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Validation of a dietary assessment instrument designed to measure fat intake
Nutrition Research, Vol. 15, No. 7. pp. 969-976.1995 Copyright 0 1995 Elsevier Science Ltd Printed in the USA. All rights reserved 0271-X317/95 $9.50+ .OO
Pergamon
VALIDATION OF A DIETARY ASSESSMENT INSTRUMENT DESIGNED TO MEASURE FAT INTAKE Kathy A. Beerman’, F’hD, Kim L. Dittus2, PhD, and Marc A. Evans3, PhD ‘Department of Food Science and Human Nutrition Washington State University Pullman, Washington 99164-6376 2Department of Nutritional and Food Service Management Syracuse University Syracuse, New York 132441250 3Program in Statistics Washington State University Pullman, Washington 99164
ABSTRACT The purpose of this study was to validate an instrument which accurately estimates dietary fat intake. The study compared actual fat intake values obtained by plate waste measures to a 24-hour semiquantitative food frequency questionnaire (SFFQ). The SFFQ lists foods along with fat-containing condiments to represent how foods are typically consumed. It was hypothesized that listing food items together with their associated condiments would serve as written prompts to facilitate recall. To determine if listing fat-containing condiments along with food items facilitates recall, a traditional semiquantitative food frequency questionnaire (SFFQ-T) was developed as a comparison. The results of this study indicate that the SFFQ more accurately estimates actual fat intake compared to the SFFQ-T. Keywords:
Dietary Assessment,
Food Recall, Nutrition Anthropology
INTRODUCTION Several large epidemiological studies which specifically measured dietary fat intake utilized dietary assessment methods which were both costly and time consuming (1,2,3,4,5). Although these dietary assessment methods provide valuable information, not all researchers have sufficient funds for such extensive and labor intensive methods of data collection. As a result, researchers often depend on the use of food frequency questionnaires to assess fat intake. The greatest benefit of food frequencies is their relative ease and low cost when administered to large numbers of ‘Author to whom correspondence
should be addressed. 969
970
K.A. BEERMAN et al.
subjects (6,7). Although this methodology is useful to evaluate dietary intake patterns over time, a quantitative measure is often lacking. This limitation highlights the need for further research to develop dietary assessment tools which provide a quantified measure of fat intake and can also be easily administered to large groups of people. The purpose of this preliminary study was to validate an instrument which accurately estimates dietary fat intake and can be easily administered to a large group of subjects. The study compared actual fat intake values obtained by plate waste measures to estimated fat intake values obtained by a 24-hour semiquantitative food frequency questionnaire (SFFQ). METHODS Dietary Assessment Inatrumenta The SFFQ integrates methodologies associated with 24-hour recalls and food frequency questionnaires, Unlike traditional food frequency questionnaires which assess food intake over an extended period of time, the SFFQ is designed to assess food intake in the last 24 hours. Therefore, like 24-hour recalls, the SFFQ must be given repeatedly to reflect variability in food intake over time. Because 24-hour hour recalls require trained interviewers to administer, their use is often limited to studies with small sample sizes. The SFFQ is a self-administered 24-hour recall which uses written rather than verbal prompts to facilitate diet recall. The SFFQ lists foods and fat containing condiments together to represent how foods are typically consumed. Condiments were defined as items which are added or served with foods and generally not consumed alone. Examples of fatcontaining condiments include gravy, sauces, butter, salad dressings, sour cream, peanut butter, cream cheese, etc. Foods such as bacon, milk and cheese were listed as both individual food items and as condiments associated with other foods. It was hypothesized that listing food items together with their associated condiments would serve as written prompts to facilitate recall. Because condiments are consumed frequently and are often high in fat, omission of these food items could significantly underestimate fat intake. To determine if listing fat-containing condiments along with food items facilitates recall, a traditional semiquantiative food frequency questionnaire (SFFQ-T) was also developed. The SFFQ-T listed the same food items as the SFFQ but listed fat containing condiments separately by their appropriate food category. To determine which condiments to list along with food items, university staff members (n=25) completed a 24-hour recall. Qualitative analysis was used to identify condiments associated with a variety of food items. This data was used for the initial development of SFFQ. The SFFQ was pretested (n=35) to assess food and condiment combinations which best represented food consumption patterns.
MEASURING FAT INTAKE
971
Food items included on the SFFQ and SFFQ-T were determined using two approaches. First, foods identified by Block et al. as the major contributors of fat in the U.S. diet were included (8). Second, the USDA Handbook 8 series published by the United States Department of Agriculture (USDA) was used to identify foods which had greater than 20 percent of their total calories derived from fat (8). Because of the extensiveness of this list, generic terms for foods were used. For example, the generic term cheese was listed rather than listing the many types of cheese available. The mean fat value for cheese and other generically listed foods was calculated and used for nutrient computation. A total of 140 different food items are listed on the SFFQ and SFFQ-T. All food items listed on the SFFQ and SFFQ-T included a standard serving size such as 3 ounces of hamburger or 1 tablespoon of butter. Commonly used portion sizes and household measures were used whenever possible (8,9,10). The standard serving size provides a reference to estimate the amount of the food item consumed. Subjects could indicate smaller or larger portions if appropriate. Sample Subjects were recruited from the student population attending summer school at Washington State University (WSU). A total of 62 adults volunteered to eat their meals (breakfast, lunch and dinner) at a campus dining hall on 2 consecutive Wednesdays. All meals were free of charge to the study participants. Foods consumed outside the dining hall were limited to food items not listed on the SFFQ or SFFQ-T (fruit juice, fresh fruits, soda pop, and plain coffee/tea). Nutrient Intake Assessment Subjects reported to the dining hall for their meals during specified time periods. Study participants were given a yellow tray to distinguish them from other dining hall patrons. Subjects were served cafeteria-style and selected from a large variety of menu items. In addition to main entrees, subjects could select items from the salad bar, deli, or grill. Dining hall employees were asked to give individuals with yellow trays premeasured serving sizes. Sandwich items served by the deli were weighed prior to serving. The weight per standard serving for all meal items was obtained from dining hall foodservice records. Upon selection of meal items, study participants left their trays with staff personnel and were directed to a reserved dining area. The number of servings for each food and beverage item on the subject’s tray was recorded. All food monitoring was conducted away from the subject’s presence. Self-serve items such as soup and cold cereal were weighed by research staff. The tray was then delivered to the subject. Subjects repeated this procedure every time they returned to the serving lines for additional food items. When the meal was finished, subjects were asked to leave their tray(s) in the dining area and not to remove or take any food items with them. Trays were removed by study personnel and food items remaining were measured or weighed and recorded.
K.A. BEERMAN et al.
972
Actual intake was determined by subtracting plate waste measures from serving size measures and weights.
of Dietary
Assessment Methods
All subjects were asked to report to a designated location by 11:OO a.m. the following morning to complete the dietary assessment. Subjects had no prior indication that they would be asked to recall their diet. Subjects were randomly assigned to receive either the SFFQ or the SFFQ-T. The study was repeated the following Wednesday. All meals were consumed at the dining hall and the following morning participants completed the opposite dietary assessment method from the previous week. The experimental set-up consists of two groups of randomly assigned subjects, two treatments (SFFQ and SFFQ-T) and two observation periods. This type of experimental design is consistent with the two treatment two period cross-over design described by Ratkowsky et al (11). If no difference is found between groups of subjects and no difference is found between the two periods (learning effect), then the statistical model for testing a difference between treatments reduces to the typical paired t-test.
Data Analysis Nutritionist III (version 7, N-Squared Computing) was used to analyze the nutrient composition of the dietary data. The data base for Nutritionist III is formulated from the USDA Handbook 8 series (9). Because the data base has a high percent of missing values for fatty acid composition, only total fat intake was calculated. All food items listed on the SFFQ and SFFQ-T were assigned a food code number prior to the data collection so that the responses could be analyzed in a consistent and unbiased manner. The food codes used to analyze the plate waste were based on the actual food items consumed. The nutrient analysis for e&h dietary assessment was rechecked by independent reviewers to ensure accuracy. Statistical analyses were performed using the Statistical Analysis System, (SAS Institute Inc., Cary, NC). A general linear model procedure was used to compare the predictive capabilities of each dietary assessment method. The dietary assessment method with a regression slope close to 1, a y-intercept close to 0 and a high correlation to actual fat intake (pCO.01) was considered to have the best predictive capability. RESULTS A total of 59 individuals, 30 females and 29 males, completed the study. The mean age of the subjects was 26.1 years e7.4) with ages ranging from 18 to 57. Females were slightly older than males, with mean ages of 27.8 elO.4) and 24.4 (54.3), respectively. The actual fat intake, calculated from plate waste measures, averaged 122.0 grams (+46.0). Females consumed on an average of 103.0 (k19.8) grams of fat compared 144.5 (k45.1) grams for males. The analysis did not detect a significant order or period effect (F=0.5, p=O.4825 and F=3.13 p=O.O824), respectively).
MEASURING FAT INTAKE
973
The mean fat intake estimated by the SFFQ was 118.8 grams (+51.9) compared to an actual fat intake of 120.7 (242.8). The results of the paired t-test indicated that the mean difference between actual fat intake and fat intake estimated by the SFFQ (-1.9 k-2.8 grams) did not differ significantly (p=O.4530). The mean fat intake estimated by the SFFQ-T was 106.5 grams (542.7) compared to an actual fat intake of 123.2 grams (k49.1). The results of the paired t-test indicated that the mean difference between actual fat intake and fat intake estimated by the SFFQ-T (-16.7 +3.8 grams of fat) was significantly different (p~O.0001). Of the two dietary assessment methods, the SFFQ was the best predictor of actual fat intake (Figure 1). The regression equation for the SFFQ had a slope of 0.85, a yintercept of 19.6, and a standard error of +0.05. A total of 86% of the variance in actual fat intake was accounted for using the SFFQ. The regression model for the SFFQ-T accounted for 63% of the variance in actual fat intake with a slope of 0.84. The standard error was +0.09 and the y-intercept was 33.8.
1
I ’
SFFQ-T
Fat (9) Estimated 350 300 250
150
200
Fat (g) Actual Figure 1 Regression analysis between actual fat intake and fat intake estimated by SFFQ-T and SFFQ Regression equations are (.) y=33.8 y=19.6 + .85x, r=.86, P
+ .84x, r=.63, P
+
SFFQ
974
K.A. BEERMAN et al.
DISCUSSION The goals of this preliminary study were: (1) to develop an instrument that provides an accurate estimate of dietary fat intake which can also be easily administered to a large group of people and (2) to determine if listing fat-containing condiments along with food items facilitates dietary recall. Studies indicate that added fats are the most under-reported food items (12,13,14,15). The results of this study demonstrate that the SFFQ, which lists condiments along with food items, resulted in a more accurate estimate of actual fat intake compared to the SFFQ-T which listed condiments separately by food category. This may not be an important consideration when assessing nutrients such as vitamins, minerals, protein or carbohydrates. However, because condiments are consumed frequently and are often high in fat, the importance of these items when assessing fat intake must not be overlooked. When testing a new dietary assessment instrument or methodology, two considerations must be addressed. First, the validity of an instrument must be evaluated. True validation requires direct measures of food consumption which can best be achieved in a controlled environment. This restrictive setting allows researchers to gain maximum control over potentially confounding variables such as reliance on self-reported measures of food intake. However, this methodology does not provide an indication of how well the dietary assessment method performs in a freeliving population (13). Therefore, a second consideration must be addressed, namely utility. Because, the SFFQ was tested under controlled conditions, it does not reflect its utility with a free-living population. The limited selection of foods in the dining hall is not representative of the variability in food consumption patterns present in a freeliving population. Therefore, further testing of the SFFQ is necessary to determine how the instrument compares to other accepted dietary assessment methods (16). The results of this study indicate that the SFFQ provided a valid estimate of fat intake. Clearly, more extensive testing of the SFFQ is necessary. Although limitations of semiquantitative food frequency questionnaires have been identified, (17) they do offer a practical approach to dietary assessment. The major limitation of the SFFQ is its length. Studies need to be conducted to determine which food items can be eliminated without compromising the accuracy of the questionnaire. The effectiveness of this instrument with different population groups needs to be tested. At present, the SFFQ has only been has tested with adults working in a university setting. It is possible that meals provided by dining services may be more accurately recalled than meals eaten at home. As with food frequency questionnaires, the potential for cultural bias is present with the SFFQ. It is unlikely that the food items and their associated condiments presented on the SFFQ are culturally appropriate for all ethnic populations. However, the methodology employed by this study could be used to design a similar instrument which reflects specific food patterns of different ethnic groups.
MEASURING FAT INTAKE
975
There are many potential uses for the SFFQ. In the clinical setting, the SFFQ could be used to help identify the primary sources of fat in the diet as well as monitor changes in food intake. It also provides an indication of dietary patterns. The SFFQ also has great potential as a research tool. Because it can be self-administered, it can be given or mailed to large population groups at a minimal cost. The SFFQ would also allow researchers to distinguish between added and total fat in the diet. ACKNOWLEDGEMENTS Funding for this research was provided by the Cffice of Grants and Research Development at Washington State University. The authors wish to express their appreciation to Wayne Tate for his computer assistance. REFERENCES 1.
Stamler J, Wentforth D, Neaton JD: Is relationshp between serum cholesterol and risk of premature death from coronary heart disease continuous and graded? Findings in 356,222 primary screenees af the Mulitiple Risk Factor Intervention Trial (MRFIT). J Am Med Assoc 1986; 256:2823-2828.
2.
Stamler J: Population studies. In Levy R, Rifkind BM, Dennis B, Ernst N (eds). Nutrition, lipids, and coronary heart diesease (26-88). New York Raven Press, 1979.
3.
Lipid Research Clinic Program. The Lipid Research Clinics Coronary Primary Prevention Trial results. II. The relationship of reduction in incidence of coronary heart disease to cholesterol lowering. J Am Med Assoc 1984; 251:365-374.
4.
McGee DL, Reed DM, Yano K, Tillotson J: Ten-year incidence of coronary heart disease in the Honolulu Heart Program: Relationship to nutrient intake. Am J Epidemiol 1984; 119:667-676.
5.
Anderson LM, Castelli OP, Levy D: Cholesterol and mortality: 30 years of followup from the Framingham study. J Am Med Assoc 1987; 256:2176-2180.
6.
Zulkifli SN, W SM: The food frequency method for dietary assessment. J Am Diet Assoc 1992; 92:681-685.
7.
Pao EM, Sykes KE, Cypel YS: Dietary intake- Large scale survey methods. Nutr Today 1990; 25:11-17.
8.
Block G, Dresser CM, Hartman AM, et al: Nutrient sources in the American diet: Quantitative data from the NHANES II survey. Am J Epidemiol 1985; 122:27-40.
9.
Composition of Foods, Handbook 8-l - 8-21 series, U.S. Department Agriculture, October 1975-1992.
of
976
K.A. BEERMAN
et al.
10.
National Center for Health Statistics. Plan and operation of the Second National Health and Nutrition Examination Survey, 1976-1980. Vital and Health Statistics. Series 1, No. 15 @HEW publication no. (PHS)81-1317). Health Research Statistics and Technology. W ~shington, DC: US GPO, July 1981.
11.
Ratkowsky DA, Evans MA, Alldredge JR: “Cross-over experiments, design, analysis, and application.” New YorkMarcel Dekker Inc, 1993.
12.
Barrett-Connor E: Nutrition epidemiology: How do we know what they ate? Am J Clin Nutr 1991; 543182%1878.
13.
Mertz W: Food intake measurements: Is there a “gold standard”? J Am Diet Assoc 1992; 92:1463-1465.
14.
Pao EM, Sykes KE, Cypel YS: USDA methodological research for larger-scale dietary intake surveys, 1975-88. Human Nutrition Information Service. USDA Home Economics Research Report No. 49, pp 121-156, 1989. Available from I-INIS, USDA, 6505 Belcrest Rd, Room 338, Hyatt&he, MD 20782;301-4368485.
15.
Jain MG, Harrison L, Howe GR, Miller AB: Evaluation of a self-administered dietary questionnaire for use in a cohort study. Am J Clin Nutr 1982; 36:931-935.
16.
Dittus K, Beer-manKA, Evans M: Utility of a semi-quantitative 24-hour food frequency questionnaire in estimating fat intake of a free-living population. Nutr Res 1994; 14:807-815.
17.
Sempos CT: Invited commentary: Some limitations of semiquantitative food frequency questionnaires. Am J of Epidemiol 1992; 135:1127-1132.
Accepted for publication January 11, 1995.
Pergamon
VALIDATION OF A DIETARY ASSESSMENT INSTRUMENT DESIGNED TO MEASURE FAT INTAKE Kathy A. Beerman’, F’hD, Kim L. Dittus2, PhD, and Marc A. Evans3, PhD ‘Department of Food Science and Human Nutrition Washington State University Pullman, Washington 99164-6376 2Department of Nutritional and Food Service Management Syracuse University Syracuse, New York 132441250 3Program in Statistics Washington State University Pullman, Washington 99164
ABSTRACT The purpose of this study was to validate an instrument which accurately estimates dietary fat intake. The study compared actual fat intake values obtained by plate waste measures to a 24-hour semiquantitative food frequency questionnaire (SFFQ). The SFFQ lists foods along with fat-containing condiments to represent how foods are typically consumed. It was hypothesized that listing food items together with their associated condiments would serve as written prompts to facilitate recall. To determine if listing fat-containing condiments along with food items facilitates recall, a traditional semiquantitative food frequency questionnaire (SFFQ-T) was developed as a comparison. The results of this study indicate that the SFFQ more accurately estimates actual fat intake compared to the SFFQ-T. Keywords:
Dietary Assessment,
Food Recall, Nutrition Anthropology
INTRODUCTION Several large epidemiological studies which specifically measured dietary fat intake utilized dietary assessment methods which were both costly and time consuming (1,2,3,4,5). Although these dietary assessment methods provide valuable information, not all researchers have sufficient funds for such extensive and labor intensive methods of data collection. As a result, researchers often depend on the use of food frequency questionnaires to assess fat intake. The greatest benefit of food frequencies is their relative ease and low cost when administered to large numbers of ‘Author to whom correspondence
should be addressed. 969
970
K.A. BEERMAN et al.
subjects (6,7). Although this methodology is useful to evaluate dietary intake patterns over time, a quantitative measure is often lacking. This limitation highlights the need for further research to develop dietary assessment tools which provide a quantified measure of fat intake and can also be easily administered to large groups of people. The purpose of this preliminary study was to validate an instrument which accurately estimates dietary fat intake and can be easily administered to a large group of subjects. The study compared actual fat intake values obtained by plate waste measures to estimated fat intake values obtained by a 24-hour semiquantitative food frequency questionnaire (SFFQ). METHODS Dietary Assessment Inatrumenta The SFFQ integrates methodologies associated with 24-hour recalls and food frequency questionnaires, Unlike traditional food frequency questionnaires which assess food intake over an extended period of time, the SFFQ is designed to assess food intake in the last 24 hours. Therefore, like 24-hour recalls, the SFFQ must be given repeatedly to reflect variability in food intake over time. Because 24-hour hour recalls require trained interviewers to administer, their use is often limited to studies with small sample sizes. The SFFQ is a self-administered 24-hour recall which uses written rather than verbal prompts to facilitate diet recall. The SFFQ lists foods and fat containing condiments together to represent how foods are typically consumed. Condiments were defined as items which are added or served with foods and generally not consumed alone. Examples of fatcontaining condiments include gravy, sauces, butter, salad dressings, sour cream, peanut butter, cream cheese, etc. Foods such as bacon, milk and cheese were listed as both individual food items and as condiments associated with other foods. It was hypothesized that listing food items together with their associated condiments would serve as written prompts to facilitate recall. Because condiments are consumed frequently and are often high in fat, omission of these food items could significantly underestimate fat intake. To determine if listing fat-containing condiments along with food items facilitates recall, a traditional semiquantiative food frequency questionnaire (SFFQ-T) was also developed. The SFFQ-T listed the same food items as the SFFQ but listed fat containing condiments separately by their appropriate food category. To determine which condiments to list along with food items, university staff members (n=25) completed a 24-hour recall. Qualitative analysis was used to identify condiments associated with a variety of food items. This data was used for the initial development of SFFQ. The SFFQ was pretested (n=35) to assess food and condiment combinations which best represented food consumption patterns.
MEASURING FAT INTAKE
971
Food items included on the SFFQ and SFFQ-T were determined using two approaches. First, foods identified by Block et al. as the major contributors of fat in the U.S. diet were included (8). Second, the USDA Handbook 8 series published by the United States Department of Agriculture (USDA) was used to identify foods which had greater than 20 percent of their total calories derived from fat (8). Because of the extensiveness of this list, generic terms for foods were used. For example, the generic term cheese was listed rather than listing the many types of cheese available. The mean fat value for cheese and other generically listed foods was calculated and used for nutrient computation. A total of 140 different food items are listed on the SFFQ and SFFQ-T. All food items listed on the SFFQ and SFFQ-T included a standard serving size such as 3 ounces of hamburger or 1 tablespoon of butter. Commonly used portion sizes and household measures were used whenever possible (8,9,10). The standard serving size provides a reference to estimate the amount of the food item consumed. Subjects could indicate smaller or larger portions if appropriate. Sample Subjects were recruited from the student population attending summer school at Washington State University (WSU). A total of 62 adults volunteered to eat their meals (breakfast, lunch and dinner) at a campus dining hall on 2 consecutive Wednesdays. All meals were free of charge to the study participants. Foods consumed outside the dining hall were limited to food items not listed on the SFFQ or SFFQ-T (fruit juice, fresh fruits, soda pop, and plain coffee/tea). Nutrient Intake Assessment Subjects reported to the dining hall for their meals during specified time periods. Study participants were given a yellow tray to distinguish them from other dining hall patrons. Subjects were served cafeteria-style and selected from a large variety of menu items. In addition to main entrees, subjects could select items from the salad bar, deli, or grill. Dining hall employees were asked to give individuals with yellow trays premeasured serving sizes. Sandwich items served by the deli were weighed prior to serving. The weight per standard serving for all meal items was obtained from dining hall foodservice records. Upon selection of meal items, study participants left their trays with staff personnel and were directed to a reserved dining area. The number of servings for each food and beverage item on the subject’s tray was recorded. All food monitoring was conducted away from the subject’s presence. Self-serve items such as soup and cold cereal were weighed by research staff. The tray was then delivered to the subject. Subjects repeated this procedure every time they returned to the serving lines for additional food items. When the meal was finished, subjects were asked to leave their tray(s) in the dining area and not to remove or take any food items with them. Trays were removed by study personnel and food items remaining were measured or weighed and recorded.
K.A. BEERMAN et al.
972
Actual intake was determined by subtracting plate waste measures from serving size measures and weights.
of Dietary
Assessment Methods
All subjects were asked to report to a designated location by 11:OO a.m. the following morning to complete the dietary assessment. Subjects had no prior indication that they would be asked to recall their diet. Subjects were randomly assigned to receive either the SFFQ or the SFFQ-T. The study was repeated the following Wednesday. All meals were consumed at the dining hall and the following morning participants completed the opposite dietary assessment method from the previous week. The experimental set-up consists of two groups of randomly assigned subjects, two treatments (SFFQ and SFFQ-T) and two observation periods. This type of experimental design is consistent with the two treatment two period cross-over design described by Ratkowsky et al (11). If no difference is found between groups of subjects and no difference is found between the two periods (learning effect), then the statistical model for testing a difference between treatments reduces to the typical paired t-test.
Data Analysis Nutritionist III (version 7, N-Squared Computing) was used to analyze the nutrient composition of the dietary data. The data base for Nutritionist III is formulated from the USDA Handbook 8 series (9). Because the data base has a high percent of missing values for fatty acid composition, only total fat intake was calculated. All food items listed on the SFFQ and SFFQ-T were assigned a food code number prior to the data collection so that the responses could be analyzed in a consistent and unbiased manner. The food codes used to analyze the plate waste were based on the actual food items consumed. The nutrient analysis for e&h dietary assessment was rechecked by independent reviewers to ensure accuracy. Statistical analyses were performed using the Statistical Analysis System, (SAS Institute Inc., Cary, NC). A general linear model procedure was used to compare the predictive capabilities of each dietary assessment method. The dietary assessment method with a regression slope close to 1, a y-intercept close to 0 and a high correlation to actual fat intake (pCO.01) was considered to have the best predictive capability. RESULTS A total of 59 individuals, 30 females and 29 males, completed the study. The mean age of the subjects was 26.1 years e7.4) with ages ranging from 18 to 57. Females were slightly older than males, with mean ages of 27.8 elO.4) and 24.4 (54.3), respectively. The actual fat intake, calculated from plate waste measures, averaged 122.0 grams (+46.0). Females consumed on an average of 103.0 (k19.8) grams of fat compared 144.5 (k45.1) grams for males. The analysis did not detect a significant order or period effect (F=0.5, p=O.4825 and F=3.13 p=O.O824), respectively).
MEASURING FAT INTAKE
973
The mean fat intake estimated by the SFFQ was 118.8 grams (+51.9) compared to an actual fat intake of 120.7 (242.8). The results of the paired t-test indicated that the mean difference between actual fat intake and fat intake estimated by the SFFQ (-1.9 k-2.8 grams) did not differ significantly (p=O.4530). The mean fat intake estimated by the SFFQ-T was 106.5 grams (542.7) compared to an actual fat intake of 123.2 grams (k49.1). The results of the paired t-test indicated that the mean difference between actual fat intake and fat intake estimated by the SFFQ-T (-16.7 +3.8 grams of fat) was significantly different (p~O.0001). Of the two dietary assessment methods, the SFFQ was the best predictor of actual fat intake (Figure 1). The regression equation for the SFFQ had a slope of 0.85, a yintercept of 19.6, and a standard error of +0.05. A total of 86% of the variance in actual fat intake was accounted for using the SFFQ. The regression model for the SFFQ-T accounted for 63% of the variance in actual fat intake with a slope of 0.84. The standard error was +0.09 and the y-intercept was 33.8.
1
I ’
SFFQ-T
Fat (9) Estimated 350 300 250
150
200
Fat (g) Actual Figure 1 Regression analysis between actual fat intake and fat intake estimated by SFFQ-T and SFFQ Regression equations are (.) y=33.8 y=19.6 + .85x, r=.86, P
+ .84x, r=.63, P
+
SFFQ
974
K.A. BEERMAN et al.
DISCUSSION The goals of this preliminary study were: (1) to develop an instrument that provides an accurate estimate of dietary fat intake which can also be easily administered to a large group of people and (2) to determine if listing fat-containing condiments along with food items facilitates dietary recall. Studies indicate that added fats are the most under-reported food items (12,13,14,15). The results of this study demonstrate that the SFFQ, which lists condiments along with food items, resulted in a more accurate estimate of actual fat intake compared to the SFFQ-T which listed condiments separately by food category. This may not be an important consideration when assessing nutrients such as vitamins, minerals, protein or carbohydrates. However, because condiments are consumed frequently and are often high in fat, the importance of these items when assessing fat intake must not be overlooked. When testing a new dietary assessment instrument or methodology, two considerations must be addressed. First, the validity of an instrument must be evaluated. True validation requires direct measures of food consumption which can best be achieved in a controlled environment. This restrictive setting allows researchers to gain maximum control over potentially confounding variables such as reliance on self-reported measures of food intake. However, this methodology does not provide an indication of how well the dietary assessment method performs in a freeliving population (13). Therefore, a second consideration must be addressed, namely utility. Because, the SFFQ was tested under controlled conditions, it does not reflect its utility with a free-living population. The limited selection of foods in the dining hall is not representative of the variability in food consumption patterns present in a freeliving population. Therefore, further testing of the SFFQ is necessary to determine how the instrument compares to other accepted dietary assessment methods (16). The results of this study indicate that the SFFQ provided a valid estimate of fat intake. Clearly, more extensive testing of the SFFQ is necessary. Although limitations of semiquantitative food frequency questionnaires have been identified, (17) they do offer a practical approach to dietary assessment. The major limitation of the SFFQ is its length. Studies need to be conducted to determine which food items can be eliminated without compromising the accuracy of the questionnaire. The effectiveness of this instrument with different population groups needs to be tested. At present, the SFFQ has only been has tested with adults working in a university setting. It is possible that meals provided by dining services may be more accurately recalled than meals eaten at home. As with food frequency questionnaires, the potential for cultural bias is present with the SFFQ. It is unlikely that the food items and their associated condiments presented on the SFFQ are culturally appropriate for all ethnic populations. However, the methodology employed by this study could be used to design a similar instrument which reflects specific food patterns of different ethnic groups.
MEASURING FAT INTAKE
975
There are many potential uses for the SFFQ. In the clinical setting, the SFFQ could be used to help identify the primary sources of fat in the diet as well as monitor changes in food intake. It also provides an indication of dietary patterns. The SFFQ also has great potential as a research tool. Because it can be self-administered, it can be given or mailed to large population groups at a minimal cost. The SFFQ would also allow researchers to distinguish between added and total fat in the diet. ACKNOWLEDGEMENTS Funding for this research was provided by the Cffice of Grants and Research Development at Washington State University. The authors wish to express their appreciation to Wayne Tate for his computer assistance. REFERENCES 1.
Stamler J, Wentforth D, Neaton JD: Is relationshp between serum cholesterol and risk of premature death from coronary heart disease continuous and graded? Findings in 356,222 primary screenees af the Mulitiple Risk Factor Intervention Trial (MRFIT). J Am Med Assoc 1986; 256:2823-2828.
2.
Stamler J: Population studies. In Levy R, Rifkind BM, Dennis B, Ernst N (eds). Nutrition, lipids, and coronary heart diesease (26-88). New York Raven Press, 1979.
3.
Lipid Research Clinic Program. The Lipid Research Clinics Coronary Primary Prevention Trial results. II. The relationship of reduction in incidence of coronary heart disease to cholesterol lowering. J Am Med Assoc 1984; 251:365-374.
4.
McGee DL, Reed DM, Yano K, Tillotson J: Ten-year incidence of coronary heart disease in the Honolulu Heart Program: Relationship to nutrient intake. Am J Epidemiol 1984; 119:667-676.
5.
Anderson LM, Castelli OP, Levy D: Cholesterol and mortality: 30 years of followup from the Framingham study. J Am Med Assoc 1987; 256:2176-2180.
6.
Zulkifli SN, W SM: The food frequency method for dietary assessment. J Am Diet Assoc 1992; 92:681-685.
7.
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Accepted for publication January 11, 1995.