Comparison of a Food Frequency Questionnaire with a 10-Day Weighed Record in Cigarette Smokers

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1 International Journal of Epidemiology International Epidemiological Association 1993 Vol. 22, No. 5 Printed in Great Britain Comparison of a Food Frequency Questionnaire with a 10-Day Weighed Record in Cigarette Smokers RACHEL L THOMPSON AND BARRIE M MARGETTS Thompson R L (Institute of Human Nutrition, University of Southampton, Southampton SO9 3TU, UK) and Margetts B M. Comparison of a food frequency questionnaire with a 10-day weighed record in cigarette smokers. International Journal of Epidemiology 1993; 22: The aim of the study was to compare nutrient intakes estimated by a self-administered food frequency questionnaire and a 10-day weighed record in 122 men and 179 women cigarette smokers aged years. Comparison of nutrient intake by means, per cent mean differences and ability to rank individuals correctly between the methods showed good agreement for most nutrients. Spearman rank correlations were statistically significant for all nutrients except vitamin A intake in men; adjusting for energy intake increased the strength of the associations found. Bland-Altman plots showed differences in agreement over the range of intakes for energy in men and ascorbic acid in women. Food frequency questionnaires may be used to assess the dietary habits of smokers, but some caution is required and the method should be assessed in the study sample before being applied to the whole sample. Food frequency questionnaires (FFQ) are often the preferred method in epidemiological studies as they are simple, easy to administer and process, and require minimal effort from the subjects themselves. 1 As a result FFQ can be administered to a large number of subjects, whereas a recording method such as the weighed record (WR) may only be completed by a subsample of the population. Before use an FFQ should be validated in a group of subjects representative of the study population. As there is no perfect measure of diet the relative validity of an FFQ is often compared with another dietary survey method such as WR. The WR is chosen as errors associated with this method are independent of the errors associated with the FFQ and therefore validity is unlikely to be overestimated and may in fact be underestimated. 2 Validation studies are usually carried out in selected groups of subjects, often volunteers, who may differ in gender, age, social class, lifestyle characteristics and region of residence from the study population. It is therefore unclear whether the results of such studies are equally valid in a wider study sample. There is now Institute of Human Nutrition, University of Southampton, Southampton SO9 3TU, UK. Reprint requests to: DrBM Margetts. substantial evidence that the dietary habits of smokers differ from those of non-smokers. However, to date there have been no studies published validating an FFQ in a group of smokers, although Colditz et al. 3 found that the reproducibility of an FFQ was not affected by smoking status. It is possible that the observed differences in diet may arise at least partially from differential bias in the measurement of diet between smokers and non-smokers. This paper reports the comparison of nutrient intakes from an FFQ and a 10-day WR in men and women cigarette smokers. SUBJECTS AND METHODS Subjects Subjects were recruited between January 1990 and June 1991 as part of a study looking at the effect of giving up smoking on dietary habits. The sample consisted of 275 randomly selected cigarette smokers aged years from general practices in Southampton. Subjects were invited to attend the Preventive Cardiology clinic at the Royal South Hants Hospital in Southampton; 168 (61) attended and of these 117 (49 men and 68 women) satisfactorily completed a WR. A second sample of 263 men and women cigarette smokers in the same age group was recruited by means 824

2 NUTRIENT INTAKES IN SMOKERS 825 of advertisements in local newspapers; 207 (79) attended and 184 (73 men and 111 women) completed a WR. Methods Reported smoking habit was confirmed by breath carbon monoxide measurement. Social class was classified by longest occupation coded from classification of occupations of the UK Office of Populations, Censuses and Survey. 4 Non-Manual occupations were grouped as I, II, IIINM and manual occupations as HIM, IV, V. Married women were classified by their husband's occupation and single women by their own occupation. Height and weight were measured in indoor clothing with jacket and shoes removed. An FFQ validated in the Welsh population 5 ' 6 was used unchanged except for the inclusion of linoleic acid to the nutrient database. The FFQ contained a list of 84 foods or food groups and subjects were required to state how often they usually ate each item. Estimates of the quantity consumed were obtained for some items: e.g. number and size of slices of bread per day; the amount of milk per day; number of eggs per week and number of fresh fruits per week; and amounts of butter, margarine, cheese and cream per week. For other foods a mean portion size, calculated from mean values of intakes from 7-day WR from South Wales, was used to derive amounts of foods eaten. On attending the clinic subjects were given both verbal and written instructions on how to fill in the selfadministered FFQ. It was then checked for completeness and ambiguities. Subjects were then instructed on how to weigh and record all items of food and drink consumed over 10 days (7 weekdays and 3 weekend days). Subjects were provided with digital scales (Soehnle 8000) and food recording and instruction booklets. Items consumed outside the home were recorded in household measures. Subjects returned to the clinic approximately 2 weeks later when the record was checked. Analysis of Dietary Data The data were converted to nutrient intake using commercially available software packages (DietQ version 2, Tinuviel for FFQ and Comp-eat version 4 for WR). Each computer software package used a separate but similar nutrient database developed from food composition tables. 7 ' 8 The databases used to calculate nutrient intakes were compared for the FFQ and WR. A number of discrepancies were found between the two databases and as a result the FFQ database was updated and made consistent with Comp-eat version 4 (used to calculate intakes from the WR). For the analysis of food groups, foods from the WR were grouped as shown in the FFQ. Statistical Analyses Sample means and 95 confidence intervals (CI) of mean daily nutrient intakes were computed. nutrient differences between the methods were calculated from FFQ - WR along with 95 CI. The ability of the FFQ to correctly rank individuals was assessed by the Spearman rank correlation coefficient, both energy-unadjusted and energy-adjusted values were calculated. The adjustment for energy was done using the approach outlined by Willett. 2 Agreement between the methods for energy, ascorbic acid and fibre was also examined by the Bland-Altman technique in which the difference in nutrient value between dietary methods was plotted against their mean for each subject. 9 Nutrient intakes were log transformed to approximate normal distribution. Contribution of food groups to ascorbic acid intake was examined by gram and percentage contributions. RESULTS Table 1 shows the main characteristics for men and women by recruitment method. There were no statistically significant differences for age or body mass index between recruitment groups. However, volunteers reported smoking more cigarettes per day than the random sample. In men, the reported number of cigarettes smoked per day was 19.4 for the random sample and 24.3 for the volunteers. In women, the number of cigarettes smoked was 15.6 and 22.0 for the random sample and volunteers respectively. There was also a difference in the social class distribution between recruitment groups. For men 57 of the random sample and 44 of the volunteers had manual occupations and 37 of the random sample and 49 of the volunteers had non-manual occupations. In women, 53 of the random sample and 39 of the volunteers were classified into manual occupations and 38 and 51 respectively into non-manual occupations. Table 2a shows the comparison of mean daily nutrient intakes between FFQ and WR for men. The FFQ tended to give lower estimates for energy and most macronutrients except sugar than WR. The per cent mean differences between the methods, however, were almost zero for protein and carbohydrate and in the range of-4 to -7 for energy, saturated fat, starch and alcohol and 6 for sugar. Largest per cent mean differences were seen for fat, polyunsaturated fat, linoleic acid and fibre but did not exceed 11. For micronutrients the FFQ tended to overestimate intakes

3 826 INTERNATIONAL JOURNAL OF EPIDEMIOLOGY TABLE 1 Subject characteristics; mean values (95 confidence intervals) Men Women Source Random Volunteer Random Volunteer No. Age (years) Body mass index (kg/m 2 ) Number of cigarettes/day Occupation 3 manual/ non-manual 49 5 (48.5,51.9) 25.2 (24.3,26.1) 19.4 (16.8,22.0) (48.2,50.5) 26.0 (25.2,26.7) 24.3* (22.3,26.4) (49.3,52.4) 25.5 (24.3,26.7) 15.6 (13.9,17.3) (48.3,50.4) 24.5 (23.8,25.2) 22.0* (20.3,23.6) 57/37 44/49 53/38 39/51 P < a Numbers do not add up to 100 as some subjects could not be classified e.g. worked in armed forces; housewife. TABLE 2 Comparison of mean daily nutrient intake by the food frequency questionnaire (FFQ) and 10-day weighed record (WR) with 95 confidence intervals (Cl) a) Men (n = 122) Energy (MJ) Protein Fat Polyunsaturated fat Linoleic acid Saturated fat Carbohydrate Starch Sugar Fibre Alcohol Vitamin A (ug) Vitamin C (mg) Vitamin E (mg) Calcium (mg) WR 10.1 (9.8,10.5) 84.3 (82.1,87.3) 98.8 (94.9,102.6) 16.2 (15.2,17.2) 11.8 (10.9,12.8) 39.6 (37.8,41.3) (264.3,29) (139.9,153.9) (120.8,139.9) 19.1 (18.0,2) 21.0 (16.3,25.6) 1180 (1004,1356) 57.8 (51.8,63.7) 6.6 (6.1,7.0) 966 (918,1014) FFQ 9.7 (9.2,1) 84.1 (80.3,87.9) 87.7 (82.3,93.0) 14.4 (13.0,15.8) 10.4 (9.1,11.7) 37.5 (35.0,40.0) (260.6,291.3) (130.7,145.7) (126.2,149.4) 21.1 (19.9,22.3) 19.6 (15.4,23.7) 1639 (1400,1878) 61.9 (57.1,66.8) 5.4 (4.9,5.8) 1032 (983,1080) -0.4 (-0.8,0.0) (-4.1,3.9) (-16.6,-5.6) -1.8 (-3.0,-0.6) -1.4 (-2.4,-0.4) -2.0 (-4.4,0.4) -1.3 (-15.0,12.4) -8.7 (-16.1,-1.3) 7.4 (16.0,-1.2) 2.0 (0.8,3.2) -1.4 (-3.9,1.1) 458 (170,746) 4.2 (-1.5,9.9) -1.2 (-1.8,-0.6) 65 (16,114)

4 NUTRIENT INTAKES IN SMOKERS 827 TABLE 2 (cont.) WR (95 Cl) FFQ (95 Cl) Iron (mg) Folate (ug) 13.1 (12.2,13.9) 252 (238,265) 12.3 (11.3,13.3) 289 (272,305) -0.8 (-1.8,) 37 (23,51) b) Women (n = 179) Energy (MJ) Protein Fat Polyunsaturated fat Linoleic acid Saturated fat Carbohydrate Starch Sugar Fibre Alcohol Vitamin A (ug) Vitamin C (mg) Vitamin E (mg) Calcium (mg) Iron (mg) Folate (ug) 7.0 (6.8,7.3) 63.9 (61.6,66.1) 72.8 (69.5,76.1) 11.3 (10.7,11.9) 7.9 (7.3,8.5) 30.1 (28.5,31.7) (183.5,199.5) (99.5,107.7) 87.9 (81.6,94.2) 16.0 (15.1,16.8) 6.1 (4.8,7.5) 1081 (942,1219) 54.9 (50.0,59.8) 4.9 (4.6,5.2) 772 (728,815) 1 (9.6,10.7) 190 (181,200) 7.2 (7.0,7.5) 74.6 (71.9,77.4) 68.1 (64.7,71.6) 11.1 (10.4,11.9) 8.0 (7.2,8.7) 29.6 (27.8,31.5) (193.6,212.7) (99.0,109.6) 98.8 (92.1,140.5) 20.4 (19.3,21.5) 5.9 (4.4,7.3) 1734 (1517,1952) 68.3 (63.8,72.9) 4.7 (4.5,5.0) 895 (860,929) 11.9 (11.1,12.7) 239 (229,249) (,0.6) 10.8 (7.9,13.7) ^4.7 (-8.4,-1.0) (-1.0,0.6) 0.1 (-0.5,0.7) -0.5 (-2.1,1.1) 11.6 (2.8,20.4) 0.7 (^4.4,5.8) 10.9 (5.2,16.5) 4.4 (3.4,5.4) -0.3 (-1.3,0.7) 654 (419,889) 13.5 (8.8,18.2) (-0.6,) 123 (84,162) 1.8 (1.0,2.6) 49 (39,59) a MD, mean difference (FFQ-WR). b MD, ( FFQ-mean WR)/mean WR. compared with the WR with the exception of vitamin E and folate. Agreement was within 10 for ascorbic acid, calcium and iron but larger for vitamin E (-18), folate (15) and vitamin A (39). Table 2b shows the same results for women. In contrast to men, the FFQ gave higher estimates for energy and macronutrients except for fats and alcohol than the WR. The per cent mean differences were close to zero for starch, linoleic acid, polyunsaturated fats and saturated fat and in addition less than 10 for energy, fai, carbohydrate and alcohol. The largest discrepancies in per cent mean difference were seen for sugar, protein and fibre. As in men micronutrient intakes were higher by FFQ than WR except for vitamin E (-4). The remainder of the micronutrients were overestimated by greater than 10 and ranged between for calcium, iron, folate, ascorbic acid and vitamin A. For both men and women, in

5 828 INTERNATIONAL JOURNAL OF EPIDEMIOLOGY general differences for micronutrients were larger than those for macronutrients. Table 3 shows mean difference and per cent mean difference for the random and volunteer samples for selected nutrients. In men mean differences tended to be closer to zero for the volunteer sample than the random sample except for sugar, fibre and calcium. Largest discrepancies were seen for alcohol and ascorbic acid with the random sample underestimating their alcohol consumption and overestimating their ascorbic acid intake by FFQ compared with WR. For nutrients not shown, type of fats, starch, vitamins A and E, iron and folate there were no significant differences, and in general differences were nearer to zero for the volunteer sample. In women estimates of energy intakes were the same for the random sample but for the volunteer sample the measurement was larger for FFQ than WR. For the other nutrients with the exception of fat and types of fat (not shown) and alcohol, differences were closer to zero for the random sample than the volunteer sample. In general this also followed for the remainder of the nutrients not shown. None of the differences reached the nominal level of TABLE 3 Comparison of nutrient intake by randomly recruited subjects and volunteers Source Energy (MJ) Protein Fat Carbohydrate Sugar Fibre Alcohol Vitamin C c (mg) Calcium (mg) Random (95 Cl) -O.8 (-1.6,0) -2.5 (-8.6,3.6) (-23.3,-5.3) (-35.9,10.3) 0.7 (-13.8,15.2) 1.8 (0.0,3.6) -4.2 (-7.7,-0.7) 11.3 (3.9,18.7) 7 (-73,87) Men Volunteer -0.1 (-0.7,0.5) 1.4 (-3.9,6.7) -8.9 (-15.8,-2.0) 6.4 (-10.5,23.3) 12.0 (1.2,22.8) 2.1 (0.5,3.7) 0.5 (-3.0,4.0) -O.6 (-8.4,7.2) 105 (43,166) statistical significance {P < 0.05) after log transformation except for ascorbic acid in men. Agreement was also looked at by per cent of subjects that were grossly misclassified into the opposite fifth of consumption by FFQ compared with WR. Overall in men the per cent grossly misclassified was less than 6 except for energy and vitamin A and overall in women it was less than 6 for all nutrients except for vitamin A. After adjusting for energy the overall per cent grossly misclassified remained at 2 for both men and women. There were no overall differences by source of recruitment for men or women. Table 4 shows Spearman rank correlation coefficients both unadjusted and adjusted for energy. Rank correlation coefficients were statistically significant for all nutrients except vitamin A in men. They ranged from 0.18 to 0.83 with a mean of 0.49 in men and from 0.31 to 0.81 with a mean of 0.49 in women. Energyadjusted values were higher except for sugar, vitamin A and alcohol in men and alcohol, vitamin C and calcium in women. Table 5 shows the contribution of different food groups to ascorbic acid estimates by FFQ and WR. For Random 0.0 (-0.4,0.4) 8.5 (4.0,13.0) -7.1 (-13.2,-1.0) 4.6 (7.4,22.8) 9.1 (-1.3,19.5) 4.0 (2.6,5.4) -0.9 (-1.9,0.1) 12.8 (4.4,21.2) 78 (4,152) Women Volunteer 0.4 (0.0,0.8) 12.1 (8.4,15.8) -3.3 (-8.0,1.4) 15.9 (5.3,26.5) 12.0 (5.3,18.7) 4.7 (3.5,5.9) (-1.2,1.6) 13.9 (8.6,19.2) 151 (105,197) a b MD, difference (FFQ-WR). MD ( FFQ-mean WR)/mean WR. c P = 0.05 for etween random and volunteer men (log transformed data).

6 NUTRIENT INTAKES IN SMOKERS 829 TABLE 4 Spearman rank correlation coefficients 0 unadjusted (r) and adjusted for energy (r-adjusted) between the food frequency questionnaire and weighed records Energy (MJ) Protein Fat Polyunsaturated fat Linoleic acid Saturated fat Carbohydrate Starch Sugar Fibre Alcohol Vitamin A (ug) Vitamin C (mg) Vitamin E (mg) Calcium (mg) Iron (mg) Folate (ng) b Men r-adjusted b Women r-adjusted a Two-tailed tests for significance P < 0.001, except for significant. TABLE 5 (WR) Source Method Vegetables 8 Fruit juice b both men and women FFQ gave a higher estimate for ascorbic acid intake from vegetables than WR in both absolute and relative amounts. Also, in both men and women estimates of fruit juice consumption were similar by both methods for the random sample but for volunteers estimates of fruit juice from the WR were twice that of the FFQ. There were no differences by source in the agreement between the methods for potatoes and milk. Figure 1 shows Bland-Altman plots 9 for energy, ascorbic acid and fibre intakes. Limits of agreement ( ± 2SD) are shown on the plots along with the mean values. In men the Bland-Altman plot for energy shows that at low intakes the FFQ gives a lower estimate for energy but at higher intakes it gives a higher estimate than the WR. For fibre and ascorbic acid there appeared to be a constant bias with the FFQ on average giving a higher estimate across the whole range than the WR. In addition for ascorbic acid the scatter of the difference was wide especially at the lower end of intake. In women there was a constant bias for energy and fibre with the FFQ giving higher estimates than the WR. However, for ascorbic acid there was a differential bias with higher estimates by the FFQ at low intakes and lower estimates at higher intakes compared with WR. Also, the scatter of dif- Contribution (g/) of different food groups to vitamin C estimates by the food frequency questionnaire (FFQ) and weighed records Random WR FFQ (32) (35) (15) (13) Men Volunteer WR FFQ g () g () (25) (31) 14.3 (23) 6.1 (10) Random WR FFQ (30) (36) 9.5 (18) 11.0 (16) Women Volunteer WR FFQ (32) (36) 10.1 (18) 7.2 (10) Potatoes (22) (17) 10.9 (18) 12.5 (20) 8.3 (15) (13) 8.0 (14) 9.0 (13) Fruit (18) (25) 15.8 (26) 15.7 (26) 12.1 (22) 16.3 (24) 12.3 (22) 21.8 (32) Milk 3.4 (7) 4.0 (6) 3.2 (5) 4.0 (7) 3.3 (6) 3.8 (6) 3.0 (5) 3.9 (6) a All vegetables except potatoes. b Including Ribena. c All types including crisps.

7 830 INTERNATIONAL JOURNAL OF EPIDEMIOLOGY MEN Ascorbic acid WOMEN Ascorbic acid Difference In log (FFQ - WR) //: <:?: SD Average log ascorbic acid by FFQ and WR Fibre Difference In log (FFO - WR) SD ' "! : ' ' Average log fibre by FFQ and WR Energy Difference In log (FFQ - WR) + 2SD * '.. Difference In log (FFO - WR) SD - 2SD Average log ascorbic acid by FFQ and WR Difference In log (FFQ - WR) Fibre r.. '. ' i " V: :. < : :V : SD - 2SD Average log fibre by FFQ and WR Difference In log (FFQ Energy WR) + 2SD :.. ' *... i.. " * ' ', '... : '.' ' '. ' - 2SD Average log energy by FFQ and WR ' " : Average log energy by FFQ and WR : - 2SD FIGURE 1 Difference in log (FFQ-WR) against log by FFQ and WRfor energy, fibre and ascorbic acid for men and women

8 NUTRIENT INTAKES IN SMOKERS 831 ference tended to decrease with intake showing a closer agreement at higher intakes. In particular at low intakes several subjects were outside the limits of agreement. DISCUSSION The results of this study show good agreement between estimates of nutrient intake derived from an FFQ and a WR for men and women. Spearman rank correlations were statistically significant for all nutrients for men and women, except for vitamin A in men. Adjusting for energy intake increases the strength of the association measured; adjusted r values ranged from 0.18 (for vitamin A in men) to 0.77 for alcohol in women. However, closer analysis of the differences between the methods for estimates of energy, fibre and ascorbic acid using Bland-Altman plots revealed that agreement between the methods was not consistent across the range of intake for energy in men and ascorbic acid in women. Food frequency questionnaires tend to measure average or usual diet and therefore to make the comparison valid the WR should also measure usual diet. Usual diet cannot be reliably assessed using a 1-day diet record; for an appropriate comparison several days are required. We used a 10-day record for comparison as, although a 7-day WR is sufficient to correctly rank subjects for energy, protein, fa 1, carbohydrate and saturated fats, a 10-day record is required for ranking fibre and iron intakes. l0 However, days may be required for polyunsaturated fats. Although the WR was not kept for the required number of days to assess polyunsaturated fat intake correctly (15-30 days) the agreement between the methods was in fact no worse for polyunsaturated fats than that for total fat in men and women. We found that the two nutrient databases for the FFQ and WR were not exactly the same because they were based on different editions of food composition tables. 78 We updated the FFQ database so that it was comparable to that used for the WR. When we looked at the derivation of ascorbic acid from the FFQ it showed that there was a composite group of green vegetables and salad for which the nutrient intake was calculated from three vegetables; cabbage, runner beans and sprouts, each contributing one-third of ascorbic acid intake in this group. The ascorbic acid content of sprouts (60 mg) is high. From the WR it was apparent that sprouts only contributed about (not 33 as used in the estimate of intake for the FFQ) of green vegetable and salad intake and it was therefore likely that the ascorbic acid intake from the FFQ was overestimated. If ascorbic acid intake was recalculated with a lower composite ascorbic acid content for the vegetable group (based on vegetables eaten) of 20 mg and not 30 mg; the contribution to ascorbic acid intake from vegetables would be reduced by 5-7 mg, increasing the agreement between the methods. With regard to the ascorbic acid contributed by fruit juices if the WR was the method of choice volunteers could be seen to consume more ascorbic acid from fruit juice than random recruits but if the FFQ was the method of choice the random recruits would consume more. Several studies have been published on randomly recruited subjects comparing an FFQ with a 7-day WR. In agreement with our results other workers 6 '"" 13 have found higher intakes in men of energy estimated by the WR compared with the FFQ. In women in our study the FFQ and WR gave the same energy estimate for the random sample but the FFQ gave a higher energy estimate for the volunteers. Posner et al. n also found the FFQ estimate of energy higher than the WR but others did not We showed a large underestimation of fat intake for randomly recruited subjects by FFQ compared with the WR. Some studies" 1 ' 2 ' 14 showed discrepancies of-9.5 to -33 g in fat estimates between the methods, but this was not seen by others. 6 ' 13 Fibre and ascorbic acid intakes in our smokers appeared to be overestimated by the FFQ compared with the WR with the exception of ascorbic acid intake in men volunteers. However, numbers misclassified into the opposite quintile were low. This overestimation was also shown by Pietinen et al.'' for ascorbic acid and Tj0nneland et al. ' 2 and Willett et al. 14 for ascorbic acid and fibre. Smokers in our study compare well with subjects in other validation studies. However, in comparison with the same questionnaire used in the Welsh population 6 the smokers performed less well for fat and ascorbic acid. This may be because the questionnaire was originally designed to be used in South Wales and portion sizes were calculated from WR in this population and hence agreement in another population is likely to be less. Agreement between the FFQ and WR may also depend on the sequence of administration. The two methods should be administered in such a way as to ensure that they cover the same period of time, but that one does not influence the other. Ideally the FFQ should be administered before the WR to avoid the possibility that the WR will influence the estimate of usual intake derived from the FFQ. 15 In the present study we administered the FFQ before the WR. Studies in which the FFQ has been completed after the WR show apparently closer agreement than if the

9 832 INTERNATIONAL JOURNAL OF EPIDEMIOLOGY order is reversed, but this agreement is likely to be due to the influence of the WR on the recall of usual intake. 15 The Bland-Altman technique 9 has not been widely used in validation studies; correlation coefficients are used more often but these tend to look at the association between the methods and not the agreement. An added advantage of the Bland-Altman method is that agreement can be assessed across the range of intakes and as many epidemiological studies seek to compare risk across a range of intakes in different groups of subjects this type of comparison is most useful. If there is differential misclassification of intake the estimate of effect will be wrong. Getting the absolute levels of intake correct is of lesser importance provided the ranking across the range of intakes for each group in the study is correct; a constant bias as found for some nutrients in the present study may not be important if absolute values are not required. However, the differential error in the estimate of energy in men and ascorbic acid in women using the difference between the FFQ and the WR, compared with the average of the FFQ plus the WR, as revealed by the Bland- Altman analysis, reinforces the need to establish whether there is likely to be any differential bias in the estimates of intakes in the sample under investigation before the method is used. It may be, for example, that differences in energy intake may be exaggerated by the use of the FFQ. Often validation studies are carried out in small groups of well-motivated volunteers. These small groups may differ from the main study sample not only in method of recruitment but also age, occupation group and gender. If volunteers produce a better agreement between dietary methods, then the results of a large study of randomly selected subjects may be misleading. This validation study was carried out on 80 of the subject sample and showed a good agreement for most nutrients. The results showed no major differences by source of recruitment, therefore it may be possible to use volunteer samples for validation studies as long as they are similar in terms of age and gender to the study population. The smokers in this study, although not giving such a good agreement as subjects completing the same questionnaire in Wales, gave a similar agreement to other published studies. Therefore, it is unlikely that any dietary differences found between smokers and non-smokers using the FFQ were a result of differential bias in completing the FFQ by smokers compared with non-smokers. In summary, we have compared the relative validity of an FFQ with a 10-day WR in a large number of cigarette smokers and found no major differences in agreement by the method of selection of subjects. We have shown the usefulness of the Bland-Altman technique, in addition to other conventional methods, in validation studies and investigated the source of the difference for some nutrients. In conclusion it is possible to use the FFQ to compare intakes of groups of subjects including smokers, but caution is required and the method should be assessed in each study sample before being applied. ACKNOWLEDGEMENTS The study was supported by a project grant from the Medical Research Council. We wish to thank Sister E A Scott for her help in the recruitment and screening of participants. REFERENCES 1 Boeing H, Wahrendorf J, Heinemann L et al. Results from a comparative dietary assessment in Europe: 1. Comparison of dietary information from concurrently applied frequency questionnaires and qualitative measurement instruments. Eur JClin Nutr 1989; 43: Willett W C. Nutritional Epidemiology. New York: Oxford University Press, Colditz G A, Willett W C, Stampfer Miet al. The influence of age, relative weight, smoking and alcohol intake on the reproducibility of a dietary questionnaire. Int J Epidemiol 1987; 16: Office of Population Censuses and Surveys. Classification of Occupations. London: HMSO, Yarnell J W G, Fehily A M, Milbank J E, Sweetnam P M, Walker C L. A short dietary questionnaire for use in an epidemiological survey: comparison with weighed dietary records. Hum Nutr: Appl Nutr 1983; 37A: Fehily A M, Butland B K, Holliday R M, Yarnell J W G. Dietary studies in the Caerphilly heart disease survey. Food Sci Nutr 1988; 42F: Paul A A, Southgate DAT. McCance and Widdowson 's The Composition of Foods. 4th edition. 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