Non-communicable diseases such as CVD and cancer are estimated to be responsible for 60 % of world deaths, and dietary habits appear to be strong determinants for their development(1). Therefore, analysis of dietary habits in large populations to identify dietary deficiencies is of paramount importance. FFQ are widely used to estimate food intake in large epidemiological settings. However, full-length FFQ are time consuming for participants and thus are unsuitable for routine clinical use and for non-dietary studies incorporating a broad spectrum of measurements. For this reason, several brief screening tools have been developed to assess intakes of major food groups. Most of these short dietary questionnaires focus on one or two dietary components(Reference Wiens, Schulzer and Chen2–Reference Thompson, Midthune and Subar7). Only a few brief screeners assess a broader range of dietary intake(Reference Mochari, Gao and Mosca8, Reference Rifas-Shiman, Willett and Lobb9), an approach that might help to identify subjects at nutritional risk by indicating their level of adherence to diet quality recommendations. To address the need for a brief, effective instrument, we designed short dietary screeners for two different settings. The brief Mediterranean Diet Screener (bMDSC) is intended to assess adherence to the healthy Mediterranean dietary pattern. The short Diet Quality Screener (sDQS) was created to estimate overall diet quality in primary-care settings. We calculated a modified Mediterranean Diet Score (mMDS) and an Antioxidant Score (ANTOX-S) from the bMDSC and a Diet Quality Index (DQI) from the sDQS. The rationale for constructing the mMDS, ANTOX-S and DQI was adherence to the Mediterranean diet, antioxidant capacity of foods and dietary recommendations for the Spanish population, respectively(Reference Willett, Sacks and Trichopoulou10, Reference Aranceta and Serra-Majem11). The objective of the present study was first to analyse the degree to which the dietary indices derived from the bMDSC and sDQI questionnaires correlate with those obtained by a reference method (concurrent validity) and second to determine the ability of the screeners to measure diet quality (construct validity) in a random subsample of a population-based cohort in Spain.
Material and methods
Study participants
The validation study consecutively selected 150 men and women from a population-based cross-sectional survey performed in Girona Province between 2004 and 2006. That survey of 6352 randomly selected free-living men and women, aged 3 to 80 years (71·5 % response rate), obtained sociodemographic, anthropometric and lifestyle variables including diet from all participants. Of those initially recruited, 133 agreed to participate in the validation study and 102 completed both short dietary screeners and a 24 h food recall questionnaire on at least ten occasions. The study was approved by the institutional ethics committee (Comités Éticos de Investigación Clínica–Instituto Municipal de Asistencia Sanitaria, Barcelona, Spain), participants signed an informed consent, and results of the examination were sent to all participants.
Measurement of non-dietary variables
Information on demographic and socio-economic variables, co-morbidity history, diet and lifestyle factors, including tobacco smoking and alcohol consumption, was obtained through structured standard questionnaires administered by trained personnel(Reference Baena-Díez, Alzamora-Sas and Grau12).
Leisure-time physical activity was measured by the Minnesota leisure-time physical activity questionnaire, also administered by a trained interviewer(Reference Elosua, Garcia and Aguilar13, Reference Elosua, Marrugat and Molina14).
Dietary assessment instruments
Multiple 24 h recalls (reference method)
Monthly 24 h recalls were collected by telephone over a 12-month period by a trained interviewer and data from at least ten recalls were required for inclusion in the analysis. Dietary recalls were conducted on non-consecutive days, including at least five weekdays and one weekend day, and participants were not alerted in any way to the date when they would be interviewed. Food intake data recorded during the 24 h recalls were grouped into the food-based dietary components of the bMDSC and sDQS for analysis.
We validated the dietary quality estimates from the bMDSC and sDQS by comparing them with the data gathered from the 24 h recalls.
The brief Mediterranean diet screener
The bMDSC was originally developed for another study(Reference Peters, Schneider and Greven15). The objective of this screener was to calculate adherence to the Mediterranean diet and to qualitatively estimate dietary antioxidant intake. For this reason we included food items considered characteristic for the Mediterranean diet and food items with high antioxidant capacity. After participants had completed the multiple 24 h recalls they received the bMDSC by postal mail, together with short instructions on completion of the screener. Participants were asked to report their consumption frequency of fifteen selected food items during the preceding year: (i) pulses; (ii) green leafy and cabbage-like vegetables; (iii) other vegetables; (iv) red meat, sausages and cold cuts; (v) white meat; (vi) blue fish; (vii) white fish; (viii) dairy products; (ix) citrus fruits and berries; (x) other fruits; (xi) wholegrain products; (xii) olive oil; (xiii) nuts; (xiv) juice; (xv) red wine. The eight frequency categories range from ‘never’ to ‘more than 4 times a day’. Standardized portion sizes were used to quantify food intake(Reference Serra Majem16, Reference Salas Salvado, Bonada and Tralerro17).
The short diet quality screener
The sDQS was developed for use in primary-care settings to estimate overall diet quality. Within 1 week of returning the completed bMDSC, the participants received the sDQS, which was mailed to them with brief instructions on completion of the screener. Subjects were asked to base their responses on their usual dietary behaviours over the previous 12 months, reporting their habitual intake of eighteen food items grouped in three food categories. These categories were based on recommended frequencies of food intake(Reference Aranceta and Serra-Majem11). Standardized portion sizes were used to quantify frequency of food intake(Reference Serra Majem16, Reference Salas Salvado, Bonada and Tralerro17). The first category includes eight items: (i) bread; (ii) vegetables (cooked and raw); (iii) fruit; (iv) milk and yoghurt; (v) rice and pasta; (vi) vegetable oils (olive and sunflower); (vii) alcoholic beverages; and (viii) cereals (cornflakes, muesli, etc.). The second category includes seven items: (i) meat; (ii) sausages; (iii) cheese; (iv) pastry; (v) animal fat (butter, lard); (vi) other vegetable oils (palm oil, etc.); and (vii) fast food. The third category had just three items: (i) fish; (ii) legumes; and (iii) nuts.
Food frequency consumption was arranged in three frequency response categories: (i) ‘less than once a day’, ‘once a day’ and ‘more than once a day’ for the eight food items in the first category; (ii) ‘less than 4 times a week’, ‘4 to 6 times a week’ and ‘once a day’ for the seven food items in the second category; and (iii) ‘less than 2 times a week’, ‘2 to 3 times a week’ and ‘4 or more times a week’ for the three food items in the third food category. The aim of the study was to validate the scores by analysis of the corresponding food items. Therefore, food items listed in the 24 h recall that were not part of the scores obtained by the screeners were omitted.
Calculation of dietary scores
The antioxidant food and modified Mediterranean diet scores derived from the brief Mediterranean diet screener
The bMDSC provides two sub-scores: the antioxidant food score (ANTOX-S) and the modified Mediterranean diet score (mMDS; Table 1). The standardized portion size of each food group was multiplied by the corresponding frequency response category to obtain the amount of intake in g/d. Tertile distribution of food items included in the ANTOX-S and mMDS was calculated. The ANTOX-S was calculated by assigning 1 point for lowest tertile ratings, 2 points for medium tertile ratings and 3 points for highest tertile ratings for the following food items: (i) citrus fruits; (ii) other fruits; (iii) green leafy vegetables; (iv) other vegetables; (v) fruit juice; and (vii) red wine. The mMDS includes ten food items: (i) vegetables (green leafy vegetables and other vegetables); (ii) fruits (citrus fruits and other fruits); (iii) dairy products; (iv) red meat and sausages; (v) wholegrain products; (vi) fish; (vii) legumes; (viii) nuts; (ix) red wine; and (x) olive oil. Tertile ratings for vegetables, fruits, wholegrain products, legumes, nuts and olive oil were scored as mentioned above. Tertile distribution ratings of two food groups (dairy products; red meat and sausages) were coded inversely (first tertile 3 points, second tertile 2 points, and third tertile 1 point) because these foods are not considered part of the Mediterranean diet. Moderate red wine consumption (1–2 glasses/d) was coded as 3 and included as a favourable component in the score; no red wine consumption and more than 2 glasses/d were both coded as 1. These values for the food items were added together to determine the ANTOX-S and mMDS, which range from 6 (very low adherence) to 18 (optimal adherence), and from 10 (very low adherence) to 30 (optimal adherence), respectively.
*Included in the mMDS.
†Included in the ANTOX-S.
‡Combined in the mMDS ‘vegetable’ food group.
§Combined in the mMDS ‘fish’ food group.
∥Combined in the mMDS ‘fruit’ group.
The diet quality index derived from the short diet quality screener
The diet quality index (DQI) includes three food group categories (Table 2): with the exception of alcoholic beverage consumption, daily intake of 1 portion of foods in the first food group category is scored 2; lower and higher intakes are scored 1 and 3, respectively. Daily consumption of one alcoholic drink (1 bottle of beer, 1 glass of wine, or 1 cup of liquor equivalent to approximately 12 g of alcohol) is scored 3; lower and higher intakes are scored 1. Consumption of foods considered detrimental in the second food group category is scored 2 if reported as 4–6 times per week; more and less frequent consumption are scored 1 and 3, respectively. High consumption (4 or more times per week) of food items considered beneficial of the third food group category is scored 3. Intakes of 2–3 times and less than twice a week are scored 2 and 1, respectively. All food item scores are added up. The total possible score ranges from 18 to 54.
Statistical analyses
Differences in continuous variables with normal distribution were compared between participant and non-participant groups using Student's t test; the Mann–Whitney U test was used otherwise. The χ 2 test was used for categorical variables. Relative agreement of the dietary quality indices, indicating the agreement between test and reference method in the ranking of subjects, was assessed by calculating Pearson product-moment correlation coefficients to compare the 24 h recall scores (reference method) with the subject's scores on the short screeners (test method). In addition, cross-classification models were fitted to test for gross misclassification of rating for the DQI, mMDS and ANTOX-S obtained from the test v. the reference method. Gross misclassification was defined as classification in the opposite tertile (lowest and highest) by the test method compared with the reference method. The proportions of correctly (i.e. similarly) categorized participants were also calculated.
Absolute agreement between scores derived from the short screeners and the 24 h recalls was analysed by the intra-class correlation coefficient (ICC). Additionally, we applied the limits of agreement (LOA) method(Reference Bland and Altman18) expressed as a percentage. A mean agreement (difference of means) of 100 % indicates total agreement between the test and reference method. For each score we plotted the difference between methods against the mean of the two. Linear regression analysis of mean differences of the dietary indices, as the dependent variable, and the mean of the corresponding dietary indices obtained by the test and the reference, as the independent variable, was performed to detect proportional biases (i.e. mean difference was significantly changed by the magnitude ratings for dietary indices). We applied the criteria for a reasonable agreement between estimates according to Ambrosini and colleagues(Reference Ambrosini, van Roosbroeck and Mackerras19): (i) LOA of the dietary indices derived from the test method were between one-half (50 %) and twice (200 %) their reference method estimate; and (ii) there were no significant changes of mean differences over the range of average ratings for the dietary indices.
To analyse construct validity, we hypothesized a relationship between a higher scoring for the dietary indices obtained by the short screeners and a more favourable nutrient intake profile reported on the 24 h recalls. General linear modelling procedures (GLM) were used to estimate nutrient intakes according to the tertile distribution of the dietary indices (DQI, mMDS and ANTOX-S). Linear trend was tested by including the categorized variable (tertile distribution of the dietary indices as continuous in this model). The polynomial contrast was used to determine P for linear trend for continuous variables and a post hoc Bonferroni correction for multiple comparisons was carried out. Differences were considered significant if P < 0·05. The SPSS for Windows statistical software package version 15 (SPSS, Inc., Chicago, IL, USA) was used to carry out all statistical analyses.
Results
With the exception of educational level, no statistically significant differences were observed between the main characteristics of participants included in the validation study and the remaining participants of the population-based survey (Table 3). The DQI, mMDS and ANTOX-S were normally distributed.
P25, 25th percentile; P75, 75th percentile; MET, metabolic equivalent task.
* Categorical variables are presented as relative frequency (95 % CI); continuous variables are presented as mean or median (sd or P25–P75).
† BMI ≥30·0 kg/m2.
‡ Ratio of energy intake (reported on a validated full-length FFQ) to BMR of <1·2.
The sDQS significantly overestimated the DQI rating, whereas the opposite finding was observed for the bMDSC, which underestimated the mMDS score (Table 4). Mean difference of the ANTOX-S was close to zero. The test methods’ estimates for DQI and mMDS were 11 % higher and 11 % lower than those of the 24 h recall reference method, respectively (Table 4). The range of LOA was highest for the ANTOX-S and lowest for the mMDS. No significant proportional variation of the agreement between the test and reference method was observed across ratings of the dietary indices (Table 4, Fig. 1).
DQI, Dietary Quality Index; ANTOX-S, Antioxidant Score; mMDS, modified Mediterranean Diet Score.
One hundred and two participants recruited from a population-based survey in Spain were administered both short questionnaires and completed at least ten interviewer-administered 24 h recalls over a 12-month period.
*Calculated as: screener – 24 h recall.
†Calculated as: (screener/24 h recall) × 100.
‡95 % limits of agreement indicating lower and upper limits of agreement.
§Regression coefficient (β) between mean (dependent variables) and mean differences (independent variables) of the dietary indices obtained by the test and the reference method.
∥Intra-class correlation coefficient.
¶Pearson correlation coefficient.
The ICC between scores obtained by the screeners and the corresponding scores retrieved by the reference method was highest for the ANTOX-S followed by the DQI and mMDS.
Furthermore, Table 4 shows the Pearson correlation coefficients between methods, indicating the capacity of the bMDSC and the sDQS to rank subjects in accordance with their DQI, mMDS and ANTOX-S ratings. Additionally, gross misclassification models were fitted. Pearson correlation coefficients between scores (DQI, mMDS and ANTOX-S) retrieved from both screeners (sDQI and bMDSC) and the corresponding scores obtained from the reference method (multiple 24 h recalls) were calculated. All three dietary scores obtained from both short screeners were significantly correlated with the corresponding scores obtained using the reference method. The correlation coefficient was highest and gross misclassification was lowest for the DQI derived from the sDQS; misclassification was somewhat higher for mMDS and ANTOX-S ratings.
Table 5 shows the construct validity of the DQI, mMDS and ANTOX-S. As expected, a direct association existed between dietary fibre, vitamin C, vitamin E, Mg and K and the tertiles of all three dietary scores. The intakes of folic acid and flavonoids increased across tertile distributions of the DQI and ANTOX-S. In contrast, trans fatty acids and the ratio of saturated fat to unsaturated fat decreased with higher ratings for the DQI.
DQI, Dietary Quality Index; mMDS, modified Mediterranean Diet Score; ANTOX-S, Antioxidant Score.
One hundred and two participants recruited from a population-based survey in Spain were administered both short questionnaires and completed at least ten interviewer-administered 24 h recalls over a 12-month period.
Discussion
The three food-based indices derived from the sDQS and the bMDSC reasonably ranked populations into similar score levels derived by 24 h recalls. Furthermore, the three dietary indices were positively associated with a beneficial nutrient intake profile.
Following a healthy diet is paramount for physical and mental health(1, Reference Féart, Samieri and Barberger-Gateau20–Reference Schroder22). The prevention and treatment of non-communicable diseases such as diabetes, obesity and CVD is strongly influenced through diet(23), and therefore identification of individuals at nutritional risk is important to public health policy and initiatives. However, lengthy comprehensive dietary assessment is a time-consuming process that becomes a real challenge in multidisciplinary epidemiological research and primary-care settings. The sDQS and bMDSC were created to rapidly capture diet quality based on food intake. The DQI, mMDS and ANTOX-S dietary indices derived from these questionnaires showed moderate to good correlations with the corresponding indices obtained by 24 h recalls. The observed range of Pearson correlation (0·40–0·61) and the average level of gross misclassification (7·7 %) are comparable to those reported for food and nutrient intakes derived from short diet screeners and full-length FFQ(Reference Schroder, Covas and Marrugat24–Reference Fernández-Ballart, Piñol and Zazpe28). Although a slightly higher correlation has been reported between the Diet Quality Index-Revised (DQI-R) derived from a full-length FFQ and two 1-week dietary records(Reference Newby, Hu and Rimm29), our results suggest that the sDQS and bMDSC adequately rank subjects with respect to the dietary indices’ ratings.
However, reasonable relative agreement between methods does not necessarily imply good absolute agreement. To address this issue we plotted mean differences between the dietary indices derived from the test and reference methods against the corresponding mean of both methods and calculated the LOA. The sDQS and the bMDSC systematically overestimated and underestimated the DQI and mMDS ratings, respectively. However, no significant proportional bias was observed for all three dietary indices. Furthermore, the widest range of LOA between methods was found for the ANTOX-S, meaning that 95 % of all bMDSC estimates were between 59 % (underestimating by 41 %) and 144 % (overestimating by 44 %) of their reference method estimates. These results indicate a reasonable absolute agreement between the dietary indices derived from the sDQS and the bMDSC and those of the reference method.
In addition to estimating the relative validity of both short dietary screeners studied, we sought to analyse their construct validity, i.e. the degree to which these dietary quality assessment tools measure the theoretical construct (diet quality) they intend to assess. For this purpose, we hypothesized that higher ratings on the dietary indices should be positively correlated with a healthy nutrient intake profile (i.e. higher intakes of vitamin C, vitamin E, dietary fibre, etc.) In most cases, the sDQS and bMDSC dietary indices correlated as anticipated with the average nutrient intakes derived from multiple 24 h recalls. A healthier nutrient intake profile was related to higher ratings of the DQI, mMDS and ANTOX-S, indicating a reasonable construct validity of the short dietary screeners. Construct validity was somewhat stronger for the sDQS-derived DQI compared with the mMDS and ANTOX-S obtained from the bMDSC. The different food composition of both screeners might particularly explain this finding.
A limitation of the present study is the somewhat higher educational level of participants who completed the validation study.
We conclude that the sDQI and bMDSC accurately rate subjects with respect to the dietary indices derived from these screeners without significant proportional variations over the range of average ratings for the dietary indices. Additionally, the LOA variations are within a reasonable range. Furthermore, both screeners show reasonable construct validity, as indicated by the correlations between the dietary indices derived from the sDQS and bMDSC and nutrient intakes reported on the 24 h recalls. Hence, the sDQS and the bMDSC are valid dietary assessment tools for rapid estimation of dietary quality.
Acknowledgements
This research was supported by a grant 2FD097-0297-CO2-01 from Fondo Europeo de Desarrollo Regional (FEDER) and by parts of grants from Spain's Ministerio de Sanidad y Consumo, Instituto de Salud Carlos III FEDER (PI080439), Red HERACLES RD06/0009, and by a joint contract of the Instituto de Salud Carlos III and the Health Department of the Catalan Government (Generalitat de Catalunya), CP 03/00115. The CIBEROBN is an initiative of the Instituto de Salud Carlos III, Madrid, Spain. The authors declare no conflict of interest. H.S. led data analysis and writing of the manuscript. J.M. and A.B.A. participated in the discussion and interpretation of results, and writing of the manuscript. J.M.B.-D., C.S. and M.-I.C. provided expertise in data analysis and in interpretation and discussion of results. They made substantial suggestions on the manuscript. All authors read and approved the final manuscript. The authors appreciate the English revision made by Elaine Lilly, PhD (Writers First Aid).