Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-26T08:20:00.186Z Has data issue: false hasContentIssue false

Validation of MEDFICTS Dietary Assessment Questionnaire in Turkish Population

Published online by Cambridge University Press:  24 May 2021

Zeynep Göktaş*
Affiliation:
Hacettepe University, Faculty of Health Sciences, Department of Nutrition and Dietetics, Ankara06100, Turkey
Derya Dikmen
Affiliation:
Hacettepe University, Faculty of Health Sciences, Department of Nutrition and Dietetics, Ankara06100, Turkey
Neslişah Rakıcıoğlu
Affiliation:
Hacettepe University, Faculty of Health Sciences, Department of Nutrition and Dietetics, Ankara06100, Turkey
*
*Corresponding author: Email zeynep.goktas@hacettepe.edu.tr
Rights & Permissions [Opens in a new window]

Abstract

Objective:

The purpose of this study was to assess the validity of MEDFICTS (Meats, Eggs, Dairy, Fried foods, fat In baked goods, Convenience foods, fats added at the Table, Snacks) questionnaire in Turkish population.

Design:

MEDFICTS questionnaire is a brief dietary assessment tool developed as part of the National Cholesterol Education Program Adult Treatment Panel guidelines, and it measures the adherence to Step 1 and Step 2 diets that are recommended for the prevention and treatment of CVD. MEDFICTS questionnaire was administered with 3-d food record to compare overall dietary fat intake.

Setting:

This study was conducted at the Hacettepe University (Ankara, Turkey) in 2017.

Participants:

Subjects were university students, recruited from several departments of Hacettepe University by trained dietitians. A total of 442 adults (249 females and 194 males) between the ages of 18 and 31 years participated in the study. Students with CVD were excluded.

Results:

Total fat intake ratio was higher than the recommended level for both males and females (39·4 % and 39·9 %, respectively). Mean MEDCISTS score was 66·3 ± 27·24 points. Total energy, total fat, SFA and cholesterol intakes from 3-d food records within the different MEDFICTS diet groups significantly differed (P < 0·001 for all). Receiver operating characteristics curve analysis demonstrated that a cut-off point of 60 showed 80 % sensitivity and 65 % specificity.

Conclusions:

Our data indicate that the MEDFICTS questionnaire is moderately accurate; however, sensitivity analysis did not demonstrate the recommended 40 points as an optimal cut-off point for Turkish population.

Type
Short Communication
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of The Nutrition Society

CVD is still the number one cause of death in developed countries despite the declining trend of global burden of CVD in the last decade(Reference Writing Group, Mozaffarian and Benjamin1,Reference Writing Group, Mozaffarian and Benjamin2) . CVD is the cause of one of every three deaths in the USA and one of every four deaths in Europe(Reference Writing Group, Mozaffarian and Benjamin2,Reference Townsend, Nichols and Scarborough3) . Furthermore, in developing countries, the incidence of CVD dramatically increased in the last 25 years due to the transition to Western diet in these countries(4,Reference Yusuf, Reddy and Ounpuu5) . In Turkey, according to Chronic Diseases and Risk Factors Survey, CVD is also the number one cause of death with a 20 % rate of myocardial infarction(Reference Dinc, Sozmen and Gerceklioglu6,Reference Unal, Ergor and Horasan7) . All deaths from CVD are at 42 % in Turkey, and in the elderly population, this ratio increases to 54 %(Reference Unal, Ergor and Horasan7). According to Turkish Adult Risk Factor Study (TEKHARF)-2017, there are 3·5 million people in Turkey suffering from CHD and, with the ageing population, there seems to be a 4 % increase annually(Reference Onat, Can and Yuksrl8). Turkey has the highest coronary mortality rates in the 45–75-year-old population when compared with European countries(Reference Onat, Can and Yuksrl8).

Dietary fat and cholesterol intake is considered as a risk factor for CVD, and behaviour changes towards decreasing the excess intake of fat and cholesterol seem to be beneficial for the prevention of CVD(Reference Ros, Martinez-Gonzalez and Estruch9). For the modification of dietary habits, it is crucial to assess the diet accurately and efficiently(Reference Liese, Krebs-Smith and Subar10). Commonly used dietary assessment tools are dietary records, dietary history, FFQ and 24-h dietary recall methods(Reference Shim, Oh and Kim11). Majority of these methods take time to collect accurately and require software to analyse the fat and cholesterol intakes. Therefore, it could be very helpful to develop a rapid and accurate tool to measure far and cholesterol intake(Reference Kris-Etherton, Eissenstat and Jaax12). MEDFICTS (Meats, Eggs, Dairy, Fried foods, fat In baked goods, Convenience foods, fats added at the Table, Snacks) is a brief dietary assessment tool developed as part of the National Cholesterol Education Program Adult Treatment Panel guidelines(Reference Kris-Etherton, Eissenstat and Jaax12). It measures the adherence to Step 1 and Step 2 diets that are recommended for the prevention and treatment of CVD. Step 1 diet has <10 % of energy intake from saturated fat, <30 % of energy intake from total fat and <300 mg of dietary cholesterol per day. Step 2 diet has <7 % of energy from saturated fat, <200 mg dietary cholesterol per day and <30 % of energy intake from fat(Reference Krauss, Eckel and Howard13,14) .

In this study, we compared MEDFICTS questionnaire scores to total fat, SFA and cholesterol intake levels from 3-d food records in a group of university students without any CVD.

Methods

Subjects

Subjects were university students, recruited from several departments of Hacettepe University by trained dietitians in Ankara, Turkey. A total of 442 adults (249 females and 194 males) between the ages of 18 and 31 years participated in the study. The exclusion criteria were as follows: CVD, CHD, hypertension, hyperlipidaemia, CHD, cerebrovascular disease, previous heart surgery, any autoimmune disease, any chronic metabolic disease, any mental disease and pregnancy. All subjects were informed, and before testing, each participant gave written consent. The study was approved by the Institutional Review Board of Hacettepe University.

Questionnaire

All subjects completed a short questionnaire, administered by a trained dietitian. Questions intended to collect data about sociodemographic information such as age, gender, education status, nutritional habits, meal frequency and physical activity habits. Anthropometric measurements like body weight (kg) and height (cm) were self-reported by the subjects.

MEDFICTS

The MEDFICTS questionnaire(Reference Kris-Etherton, Eissenstat and Jaax12) composed of twenty food groups in nine sections: meats, eggs, dairy, frozen desserts, frying foods, in baked goods, convenience foods, table fats and snacks. Each food group in each section is questioned for weekly consumption frequency as rarely/never, 3 or less and 4 or less and for serving size as small, average and large for the meats group and as ≤1, 2 and ≥3 for the rest of the food groups. Points of weekly consumption frequency (0 = rarely/never, 3 = 3 or less, and 7 = 4 or more) are multiplied by serving size points (1 = small or ≤1, 2 = average or 2, and 3 = large or ≥3). For the lean meats group only, 6 points can be included if only there is a large size consumption. Subsequently, the sum is taken for all food items to calculate the final MEDFICTS score. A score of ≥70 is considered as high-fat diet, 40–70 is adherence to step 1 diet and <40 is adherence to step 2 diet(Reference Kris-Etherton, Eissenstat and Jaax12).

In this study, the MEDFICTS questionnaire was translated and adjusted to Turkish language and food culture using the Brislin method(Reference Brislin and Leibowitz15). Fifteen native Turkish speaker trained dietitians translated the questionnaire from English to Turkish. Two native English speaker experts translated the form back to English. These translated forms were compared with the original form by an expert panel, and after deciding on necessary adjustment, the last version of the Turkish MEDFICTS was formed.

All participants repeated the MEDFICTS questionnaire 2 weeks after baseline administration to detect the test–retest reliability.

3-Day food records

All subjects were trained by a dietitian on how to keep a 3-d food record. Participants were asked to keep dietary records for three consecutive days including 1 weekend day. To minimise the recollection error, participants were asked to write down their food intake immediately after the meals. To minimise the portion size errors, participants were asked to record the food amounts using household measurements. After receiving the 3-d food records, a trained dietitian reviewed the records and interviewed the participant to clarify any unclear or missing information. Consecutively, all food records were reviewed by a supervisor dietitian for accuracy.

Statistical analysis

Statistical analyses were performed using the computer programme SPSS 22.0 (Armonk, NY: IBM Corp). Kolmogorov–Smirnov test was used to assess normality. Student’s t test was used for mean comparison of two groups. One-way ANOVA was used for comparison of more than two group means. For post hoc analysis, Bonferroni correction was used with equal variances and Games–Howell test was used with unequal variances. Correlations among variables were tested with Pearson’s correlation coefficient. Nominal data were examined using χ 2 test. Internal consistency of the MEDFICTS questionnaire was evaluated using Cronbach’s alpha. Test–retest reliability was evaluated by intra-class correlation coefficient. Receiver operating characteristics curve analysis was used to measure the sensitivity and specificity of MEDFICTS cut-off points. Data were presented as means ± SD and frequencies. Differences were considered significant at P < 0·05.

Results

Average ages of the participants were 23·3 ± 1·48 years for females and 23·6 ± 1·70 years for males. Male participants had a slightly higher average BMI than females (23·6 ± 4·56 kg/m2 and 24·9 ± 4·16 kg/m2, respectively) (Supplementary data)

Energy and macronutrient ratios for energy of the participants from 3-d food records are listed in Table 1. Macronutrient ratios for energy did not show any difference between genders (P > 0·05). Total fat ratio was higher than the recommended level for both males and females (39·4 and 39·9 %, respectively). Furthermore, SFA intake ratios were also higher than the recommended level for both gender groups (13·5 % for females and 12·9 % for males). MEDFICTS total score and diet group distribution of the participants are listed in Table 1. Mean MEDCISTS score was 66·3 ± 27·24 points. Males had significantly higher MEDFICTS scores than females (70·1 ± 30·24 and 63·3 ± 24·29, respectively; P = 0·011). According to MEDFICTS scores, 41·1 % of the participants have a high-fat diet and only 15·4 % of the participants have a low-fat diet. Total energy, total fat, SFA and cholesterol intakes from 3-d food records within the different MEDFICTS diet groups significantly differed (Table 2, P < 0·001 for all).

Table 1 Energy and macronutrient contents from 3-d food records and MEDFICTS scores (n 442)

MEDFICTS, Meats, Eggs, Dairy, Fried foods, fat In baked goods, Convenience foods, fats added at the Table, and Snacks.

*t test and χ 2 test were used for analysis.

Table 2 Comparison of energy, fat and cholesterol intakes from 3-d food records to MEDFICTS diet groups (n 442)

MEDFICTS, Meats, Eggs, Dairy, Fried foods, fat In baked goods, Convenience foods, fats added at the Table, and Snacks.

* ANOVA test was used for analysis.

Furthermore, receiver operating characteristics curve analysis demonstrated that a cut-off point of 60 showed 80 % sensitivity and 65 % specificity (Fig. 1). When receiver operating characteristic curve analysis was performed by gender, for males a cut-off point of 56 showed 84 % sensitivity and 78 % specificity and for females a cut-off point of 51 showed 72 % sensitivity and 56 % specificity (Supplementary data).

Fig. 1 Receiver operating characteristic (ROC) curve showing the relationship between Adult Treatment Panel (ATP) guidelines and MEDFICTS groups at a cut-off point of 60. ROC AUC: 0·801, P < 0·001. Optimal cut-off point 60, 80% Sensitivity, 65% Specificity

Test–retest reliability was tested with intra-class correlation coefficient, and intra-class correlation coefficient value was found as 0·891 (Supplementary data).

Discussion

The prevalence of CVD in Turkey is estimated to increase to 4·2 million adults by 2025 and to 5·4 million by 2035, which is a 26 % and 58 % increase, respectively, compared with 2016(Reference Balbay, Gagnon-Arpin and Malhan16). According to AHA guidelines, a diet pattern increasing the intake of fish, nuts, whole grains, fruits and vegetables, and legumes, decreasing the intake of Na and cholesterol, replacing saturated fats with polyunsaturated and monounsaturated fats, avoiding trans fats and limiting the intake of processed meats, refined carbohydrates and sweetened drinks may reduce the risk of CVD(Reference Arnett, Blumenthal and Albert17,Reference Van Horn, Carson and Appel18) . Therefore, assessing dietary fat intake can be useful to implement an effective dietary intervention. In this study, we compared the MEDFICTS questionnaire with 3-d food records to evaluate the validity of MEDFICTS in Turkish population. Our data indicate that the MEDFICTS questionnaire is moderately accurate with 80 % sensitivity and 65 % specificity. However, sensitivity analysis did not demonstrate the recommended 40 points as an optimal cut-off point for Turkish population. Instead, at 60 cut-off point, maximum sensitivity (80 %) without significant loss in specificity (65 %) was achieved. Overall high sensitivity at the 60 cut-off point can be interpreted as MEDFICTS’ ability to identify people who are adherent to Step 1 Adult Treatment Panel guidelines; however, specificity seems to be decreasing with lower cut-off points; therefore, it may be ruling out high-fat dietary patterns. Low specificity with lower points may be due to the underestimation of fats and oils used in everyday cooking in Turkish population. Majority of Turkish cuisine recipes involve a fat or oil-based starter which is not reflected in MEDFICTS questionnaire.

In conclusion, although the MEDFICTS questionnaire may be used to identify people who are adherent to Step 1 Adult Treatment Panel guidelines, it needs to be adjusted to better estimate the overall dietary fat intake of Turkish population.

Acknowledgements

Acknowledgements: We thank our graduate students and colleagues for valuable help in preparation of the questionnaire. Financial support: The authors declare no funding or financial support. Conflict of interest: There are no conflicts of interest. Authorship: Z.G., D.D. and N.R. formulated the research question, designed the study and collected the data. Z.G. analysed the data and wrote the first draft with contributions from D.D. and N.R. All authors reviewed and commented on subsequent drafts of the manuscript. Ethics of human subject participation: This study was conducted according to the guidelines laid down in the Declaration of Helsinki, and all procedures involving research participants were approved by the Institutional Review Board of Hacettepe University. Written informed consent was obtained from all subjects.

Supplementary material

For supplementary material accompanying this paper visit https://doi.org/10.1017/S1368980021002299

References

Writing Group, M, Mozaffarian, D, Benjamin, EJ et al. (2016) Executive summary: heart disease and stroke statistics--2016 update: a report from the American Heart Association. Circulation 133, 447454.Google Scholar
Writing Group, M, Mozaffarian, D, Benjamin, EJ et al. (2016) Heart disease and stroke statistics-2016 update: a report from the American Heart Association. Circulation 133, e38360.Google Scholar
Townsend, N, Nichols, M, Scarborough, P et al. (2015) Cardiovascular disease in Europe 2015: epidemiological update. Eur Heart J 36, 26732674.CrossRefGoogle ScholarPubMed
Mortality GBD & Causes of Death C (2015) Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 385, 117171.CrossRefGoogle Scholar
Yusuf, S, Reddy, S, Ounpuu, S et al. (2001) Global burden of cardiovascular diseases: part II: variations in cardiovascular disease by specific ethnic groups and geographic regions and prevention strategies. Circulation 104, 28552864.CrossRefGoogle ScholarPubMed
Dinc, G, Sozmen, K, Gerceklioglu, G et al. (2013) Decreasing trends in cardiovascular mortality in Turkey between 1988 and 2008. BMC Public Health 13, 896.CrossRefGoogle ScholarPubMed
Unal, B, Ergor, G, Horasan, G et al. (2013) Chronic Diseases and Risk Factors Survey in Turkey. Ankara: Ministry of Health.Google Scholar
Onat, A, Can, G, Yuksrl, H et al. (2017) Turkish Adult Risk Factor Study (TEKHARF). Istanbul, Turkey: Logos Publishing.Google Scholar
Ros, E, Martinez-Gonzalez, MA, Estruch, R et al. (2014) Mediterranean diet and cardiovascular health: teachings of the PREDIMED study. Adv Nutr 5, 330S336S.CrossRefGoogle ScholarPubMed
Liese, AD, Krebs-Smith, SM, Subar, AF et al. (2015) The Dietary Patterns Methods Project: synthesis of findings across cohorts and relevance to dietary guidance. J Nutr 145, 393402.CrossRefGoogle ScholarPubMed
Shim, JS, Oh, K & Kim, HC (2014) Dietary assessment methods in epidemiologic studies. Epidemiol Health 36, e2014009.CrossRefGoogle ScholarPubMed
Kris-Etherton, P, Eissenstat, B, Jaax, S et al. (2001) Validation for MEDFICTS, a dietary assessment instrument for evaluating adherence to total and saturated fat recommendations of the National Cholesterol Education Program Step 1 and Step 2 diets. J Am Diet Assoc 101, 8186.CrossRefGoogle ScholarPubMed
Krauss, RM, Eckel, RH, Howard, B et al. (2000) AHA Dietary Guidelines: revision 2000: a statement for healthcare professionals from the Nutrition Committee of the American Heart Association. Circulation 102, 22842299.CrossRefGoogle ScholarPubMed
(1994) National Cholesterol Education Program. Second report of the expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel II). Circulation 89, 13331445. doi: 10.1161/01.cir.89.3.1333.CrossRefGoogle Scholar
Brislin, RW & Leibowitz, HW (1970) The effect of separation between test and comparison objects on size constancy at various age-levels. Am J Psychol 83, 372376.CrossRefGoogle ScholarPubMed
Balbay, Y, Gagnon-Arpin, I, Malhan, S et al. (2018) Modeling the burden of cardiovascular disease in Turkey. Anatol J Cardiol 20, 235240.Google ScholarPubMed
Arnett, DK, Blumenthal, RS, Albert, MA et al. (2019) 2019 ACC/AHA Guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 140, e596e646.Google Scholar
Van Horn, L, Carson, JA, Appel, LJ et al. (2016) Recommended Dietary Pattern to Achieve Adherence to the American Heart Association/American College of Cardiology (AHA/ACC) Guidelines: a scientific statement from the American Heart Association. Circulation 134, e505e529.CrossRefGoogle Scholar
Figure 0

Table 1 Energy and macronutrient contents from 3-d food records and MEDFICTS scores (n 442)

Figure 1

Table 2 Comparison of energy, fat and cholesterol intakes from 3-d food records to MEDFICTS diet groups (n 442)

Figure 2

Fig. 1 Receiver operating characteristic (ROC) curve showing the relationship between Adult Treatment Panel (ATP) guidelines and MEDFICTS groups at a cut-off point of 60. ROC AUC: 0·801, P < 0·001. Optimal cut-off point 60, 80% Sensitivity, 65% Specificity

Supplementary material: File

Göktaş et al. supplementary material

Tables S1-S2 and Figures S1-S2

Download Göktaş et al. supplementary material(File)
File 56.5 KB