25
0.20
-0.21
0.19
-0.27
0.10
0.16
0.04
-0.32+
0.45-
0.06
-0.05
0.07
-0.14
Challenging/simple to prepare Relaxing/stimulating food
Meat
-0.24
Eat infrequently/frequently
0.57--
-0.18
0.32
-0.13
0.51-
0.06
0.26
Unhealthful/healthful to eat
0.48--
0.10
0.28
0.08
0.40-
-0.08
0.18
Poor/good food buy
0.32+
0.01
0.15
0.05
0.25
0.10
0.30+
Provides roughage
0.09
-0.12
-0.14
-0.16
0.30+
0.17
0.06
Provides calories
-0.42-
-0.02
0.23
0.28+
0.08
-0.17
Feel bad/good after eating
-0.21
0.16
-0.05
-0.07
0.25
-0.21
0.18
-0.14
0.08
-0.21
-0.01
0.16
Time consuming/fast to prepare -'p
~
0.49-
0.37* -0.19
.01; '.01 < P ~ .05; + .05 < P ~ .10.
amount of a food group consumed. The specific attitudes were informative, since each helped to explain a portion of the variance. No one attitude dominated the regression models or entered all of the multiple regression models. The correlation matrix of the ten attitudes also confirmed that they were independent of each other (i.e., distinct).
DISCUSSION In general, the study results indicate that certain attitudes are associated with the amounts and types of foods consumed. These findings do have practical applications in the area of nutrition education. For example, the participants felt that grains (see Table 2) had moderate levels of calories, were fast to prepare, but had only moderate amounts of roughage. In developing a nutrition education program for the elderly, a nutrition educator could use this information to reinforce the positive attitudes concerning the role of grains, their moderate caloric levels, rapid preparation, and roughage! dietary fiber. Higgins et al. (9) found that attitudes toward and usage of milk products could not be measured adequately using their attitude scaling technique. Their results indicated that the participants had to be familiar with the food products for the attitude scales to measure the required attitudes. This
familiarity was built into the present study, since participants only rated attitudes toward the foods they ate. Grotkowski and Sims (11) concluded that nutrition education for older adults needs to include strategies for shaping positive attitudes as well as providing nutrition information. This study provided a method for measuring attitudes, which could provide a starting point for shaping them through nutrition education. Prediction equations derived from stepwise multiple regressions are formulas that can be used to predict the amounts of foods consumed by individual participants over a certain time period based directly on individual attitude scores. In this study the number of participants was too small to generate accurate equations, but such prediction equations could be formulated and tested in future studies with larger sample populations. These equations may provide nutritionists with a proxy measure of food consumption. Using the simple attitude scales in conjunction with a 24-hour recall would provide a more comprehensive picture of the diet. This study has practical applications in nutrition education for the elderly in that food-related attitudes were found to vary according to the food group. If a nutrition educator were to apply these findings to a lesson plan on the prevention of osteoporosis (e.g., emphasizing the positive attributes of milk products -low in calories and healthful), it
January. February 1994
Journal of Nutrition Education Volume 26 Number 1
might result in a positive and relevant learning experience for the older adult. It should be emphasized that the findings in this study may not apply to other groups, even if they are in the same age range, because of the homogeneity of the study population. A larger sample of older participants needs to be studied to test the reproducibility of the results of this study and to determine if they can be applied to other older adults. Other studies could test for any additional statistically significant attitude-food consumption relationships from which prediction equations could be developed from the multiple regression analyses. Additional research also needs to be completed involving larger numbers of women who meet the eligibility criteria of this study. Even though the data collection methodology was detailed, it was not expected to burden the participants. In fact, all of them completed the study. None complained that the study disrupted their daily routines, nor did they have difficulty in following the directions and in finding the time needed to complete the records. It appears that this procedure can be successfully used in future studies with trained participants.
9
Stuart Gansky, M.S., Biometrics Consulting Lab, School of Public Health, University of North Carolina, Chapel Hill. From the dissertation submitted to partially fulfill the requirements for a doctorate degree from the Nutrition Department, School of Public Health, University of North Carolina, Chapel Hill.
REFERENCES 1. Fanelli MF. Effective nutrition education for older adults. Top Clin Nutr 1988; 3:65-71. 2. Kohrs MB. Evaluation of nutrition programs for the elderly. Am] Clin Nutr 1982; 36:812-8. 3. Sims LS. Nutrition education research: reaching toward the leading edge.] Am Diet Assoc 1987; 87(Suppl):1O-8. 4. Lewis C], Sims LS, Shannon B. Examination of specific nutrition/ health behaviors using social cognitive model.] Am Diet Assoc 1989; 89: 194-202. 5. Brush KH, Woolcott DM, Kawash GF. Evaluation of an affectivebased adult nutrition education program. ] Nutr Educ 1986; 18: 258-64. 6. Holt V, Nordstrom], Kohrs MB. Food preferences of older adults.]
CONCLUSIONS
Nutr Eld 1987; 6(3):47-55. 7. Betts NM, Vivian VM. Factors related to the dietary adequacy of
The study found that women 65 years and older tended to consume foods that they believed contained roughage, were simple and fast to prepare, and that they enjoyed eating. The associations between certain attitudes and the amounts of foods consumed from the selected food groups were statistically significant. For example, milk product as well as fruit consumption was significantly related to the attitude "healthy to eat," while egg consumption was significantly correlated with "providing calories." Sometimes their attitudes toward selected food groups suggested an incorrect understanding of nutrition. For instance, some participants perceived whole milk products to be low in calories. Nutrition educators can use the results of attitudinal ratings to identify both negative and positive attitudes and to focus programs on modifying misconceptions, while reinforcing and promoting the positive attributes of certain foods. The associations reported in this study cannot be considered true for all older adults because of the small number of participants. Nonetheless, these associations are indicators of possible trends in food-related attitudes that vary according to the food group and that may serve as a research foundation for future studies with more subjects so as to make nutrition education relevant for the older adult.
noninstitutionalized elderly.] Nutr Eld 1985; 4(4):3-14. 8. Fanelli MT, Kannon GA, McDuffie ]R. An assessment of the nutrition education needs of congregate meal program participants.] Nutr Educ 1987; 19:131-7. 9. Higgins BC, Smiciklas-Wright H, Warland RH. The relationship of attitudes to the use of milk products by the elderly.] Nutr Eld 1985; 4(3):3-14. 10. Axelson M, Penfield M. Food and nutrition-related attitudes of elderly persons living alone.] Nutr Educ 1983; 15:23-7. 11. Grotkowski ML, Sims LS. Nutrition knowledge, attitudes and dietary practices of the elderly.] Am Diet Assoc 1979; 72:499-506. 12. Brown EL. Factors influencing food choices and intake. Geriatrics 1976; 31(9):89-92. 13. Roundtree ]L, Tinklin GL. Food beliefs and practices of selected senior citizens. Gerontologist 1975; 15:537-40. 14. DeFleur ML, Westie FR. Attitude as a scientific concept. Soc Forces 1963; 42: 17-31. 15. English HB, English AC. A comprehensive dictionary of psychological and psychoanalytical terms: a guide to usage. 1st Ed. New York: Longman, Green, 1958:50. 16. Fanelli MF, Abernethy MM. A nutritional questionnaire for older adults. Gerontologist 1986; 26: 192-7. 17. U.S. Department of Agriculture. Food intakes: individuals in 48 states, year 1977-78. NFCS 1977-78, Report No. 1-2. Washington, DC: Government Printing Office, 1983:352-4.
ACKNOWLEDGMENTS
18. SAS Institute Inc. SAS user's guide: statistics. 5th Ed. North Carolina:
The authors acknowledge the assistance of Gary Koch, Ph.D., and Vicki Davis, M.S., Biostatistics Department, and
19. Sternbach RA. Principles of psychology. 1st Ed. N ew York: Academic
Statistical Analysis System Institute, Inc., 1985:941. Press, 1966:73.
Food Intake and Food-Related Attitudes of Older Women: Implications for Nutrition Education MARILYN MEDAUGH-ABERNETHy l AND MARIE T. FANELLI-KuCZMARSKI 2 IFramingham State College, Home Economics Department, Framingham, Massachusetts 01701 and 2Department of Nutrition and Dietetics, University of Delaware, Newark, Delaware 19716
ABSTRACT The objective of this study was to investigate the relationship between food-related attitudes and food consumption in 36 older women during a four-day period. The subjects were white, 65 years or older, literate, lived independently, and perceived themselves as healthy. Attitudes toward food consumed were measured by the semantic differential technique. The participants scored 10 attitudes toward food consumed and also completed a food consumption record. Foods were categorized into one of seven food groups: milk; meat; eggs; grains; fruit; vegetables; sugars, sweets, and beverages. Among the questions this study attempted to answer were: Do older women consume foods because they are easy to prepare, are low in calories, and/or are economical? Foodrelated attitudes varied according to the food group and to the amount consumed. Spearman rank correlations showed significant relationships between certain attitudes and certain food groups consumed such as eat infrequently !frequently and unhealthful/healthful to eat with the milk and fruit groups. Stepwise multiple regressions found significant associations between certain attitudes such as dislike/love eating and eat infrequently!frequently and the milk and fruit groups. Nutri·tion educators may be able to use findings in this study to improve eating patterns based on food-related attitudes of the elderly. (JNE 26:3-9, 1994)
INTRODUCTION A nutrition education program is more effective when it is based on a comprehensive needs assessment dealing with socioeconomic factors, food consumption patterns, and nutrition knowledge and attitudes (1,2). Among the newer areas of study in nutrition education research are attitudes towards foods that affect food consumption patterns. Many
Address for correspondence: Marilyn Abernethy, 3 Lands End Way, Ashland, MA 01721; (508) 881-2625. <© 1994 SOCIETY FOR NUTRITION EDUCATION
health professionals believe that to better understand the factors that influence actual food consumption practices, attitudes need to be studied with innovative approaches (3-5). At present there are a limited number of instruments to measure attitudes in older persons, and these instruments vary with the type of attitudes measured (6-10). Understanding attitudinal influences on food behavior may clarify the psychological underpinnings of the eating patterns of older adults and may help in designing effective nutrition education programs. As nutrition practitioners have realized, however, most people do not eat food for its nutritional content; they may eat a particular food for its sensory appeal, its satiety, or its symbolism. Food selection is based upon a complex interaction of a variety of factors both external and internal to that individual. The external factors are usually demographic, environmental, and socioeconomic, and are relatively easy to determine. However, internal factors such as values, attitudes, and beliefs toward food are more difficult to measure objectively (3). These influences of beliefs, attitudes, and values on an older adult's food intake are now better documented (6,10) than they have been in the past, when available data were limited and based on a few attitudinal statements, inference from dietary behaviors, anecdotal evidence, or speculation (11,12). Current research suggests that attitudes may playa larger role in food selection than previously considered, perhaps even a greater role than external factors (9,10). The term attitude is not defined uniformly by psychologists. At present there are more than 30 definitions used by researchers in the field of attitude study (12). In this study, the following operational definition of attitude is used: "an enduring, learned predisposition to behave in a consistent way toward a given class of objects" (13). The objectives of the present study were: 1) to develop semantic differential scales to systematically quantify attitudes of older women toward food they consumed; and 2) to evaluate the association between the measured attitudes and foods eaten.
4
Medaugh-Abernethy and Fanelli-Kuczmarski/INTAKE AND ATTITUDES
METHODS
Sample selection. Participants in this study needed to meet all of the following eligibility criteria: white, female, 65 years of age or older, minimum of a seventh grade education, independent living, and self-perceived good health. These criteria were established to provide a group of relatively homogeneous participants who would be able to carry out the necessary tasks for individual data collection and to control for extraneous variables that could confound the study results. The study was advertised in the community newspaper advertisements by contacting senior groups. Prospective participants were contacted by telephone and given a brief description of the study; questions were answered and a personal interview was scheduled. Of the 37 women contacted, 36 agreed to participate in the study. All procedures used were approved by the Institutional Review Board on Use of Human Subjects prior to the initiation of this study. The mean age of the 36 participants was 72.5 years, range: 65-88 years. Among this group, 14 were 65-69 years of age, 9 were 70--74 years; 9 were 75-79 years, and 4 were 80 y'ears and older. Of the total, 83.3% (n = 30) had completed 13 years or more of education, and 6 had 7-12 years of education. Fourteen were married, 12 were widowed, five were single, and five were divorced or legally separated. Fifty percent (n = 18) of the participants lived alone, 38.9% (n = 14) with a spouse, and 11.1% (n = 4) lived with either a friend or relative(s). Training of participants. At the first interview a nutrition needs-assessment questionnaire for older adults was administered (16). Then a training session consisting of two separate visits was scheduled to ensure accurate data collection. During the first visit the study was explained in detail, sample meal was recorded, measuring utensils and food models were demonstrated by a registered dietician, and problems that often interfere with diet record keeping were discussed. Also, at this time, participants received instruction on how to use a data collection notebook containing forms for recording food intake and attitudes, paper food models from the National Dairy Council, and food measurement techniques. During the second visit the records were checked, any errors in recording were corrected, and questions answered. At this time an appointment was made to retrieve the data collection notebook after completion of all four days' records. Upon collection, these records were reviewed for errors and completeness.
a
Diet record. To obtain accurate dietary data reflecting their usual food intake, participants were instructed to record all food and beverage items consumed over a fourday period (three weekdays, one weekend day). Each food item eaten was recorded on a separate page that contained the ten attitudinal scales. The information recorded for each
food item included its name, date and time eaten, preparation method, and amount eaten. Combination foods such as sandwiches and casseroles were not separated into individual ingredients. Instead they were recorded as a single food. An eating episode was defined as consumption of food separated by at least one hour from the previous intake of food.
Attitudinal scales. Semantic differential scales were used to measure attitudes toward food. These scales are pairs of bipolar opposites in the form of adjectives designed to measure the evaluative response to an object. The first step in the development of these attitudinal scales was to create a list of words descriptive of why older adults choose the foods they eat. In this part of the study, 25 additional older women were contacted from senior groups in the community and agreed to be interviewed. At the first interview a 24-hour diet recall was done, after which the participant was asked to briefly describe why she chose to eat each food item. Then she was asked to imagine a meal of her favorite foods and again to describe why she chose each food. Finally, she was asked what foods she disliked and why. Based on all of these interviews, a total of 90 words or phrases were listed, after duplications were eliminated. This list was circulated among three nutrition professionals who added 10 words. To attain a workable number of adjectives and to prevent age bias, the list was then given to 100 adults aged 65 years or older to solicit their opinions on each word or phrase. They were instructed to delete those words or phrases that did not describe their reasons for choosing foods they ate. Of the total, 97 evaluated the list completely. Three persons did not complete the activity and their opinions were not included in the tally. None of the participants who evaluated the word list served as participants in the actual diet record study, since they might have biased the study results. The solicited opinions were scored as tallies, and less discriminating words or phrases were eliminated. The remaining words or phrases were grouped into distinct topic areas that could be formed into specific attitudes. Then topic areas that were either too specific or had meanings that were too general were deleted. If more than one word or phrase appeared under an accepted topic, a single word or term was identified to incorporate all of the ideas. As the tallied results were examined, certain words or phrases appeared to be more useful than others having a similar tally pattern. Words or phrases that did not reflect attitudes well were eliminated in favor of those that had broader meanings, and could readily be developed into semantic differential scales. For example, under the topic "ease of preparation," the phrases "challenging to prepare" and "simple to prepare" could be easily scaled on a bipolar scale and were retained, but under the topic "taste and texture," words such as "tangy" or "strong taste" would not be relevant to an attitude study and, hence, were deleted. A committee of nutrition
Journal of Nutrition Education Volume 26 Number 1
professionals and a psychologist reviewed and modified the list prior to its administration to the study participants. Ten semantic differential scales were developed. The committee of reviewers considered this number adequate to gather information but not so great as to overwhelm the participants. Seven-point bipolar scales were established for eight of the attitudes, whereas the remaining two, calories and roughage, used unipolar scales (Table 1).
Data analysis. The foods from the four-day diet records were originally coded into ten food groups, and the amounts eaten were recorded in grams. The food groupings are those used in Nationwide Food Consumption Surveys (17) and consist of the following: milk and milk products; meat, poultry, fish, and mixtures; eggs, egg mixtures, and substitutes; dry legumes, nuts, and seeds; grain products; fruits; vegetables; fats, oils, and salad dressings; sugar, sweets, and beverages; and food items with no nutritive values (e.g., noncaloric sweeteners). The means for the attitude rating scores were calculated so that each participant would be weighted equally in the four-;day average of attitudes regardless of the amount of food consumed by each. Student's t-test, part of the Statistical Analysis System (18), was used to determine whether the mean attitudes for the food groups were significantly different from zero. The unipolar and the bipolar scales were rescaled from the one through seven numbered Likert Scales, so that the results were comparable. The formula used was: for bipolar scales: y-4 = score; and for unipolar scales: (y-1)/2, where y = score on scaled item and 0 = neutral point. This shift rearranged the bipolar scales so zero was associated with the neutral point (representing a neutral attitude toward food) and +3 becomes the maximum positive rating and -3 the maximum negative rating. The unipolar scales were also changed because they did not have a neutral midpoint. Spearman rank correlations were used to calculate the relationship between mean attitudes and amounts of food eaten in each food group (18). A forward stepwise multiple regression (18) was also employed to describe the relationship between the dependent variables (i.e., amounts offood consumed within each food group) and independent variables (i.e., the ten attitudes). Only participants who ate one or more items in the food group were included in the multiple regression model for that group. A probability value ofless than 0.05 was considered statistically significant for all analyses.
RESULTS
Attitude rating scores. The mean ± SEM for the ten attitudes are shown in Table 1. These attitude means are for all food groups eaten by all 36 participants. The attitudes that received the scores in descending order are: provides
January. February 1994
5
roughage, simple to prepare, fast to prepare, and like eating. These attitudes were significantly different from the neutral point. Reviewing the individual rating scales showed that a few participants ate foods they disliked because they felt it was "good" or "healthy" for them, but these were infrequent and did not affect the mean scores of the group. The participants' rating about the roughage content of foods eaten was closest to "provides very small amounts of roughage eaten." This rating could be an indication that these women did not know about the roughage content of their diets or that they felt their diets contained inadequate amounts of roughage.
Food groups. Attitudes (mean and SEM) toward each food group are shown in Table 2. To generate a reliable statistic each food group having more than 24 respondents was analyzed using the Student's t-test. The following groups did not contain enough participants to warrant further statistical analysis: dry legumes, nuts, and seeds; fats, oils, and salad dressings; and non-nutritive food items. All of the means (62 of 70) of the scores on the attitude scales using t-tests differed significantly (p ::;; .01) from the neutral point for the following: milk - relaxing/stimulating food; meat - eat infrequently !frequently; egg - relaxing/stimulating food; and sugar, sweets, and beverages - unhealthful/healthful to eat and poor/good food buy. Spearman rank correlations were used to analyze the relationships between the attitude scores and the weight in grams of the food consumed within each of the food groups (Table 3). For milk products four Spearman rank correlation coefficients were statistically significant, including "eat infrequently / eat frequently" and "unhealthful/healthful to eat" and "provides calories." The higher the milk product consumption, the more the participants viewed milk products as healthful and low in calories. Also, what they actually consumed matched what they thought they consumed. There was a significant association between high egg consumption and viewing eggs as stimulating rather than relaxing and more caloric than not, according to Spearman rank correlation coefficients. The lower the consumption of eggs, the more they were seen as relaxing and less caloric. There was a significant positive correlation between fruit consumption and the attitudes" eat infrequently!frequently" and "unhealthful/healthful to eat." Results of the Spearman rank correlations for the attitudes for sugar, sweets, and beverages group indicated that one correlation was statistically significant: "feel bad/good after eating." Neither the grain nor the vegetable group had statistically significant correlations between amounts of foods eaten and ratings on the 10 attitude scales. This finding could be explained partially because grains and many vegetables were eaten in combination with other food items.
6
Medaugh-Abernethy and Fanelli-Kuczmarski/INTAKE AND ATTITUDES
Table 1.
Semantic differential scales of attitudes (X
-3
-2
± SEM)
-1
related to all foods eaten by older women (n = 36).
+1.3±0.4 +1 1
0
+2
+3
1---------1---------1---------1---------1---------1---------1 Dislike intensely
Dislike eating this
Dislike eating
Neither love nor
Like eating
Like eating this
Love eating
eating this
food very much
this food
dislike eating
this food
food very much
this food
-3
-2
-1
+1.6 ± 0.6 0
+1
+2
1
+3
1---------1---------1---------1---------1---------1---------1 Extremely
Very challenging
Challenging to
Neither
Simple to
Very simple to
Extremely simple
challenging to
to prepare
prepare
challenging nor
prepare
prepare
to prepare
prepare
simple to prepare +0.2 ± 0.3
-3
-2
-1
0
Extremely
Very relaxing
Relaxing
1
+1
+2
+3
1---------1---------1---------1---------1---------1---------1 Neither relaxing
-3
Stimulating
Very stimulating
nor stimulating
relaxing
-2
-1
0
Eat extremely
Eat very
Eat infrequently
infrequently
infrequently
Extemely stimulating
1.0 ± 0.5 +1
+2
+3
1---------1---------1---------1---------1---------1---------1 Neither eat
Eat fairly often
Eat often
Eat frequently
frequently nor infreqently
-3
-2
-1
0
1.0 ± 0.3 +1
+2
+3
1---------1---------1---------1---------1---------1----------1 Extremely
Very unhealthful
Unhealthful to
Neither healthful to Healthful to eat
Very healthful
Extremely
unhealthful to eat
to eat
eat
eat nor unhealthful
to eat
healthful to eat
-3
-2
-1
Poor food buy
+0.7 ± 0.4 0
+1
+2
+3
1---------1---------1---------1---------1---------1---------1 Extremely poor
Very poor food
food buy
buy
-3
-2
-1
Feel bad after
Feel very
Feel uncomfort-
uncomfortable
able after eating
Neither a good
Good food buy
nor bad food buy
+0.7 ± 0.5 0
+1
Very good food
Extremely good
buy
food buy
+2
+3
1---------1---------1---------1---------1---------1---------1 eating
Feel neither good
Feel good after
Feel very good
Feel extremely
nor bad after
eating
after eating
good after eating
eating
after eating
+1.4±0.7 -3
-2
-1
0
+1
1
+2
+3
1---------1---------1---------1---------1---------1---------1 Extremely time
Very time
Time consuming
Neither fast nor
consuming to
consuming to
to prepare
time consuming
prepare
prepare
0.0
0.5
Fast to prepare
Very fast to
Extremely fast
prepare
to prepare
to prepare
+1.2 ± 0.3 1.0 1
1.5
2.0
2.5
3.0
1---------1---------1---------1---------1---------1---------1 No opinion
Provides no
Provides very
Provides some
Provides
calories
few calories
calories
moderate amounts calories
Provides many
Provides too many calories
of calories
+1.7±0.2 0.0
0.5
1.0
1
1.5
2.0
2.5
3.0
I-~-------I---------I---------I---------I---------I---------1
No opinion
Provides no
Provides
Provides very
Provides small
Provides
roughage
extremely small
small amounts of
amounts of
moderate amounts amounts of
amounts of
roughage
roughage
of roughage
roughage
Provides large roughage
Journal of Nutrition Education Volume 26 Number 1 Table 2.
January. February 1994
7
Attitudes (X ± SEM) toward the selected food groups. X±SEM
Attitude Dislike/love eating
Challenging/simple to prepare
Relaxing/stimulating food
Eat infrequently/frequently
Unhealthful/healthful to eat
Poor/good food buy
Provides roughage
Provides calories
Feel bad/good after eating
Time consuming/fast to prepare
Milk
Meat
1.46
1.29
±0.10
±0.07
Egg
Grain
Fruit
Vegetables
Sweets
1.15
1.28
1.45
1.29
1.24
±0.10
±0.08
±0.09
±0.08
±0.10
1.66
0.94
0.39
1.59
1.84
1.23
1.97
±0.16
±0.08
±0.15
±0.12
±0.14
±0.11
±0.11
0.03
0.16
0.08
0.16
0.30
0.14
0.42
±0.08
±0.06
±0.08
±0.05
±0.06
±0.06
±0.09
0.91
0.03
0.60
0.89
0.98
0.78
1.72
±0.18
±0.15
±0.19
±0.12
±0.12
±0.13
±0.13
1.23
1.04
1.15
0.94
1.35
1.28
0.08
±0.09
±0.07
±0.09
±0.08
±0.08
±0.08
±0.07
0.81
0.72
1.07
0.63
0.89
1.02
±0.11
±0.08
±0.15
±0.09
±0.10
±0.08
-0.005 ±0.10
0.85
1.19
0.84
1.58
1.13
1.74
0.55
±0.07
±0.09
±0.10
±0.08
±0.09
±0.08
±0.02
2.10
2.01
1.01
1.98
1.73
1.67
1.08
±0.07
±0.05
±0.05
±0.04
±0.05
±0.05
±0.07
0.68
0.71
0.63
0.65
0.83
0.64
0.77
±0.09
±0.87
±0.13
±0.97
±0.09
±0.09
±0.08
1.66
0.66
1.32
1.45
1.68
±0.16
±0.11
±0.16
±0.14
±0.19
Also these foods were eaten so frequently that the participants may have become so "adaptively habituated" to the foods in both of these groups that they may not have evoked strong meanings for the participants. In physiological psychology, adaptive habituation is a well-documented phenomenon that causes a "diminuation of responses to repetitive stimulation" (19). Multiple regression analyses were conducted to determine the best subset of independent variables (attitudes) for describing the relationship between these and the dependent variables (amount by weight consumed of a food group). These stepwise multiple regression equations, or models, showed two or more of the ten attitude scales used in this study to be predictive of the amount consumed within all but one (sugar, sweets, and beverages) of the food groups. For example, the milk group had four associated attitudes that entered into the regression equation: dislike/like eating, relaxing/stimulating food, eat infrequently/frequently,
0.8 ±0.14
1.89 ±0.13
and unhealthful/healthful to eat. These four attitudes accounted for approximately 56% of the variance in the amount of foods consumed (in grams) from the milk group in the four-day period. Multiple regression analysis indicated that food group attitudes were found to account for a significant proportion of the variance for the milk, egg, fruit, and grain groups. These relationships between attitude scales and amount (by weight) consumed are not only statistically significant (i.e., they are not occurring by random chance variations), they are also meaningful. These models account for from 19 to 56% of the variance in the data collected in this study and include from two to five of the ten attitude scales. The multiple regression models included seven of the ten attitudes (i.e., dislike/loving eating, relaxing/ stimulating, eat infrequentlylfrequently, unhealthful/healthful to eat, challenging/simple to prepare, provides roughage, and provides calories) to account for proportions of the variance in the
Medaugh-Abernethy and Fanelli-KuczmarskilINTAKE AND ATTITUDES
8
Table 3.
Spearman rank correlations between attitude scale scores and amounts of food consumed from selected food groups. Spearman Correlations
Attitude
Dislike/love eating
Milk
Egg
Grain
Fruit
Vegetables
Sweets
-0.17
-0.11
-0.03
0.16
0.27
-0.26
0.25
0.20
-0.21
0.19
-0.27
0.10
0.16
0.04
-0.32+
0.45-
0.06
-0.05
0.07
-0.14
Challenging/simple to prepare Relaxing/stimulating food
Meat
-0.24
Eat infrequently/frequently
0.57--
-0.18
0.32
-0.13
0.51-
0.06
0.26
Unhealthful/healthful to eat
0.48--
0.10
0.28
0.08
0.40-
-0.08
0.18
Poor/good food buy
0.32+
0.01
0.15
0.05
0.25
0.10
0.30+
Provides roughage
0.09
-0.12
-0.14
-0.16
0.30+
0.17
0.06
Provides calories
-0.42-
-0.02
0.23
0.28+
0.08
-0.17
Feel bad/good after eating
-0.21
0.16
-0.05
-0.07
0.25
-0.21
0.18
-0.14
0.08
-0.21
-0.01
0.16
Time consuming/fast to prepare -'p
~
0.49-
0.37* -0.19
.01; '.01 < P ~ .05; + .05 < P ~ .10.
amount of a food group consumed. The specific attitudes were informative, since each helped to explain a portion of the variance. No one attitude dominated the regression models or entered all of the multiple regression models. The correlation matrix of the ten attitudes also confirmed that they were independent of each other (i.e., distinct).
DISCUSSION In general, the study results indicate that certain attitudes are associated with the amounts and types of foods consumed. These findings do have practical applications in the area of nutrition education. For example, the participants felt that grains (see Table 2) had moderate levels of calories, were fast to prepare, but had only moderate amounts of roughage. In developing a nutrition education program for the elderly, a nutrition educator could use this information to reinforce the positive attitudes concerning the role of grains, their moderate caloric levels, rapid preparation, and roughage! dietary fiber. Higgins et al. (9) found that attitudes toward and usage of milk products could not be measured adequately using their attitude scaling technique. Their results indicated that the participants had to be familiar with the food products for the attitude scales to measure the required attitudes. This
familiarity was built into the present study, since participants only rated attitudes toward the foods they ate. Grotkowski and Sims (11) concluded that nutrition education for older adults needs to include strategies for shaping positive attitudes as well as providing nutrition information. This study provided a method for measuring attitudes, which could provide a starting point for shaping them through nutrition education. Prediction equations derived from stepwise multiple regressions are formulas that can be used to predict the amounts of foods consumed by individual participants over a certain time period based directly on individual attitude scores. In this study the number of participants was too small to generate accurate equations, but such prediction equations could be formulated and tested in future studies with larger sample populations. These equations may provide nutritionists with a proxy measure of food consumption. Using the simple attitude scales in conjunction with a 24-hour recall would provide a more comprehensive picture of the diet. This study has practical applications in nutrition education for the elderly in that food-related attitudes were found to vary according to the food group. If a nutrition educator were to apply these findings to a lesson plan on the prevention of osteoporosis (e.g., emphasizing the positive attributes of milk products -low in calories and healthful), it
January. February 1994
Journal of Nutrition Education Volume 26 Number 1
might result in a positive and relevant learning experience for the older adult. It should be emphasized that the findings in this study may not apply to other groups, even if they are in the same age range, because of the homogeneity of the study population. A larger sample of older participants needs to be studied to test the reproducibility of the results of this study and to determine if they can be applied to other older adults. Other studies could test for any additional statistically significant attitude-food consumption relationships from which prediction equations could be developed from the multiple regression analyses. Additional research also needs to be completed involving larger numbers of women who meet the eligibility criteria of this study. Even though the data collection methodology was detailed, it was not expected to burden the participants. In fact, all of them completed the study. None complained that the study disrupted their daily routines, nor did they have difficulty in following the directions and in finding the time needed to complete the records. It appears that this procedure can be successfully used in future studies with trained participants.
9
Stuart Gansky, M.S., Biometrics Consulting Lab, School of Public Health, University of North Carolina, Chapel Hill. From the dissertation submitted to partially fulfill the requirements for a doctorate degree from the Nutrition Department, School of Public Health, University of North Carolina, Chapel Hill.
REFERENCES 1. Fanelli MF. Effective nutrition education for older adults. Top Clin Nutr 1988; 3:65-71. 2. Kohrs MB. Evaluation of nutrition programs for the elderly. Am] Clin Nutr 1982; 36:812-8. 3. Sims LS. Nutrition education research: reaching toward the leading edge.] Am Diet Assoc 1987; 87(Suppl):1O-8. 4. Lewis C], Sims LS, Shannon B. Examination of specific nutrition/ health behaviors using social cognitive model.] Am Diet Assoc 1989; 89: 194-202. 5. Brush KH, Woolcott DM, Kawash GF. Evaluation of an affectivebased adult nutrition education program. ] Nutr Educ 1986; 18: 258-64. 6. Holt V, Nordstrom], Kohrs MB. Food preferences of older adults.]
CONCLUSIONS
Nutr Eld 1987; 6(3):47-55. 7. Betts NM, Vivian VM. Factors related to the dietary adequacy of
The study found that women 65 years and older tended to consume foods that they believed contained roughage, were simple and fast to prepare, and that they enjoyed eating. The associations between certain attitudes and the amounts of foods consumed from the selected food groups were statistically significant. For example, milk product as well as fruit consumption was significantly related to the attitude "healthy to eat," while egg consumption was significantly correlated with "providing calories." Sometimes their attitudes toward selected food groups suggested an incorrect understanding of nutrition. For instance, some participants perceived whole milk products to be low in calories. Nutrition educators can use the results of attitudinal ratings to identify both negative and positive attitudes and to focus programs on modifying misconceptions, while reinforcing and promoting the positive attributes of certain foods. The associations reported in this study cannot be considered true for all older adults because of the small number of participants. Nonetheless, these associations are indicators of possible trends in food-related attitudes that vary according to the food group and that may serve as a research foundation for future studies with more subjects so as to make nutrition education relevant for the older adult.
noninstitutionalized elderly.] Nutr Eld 1985; 4(4):3-14. 8. Fanelli MT, Kannon GA, McDuffie ]R. An assessment of the nutrition education needs of congregate meal program participants.] Nutr Educ 1987; 19:131-7. 9. Higgins BC, Smiciklas-Wright H, Warland RH. The relationship of attitudes to the use of milk products by the elderly.] Nutr Eld 1985; 4(3):3-14. 10. Axelson M, Penfield M. Food and nutrition-related attitudes of elderly persons living alone.] Nutr Educ 1983; 15:23-7. 11. Grotkowski ML, Sims LS. Nutrition knowledge, attitudes and dietary practices of the elderly.] Am Diet Assoc 1979; 72:499-506. 12. Brown EL. Factors influencing food choices and intake. Geriatrics 1976; 31(9):89-92. 13. Roundtree ]L, Tinklin GL. Food beliefs and practices of selected senior citizens. Gerontologist 1975; 15:537-40. 14. DeFleur ML, Westie FR. Attitude as a scientific concept. Soc Forces 1963; 42: 17-31. 15. English HB, English AC. A comprehensive dictionary of psychological and psychoanalytical terms: a guide to usage. 1st Ed. New York: Longman, Green, 1958:50. 16. Fanelli MF, Abernethy MM. A nutritional questionnaire for older adults. Gerontologist 1986; 26: 192-7. 17. U.S. Department of Agriculture. Food intakes: individuals in 48 states, year 1977-78. NFCS 1977-78, Report No. 1-2. Washington, DC: Government Printing Office, 1983:352-4.
ACKNOWLEDGMENTS
18. SAS Institute Inc. SAS user's guide: statistics. 5th Ed. North Carolina:
The authors acknowledge the assistance of Gary Koch, Ph.D., and Vicki Davis, M.S., Biostatistics Department, and
19. Sternbach RA. Principles of psychology. 1st Ed. N ew York: Academic
Statistical Analysis System Institute, Inc., 1985:941. Press, 1966:73.