Using PCA we have found that prudent diet scores calculated using the 100-item SWS FFQ are correlated with red blood cell folate status. A 20-item prudent diet score, based on the 20 most influential foods for this pattern, was highly correlated with the full 100-item score and was similarly correlated with red blood cell folate. Furthermore, amongst a subset of women (Borland et al, 2008
), the change in prudent diet score over two years was correlated with change in red cell folate for both the 20-item and 100-item scores. A 20-item FFQ can capture very similar information about the prudent diet score, but has clear advantages of being simpler to administer and requiring fewer resources.
The SWS had a good response rate (75%) and participants have been shown to be broadly representative of young women in England and Wales, although those from ethnic minorities are somewhat under-represented (Inskip et al, 2006
). The FFQ was interviewer-administered meaning that there was little missing information, a particular advantage for principal component analyses where complete dietary data is required. There is concern that FFQs may be subject to bias (Byers, 2004
). However, in the context of dietary patterns analysis, Hu et al. showed that an FFQ revealed similar patterns of diet as weighed diet records and that individuals’ scores on both were strongly positively correlated (Hu et al, 1999
). In a Southampton cohort we have also shown that prudent diet scores calculated from FFQ and diary data are highly correlated (Crozier et al, 2008
A reduced-item score is able to account for a large proportion of the variability in diet because the food consumption frequencies are correlated. In the SWS, for example, mushroom consumption, which is not included in the 20-item score, is correlated with pepper consumption (rS
=0.31), which is included. Byers et al. suggest that between 15 and 20 items may be all that is required for assessment of a single nutrient for epidemiological purposes (Byers et al, 1985
Principal component analysis has previously been performed on 49 foods and food groups formed by grouping the 100 foods in the SWS data (Robinson et al, 2004
; Crozier et al, 2006
). The 100-item and 49-item prudent diet scores are strongly correlated (r=0.97) (Crozier et al, 2006
). Since we aimed to produce a simple short FFQ, we based our investigations on the 100-item prudent diet score.
We have demonstrated how using the most influential foods from a 100-item prudent diet score in the SWS we were able to generate a 20-item score with necessarily reduced information, but able to capture a large amount of the variability in the 100-item prudent diet score, with which it was highly correlated (r=0.94) and had strong agreement (Bland-Altman 95% limits of agreement = 0.0 (−0.7, 0.7) SDs). The correlation of our 20-item score with the full score compares well with that found by Schulze et al. (r>0.95) (Schulze et al, 2003
), although these results are not directly comparable because different numbers of foods were chosen for the reduced-item score. In contrast to Mishra et al. we used the standardised food frequencies, rather than binary intake data (Mishra et al, 2006
). When using standardised food frequencies it is important to standardise the foods at a second time point or in an alternative study using the mean and standard deviation from the initial foods (as shown in ), because otherwise it is not possible to assess change or differences (if foods are standardised to an internal mean of zero there is no change or difference by definition).
The SWS 20-item prudent diet score had a correlation with red cell folate measurement very similar to that for the 100-item prudent diet score (r=0.25 compared to r=0.28), indicating that the reduced-item prudent diet score has moderate associations with a biomarker that reflects variation in intake of fruit and vegetables, wholemeal bread and breakfast cereals. Previous analyses (Borland et al, 2008
) have demonstrated that the initial and repeat prudent diet scores are strongly associated (rS
=0.81), and showed a slight increase in score over a two-year period (mean increase = 0.13 SDs). Change in red cell folate intake between these two time points is reflected by change in the 20-item prudent diet score (rS
=0.31), a very similar association as when using the 100-item prudent diet score (rS
A particular strength of this work has been the opportunity to create a short FFQ and to use this amongst a cohort of young women attending SureStart Children’s Centres in Southampton: the Nutrition and Well-being Study. Since limited time was available in each NWS interview we were keen to develop a short FFQ with which to assess diet. Women in the NWS had the same average age as those in the SWS (28 years), and both studies included women with a wide range of educational achievements. The scores in the NWS showed the same variation as those in the SWS with the same average score. Furthermore, the 20-item prudent diet score within the NWS had a similar correlation with educational qualifications as the 100-item prudent diet score in the SWS (r=0.41 compared to r=0.47), indicating a consistent association with an important predictor of dietary quality (Robinson et al, 2004
The prudent diet pattern has been found to describe a robust axis of variation in a range of studies (Kant, 2004
) and in a variety of analyses within the SWS (Crozier et al, 2006
). Amongst young women in Southampton a 20-item prudent diet score is strongly associated with the initial 100-item prudent diet score, and with red blood cell folate measures. There is evidence from the Nutrition and Well-being Study that a 20-item FFQ based on this score might be a helpful tool for use amongst young women in Southampton where time available for ascertainment of diet is limited. However, it is unlikely that it would be appropriate for researchers in other settings to use a 20-item FFQ based on the foods in . Differences in food consumption patterns amongst men, participants of different ages and ethnicity, or those from different geographical areas mean that the 20 foods in may not correlate as well with a full prudent diet score. In order to develop a short FFQ to assess a prudent diet score the researcher should ideally apply the techniques described in this paper to an existing dataset in order to generate a population-specific short FFQ.
The 20-item FFQ we have developed has clear advantages for use in large surveys in terms of the time and resources required for completion and analysis. Our data from young women in Southampton show that this short FFQ can be used to provide useful information about variation in their compliance with the prudent dietary pattern.