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Estimation of salt intake by questionnaire
Appetite, 1985, 6, 219-233
Estimation of Salt Intake by Questionnaire R. SHEPHERD, C. A. FARLEIGH and D. G. LAND A.F.R.C. Food Research Institute, Norwich
A questionnaire designed to assess salt intake was tested. This involved principal components analysis of responses from 155 subjects to find the underlying components related to the questions. Validation of the questionnaire used 7-day urinary sodium excretion for 33 subjects, along with table and cooking salt usage over 7-days. This gave comparatively good prediction for total intake (r = 0'66) and table salt use (r = 0'70) but not for cooking salt use (r = 0,17). Test-retest reliability for the estimate of total intake was r = 0·75. This method would therefore offer a useful estimate of total intake, especially where group means are required rather than accurate estimates of individual intakes.
INTRODUCTION
In recent years there has been a great deal of research on the relationship between high blood pressure and salt intake (Meneely & Battarbee, 1976; Tobian, 1979). In studies of this type it is necessary to estimate the salt, or sodium, intake of individuals or groups. Several different methods may be used, depending on the type of study undertaken and the importance of factors such as required level of accuracy, inconvenience to subjects, or the number of subjects involved. The most popular method of estimating sodium intake is by measuring sodium excretion. Most studies seeking to relate salt intake to high blood pressure have used single 24-h urine collections (e.g. Dawber, Kannel, Kagan, Donabedian, McNamara & Pearson, 1967; Swaye, Gifford & Berrettoni, 1972). Although excretion is a good indicator of intake, it is variable over days within subjects and so, in order to classify subjects accurately, it is necessary to obtain several complete 24..h urine collections (James, Bingham & Cole, 1981; Farleigh, Shepherd & Land, 1985). However, it would be impossible to collect several samples in a large-scale epidemiological study. There have been many attempts at estimating nutrient intake using questionnaires based on the frequency of eating foods (e.g. Marr, 1971; Yarnell, Fehily, Milbank, Sweetnam & Walker, 1983). Such questionnaires on general food consumption do not generally give good estimates for particular nutrients. One method of overcoming this problem is to design questionnaires individually for specific nutrients, and include
The authors would like to thank Dr. M. Nelson of the MRC Epidemiology Unit, Southampton for making available data on weighed intakes from which the estimates of average portion sizes were calculated. We would also like to thank Lynn Stockley for making available data on weighed intakes which were used to validate the food content portion of the questionnaire. Reprint requests should be addressed to Dr. R. Shepherd, A.F.R.C. Food Research Institute, Colney Lane, Norwich NR4 7UA. 0195-6663/85/030219+ 15 $03'00/0
© 1985 Academic Press Inc. (London) Limited
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questions only on those foods which are major contributors to the intake of the particular nutrient. In the case of sodium intake, there is also the problem of salt added to food at the table and in cooking, which cannot be estimated by such frequency of consumption questionnaires. There have been several studies reported using questionnaires designed specifically to assess salt intake. Some have included no external validation of the questionnaire (Dahl & Love, 1954; Dahl & Love, 1957; Pangborn & Pecore, 1982), whilst others report the use of questionnaires where the validation has not been published (Chauncey, Wallace & Alman, 1980). Several studies have involved a single 24-h urine collection to estimate total salt intake, along with the Dahl & Love (1954) classification by table salt use, or a modification of this to include questions on eating salty foods. Whilst Dahl (1957) and Swaye et ale (1972) found groups of subjects to differ in sodium excretion, Dawber et ale (1967) and Beevers, Hawthorne & Padfield (1980) found no difference. Tuomilehto, Karppanen, Tanskanen, Tikkanen & Vuori (1980) did not test for a statistical difference between the groups. There are two problems with these studies. The first is the use of a single 24-h urine collection, which will be a very poor indicator of habitual sodium intake for individuals (James et al., 1981). Secondly, there is the use of urinary sodium, which is a measure of total intake, as a criterion for a classification by table salt use, whereas table salt use is only a small contributor to total intake (Fregly & Fregly, 1983). Questionnaires have been devised which include the frequency of consumption or liking for foods high in salt. This is likely to be a more successful procedure, since a much larger proportion of total intake derives from this source than from table salt use (Fregly & Fregly, 1983). Again, not all of these have been validated (Medeiros & Borgman, 1982). Hankin, Reynolds & Margen (1967), using a 7-day weighed intake, found consumption of a small number of foods predicted salt intake in a group of Japanese-Americans, but this may relate only to the specific diet of this particular ethnic group. A questionnaire based on these foods was constructed (Hankin, Stallones & Messinger, 1968) but a subsequent test of the questionnaire on a subsample of the original subjects showed it to be much poorer at estimating sodium intake, with a correlation of 0·33 (Hankin, Messinger & Stallones, 1970). Hill, Montandon, Scott, Hammond, Tristan & Baer (1980) used. two '24-h urine collections and found no .prediction for sodium excretion from their questionnaire. Faust (1982) found no general relationship (although there was' a correlation for a subgroup of 6 subjects). Pietinen, Tanskanen & Tuomilehto (1982) found significant but very small correlations using a single 24-h urine sample (males r = 0·18, females r = 0·20). Maller, Cardello, Sweeney & Shapiro (1982) described a questionnaire designed specifically to assess table salt use. They measured table salt use at standard meals and found their questionnaire to be a good predictor of usage (for best single question, r = 0·73; for best 2 questions, multiple R = 0·88). However, this was in a controlled setting, rather than in normal life, and the number of subjects was small (N = 12). Although previous questionnaires provide a relatively good estimate of table salt use in a controlled setting, they are not so useful for estimating intake in ordinary life, and particularly so for total salt intake. However, within a health context, interest is usually centred on total salt intake. The aim of the present study was to develop a relatively short questionnaire designed specifically to measure sodium intake and to assess intake from different sources. It was hoped that this would allow reasonably accurate assessment without the inconvenience of collecting urine samples.
SALT INTAKE BY QUESTIONNAIRE
221
METHOD
Design The questionnaire included questions on table salt use, cooking salt use and the frequency of eating foods high in sodium. Other questions were included, mainly on the use of sugar, in order to disguise the purpose of the questionnaire which was entitled "Survey of Food Intake". The questions relating to salt use are shown in Figure 1. The responses to the extra questions were not analyzed. More recent work using modifications of the questionnaire does not show any differences in responses between the questionnaire with these extra questions included or excluded (Shepherd & Farleigh, Note 2). Cooking use was assessed in question 9. The distance along the scale was modified by the frequency of eating foods expected to be salted during cooking (cooked fresh vegetables, boiled potatoes, rice, spaghetti) giving Q9FR. There were two questions relating to the use of table salt (questions 3 and 14). Question 3 on salting food at the table before tasting was found by Maller et ale (1982) to be the best predictor of table salt use from among 12 questions. Their second-best predictor was a question on how often subjects added salt to hamburger, french fries and/or popcorn. This was modified in question 14 where subjects ticked whether they added salt to each of a list of foods, the total giving Q 14. The foods were changed from the original American version because of differences between the two cultures in foods normally salted. The response to each food was modified by how often it is eaten to give Q14FR. Subjects could write in any other foods salted, the number of foods giving Q14EX. One further question was included from the Maller et ale (1982) questionnaire on the importance of salt to the subject's enjoyment offood (question 7), the distance along the scale giving Q7. This is a more general question on attitude rather than actual behaviour, and might be related to the use of salt both at the table and in cooking. Question 15 was on the frequency of eating 24 foods. These were 14 foods high in sodium, the nine foods from question 14, and the extra one being "cooked fresh vegetables". The frequency of eating responses was on a 100 mm graphic scale, as in the earlier questions, but the anchors were labelled "Never", "Monthly", "Weekly", "Daily" and "Six times per day", and were spaced logarithmically along the line ("Never" would correspond to less than once a year). An example for one food is shown in Figure 2. The distance along the scale was then converted to a frequency, making use of the logarithmic nature of the scale. This does not involve the difficulties in quantifying responses on scales with labels such as "often", "frequently", etc., found by Bass, Cascio & O'Connor (1974). The 14 high sodium foods in question 15 are shown in Table 1 (along with milk which was assessed separately in question 1). Portion sizes were not included in the questionnaire, but instead average portion sizes were estimated from data collected by Nelson (Note 1). This involved 7-day semiweighed intakes by 100 men and 111 women, i.e. most of the foods were weighed but standard measures were used for some foods. The portion sizes were calculated separately for males and females. The mean portion size was calculated from every occasion a subject in Nelson's study ate one of the foods which would fall into one of the categories in the present questionnaire. The average sodium content for the questionnaire items were weighted according to how often the subjects in Nelson's study had eaten the individual foods. The calculated average sodium values for the 14 items in
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R. SHEPHERD ET AL. 14 )
Do you usually add salt to the following foods at the table?
Yes
(i)
Chips
(ii)
Boiled eggs
(ii n
Eggs
(iv)
Tomatoes
(v)
Boi led potatoes
(vi)
Baked potatoes
(vii)
Boiled rice
( viii)
Spaghetti or other pasta
( ix)
Porridge
( x)
Other foods -
Not eaten
No
(other than boiled)
please specify
(a)
1)
How much milk do you drink in an average week?
None
3)
2.5 pints
5 pints
7.5 pints
Do you salt food at the table before tasting it?
Never
Always
7)
How important is salt to your enjoyment of food?
Not important
9)
10 pints
Very important
How much salt is added during cooking to the vegetables you eat at home?
Very much
None
(b) FIGURE
1.
Questionnaire items on table and cooking salt use.
223
SALT INTAKE BY QUESTIONNAIRE Breakfast cereals (except Puffed Wheat, Sugar Puffs, Shredded Wheat and Muesli)
Never
Monthly
Weekly
Daily
I
I
I
6 times per day
I
FIGURE 2. Example of form of items in question 15 for assessing the frequency of eating foods high in salt. TABLE
1
Estimates of sodium content and portion sizes used to calculate sodium intake from question 15 Average Na content both male and female (g/100 g) Milk (from question 1) Breakfast cereals (except Puffed Wheat, Sugar Puffs, Shredded Wheat and Muesli) Bread Margarine or salted butter Cheese (except cottage cheese) Bacon Sausages Meat pies, pate, luncheon meat, etc. Oxo, Marmite, Bovril, etc. (in foods or drinks) Tinned vegetables (including baked beans) Crisps, etc. Salted peanuts Soups (packet or tinned) Shellfish (e.g. prawns, cockles, shrimps) Pickles and sauces (including salad cream)
Portion sizes (g) Males
Females
0·050
Multiplication factor for Q15 Males
Females
0·00406
0·00406
0·776 0·564
33·33 74·02
30·16 51·83
0·259 0·417
0·234 0·293
0·838
16·13
12·06
0·135
0·101
0·705 1·832 1·034
45·22 62·74 87·16
34·45 45·47 65·63
0·319 1·149 0·901
0·243 0·833 0·679
0·906
79·65
66·70
0·722
0·604
5·252
5·36
6·15
0·282
0·323
0·381 0-550 0-440
114·11 28·0 31·0
91-98 28-21 25-30
0-435 0-154 0-136
0-350 0-155 0-111
0·383
229-8
243-64
0-880
0-933
1-840
33-83
40·1
0·622
0-738
1-069
22·99
22·91
0-246
0-245
question 15 are shown in Table 1. Also shown are the estimates of portion sizes for males and females, and the factors used in the calculation of g Na/day from the frequency of eating. The sum of the estimated intake from the items in question 15 was then calculated (Q15).
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Question 1 asked the number of pints of milk drunk per week. This was asked separately since it was felt this would be easier to respond to than a question on frequency of use where portion size for milk varies greatly. The sodium from this source was calculated from the food composition tables, and added to that from question 15 (QIANDQI5). Using the National Food Survey and McCance and Widdowson's Composition of Foods (Paul and Southgate, 1978), it was calculated that the food categories used in this questionnaire account for approximately 83% of average sodium intake (other than table and cooking salt).
Distribution The questionnaires were distributed to 254 staff at the A.F.R.C. Food Research Institute, Norwich, and 169 (67%) were returned. Excluding questionnaires not completed adequately (e.g. "Don't know" answers, no name), along with three which were returned after data analysis, left 155 questionnaires (61 % of those distributed). Seventy-eight of the analyzed responses were from males and 77 from females.
Validation Subjects differed in each section of the validation and sothe number of subjects in each case is different. This is because the results have been combined from several studies where subjects followed the same procedures.
Table salt Fifty-three subjects used salt pots which were weighed at the beginning and end of a 7-day period. Cooking salt Forty-seven of the subjects were also given a salt pot for use in cooking. This was not so straightforward since the salt could not easily be used for cooking food for only the individual studied. In order to get over this problem, the subject was instructed to use the salt normally in cooking for the family but to note the number of meals in which it was used and for how many people each meal was cooked. This allowed the proportion relating to the individual to be calculated. Some of the salt added to vegetables during cooking is thrown away after cooking, only a proportion being absorbed by the food. The estimate of the amount actually consumed was two-thirds of that used in cooking; this is of course an arbitrary estimate and will depend upon the type of foods consumed (Teply & Derse, 1958; Scheffeldt & Blumenthal, 1982). Food content Twenty-three subjects took part in a weighed-intake study for 7 consecutive days. The intake of sodium from food (not added as table or cooking salt) was then calculated using the McCance and Widdowson food composition tables, to give the subject's mean daily sodium intake from this source.
SALT INTAKE BY QUESTIONNAIRE
225
Total salt intake Total intake was estimated from urinary excretion of sodium. Thirty-three subjects collected complete 24-h urine samples over 7 consecutive days. Subjects were asked if any samples were incomplete and these samples were excluded. The urine was analyzed for sodium content by flame photometry (Farleigh et al., 1985), and the mean daily sodium excretion was calculated for each subject.
Reliability Twenty-two subjects completed the same questionnaire for a second time approximately two months after the first; these subjects were among those who had taken part in the validation. The scoring and calculations were identical in both cases.
Data Analysis Principal components analysis was performed on the 155 questionnaire responses. The analysis included a varimax rotation. The relationships between questionnaire items and intake were tested using linear multiple or simple regression analysis, and the reliability using correlations. RESULTS
Intake from Different Sources Correlations were calculated between the salt intake derived from different sources for those subjects who took part in the urine collections. These correlations are shown in Table 2.
Principal Components Analysis The purpose of this analysis was to investigate whether the responses to questions expected to be related to salt use were correlated, and hence have some underlying component in common. If there are several items expected to relate to a particular criterion variable (e.g. salt use) then the responses on those items should be correlated. The principal components analysis attempts to represent the original data on those several items by scores on a small number of components. If the original items correlate well then they will be combined into a single component. In the present analysis a twocomponent solution was found to represent the original data reasonably well, the first
TABLE
2
Correlations between salt from different sources
Urine Na Table Cooking
Table
Cooking
"Food"
0·48*
0·28 0-24
0-91 ** 0-23 -0-11
Notes: For these subjects, the amount from food has been estimated as the total (from urinary sodium) minus table and cooking salt (n = 33)_ * p
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R. SHEPHERD ET AL.
component accounting for 41% of the original variance and the second accounting for a further 17%. The relationship of the components to the original items can be judged by the size of the loadings for the items on the components (Table 3). High loadings (close to 1) mean that the component is closely related to the original item, and hence will represent that item reasonably well, whereas a loading close to zero means the component is unrelated to the original item. The pattern ofloadings shows which of the original items are related, so that on component 1 Q3, Q7 and Q14FR tend to be very closely related to each other and to component 1. Q9FR and Q14EX are less related to component 1, and Q1ANDQ15 is completely independent of this component. On the second component, only Q1ANDQ15 has a high loading and so relates closely to this component. This would imply that there is a common underlying component of adding salt to food (component 1) and an independent component of eating foods high in sodium (component 2). The present analysis included a varimax rotation which aims to maximize the variance accounted for by the two components. Following this procedure, the components need not be perfectly orthogonal (i.e. uncorrelated) and in this case the components were correlated at r=0·25.
Validation Table salt Correlations were calculated between the amount of table salt used and the responses to questions relating to table salt use (Table 4). Although table salt use was found to be related to Q3, Q7, Q14 and Q14FR, the best predictor of table salt use is TABLE
3
Loadings ofthe variables on the two components from the principal components analysis Component 1
Component 2
0·78 0·86 0·43 0·83 0·47 0·03
-0,08 -0,04 -0,09 0·12 0·06 0·99
Q3 Q7 Q9FR Q14FR Q14EX Q1ANDQ15
Notes: A high loading means that the component relates closely to the original variable.
4 Correlations between table salt use and questionnaire responses (n = 53) TABLE
Questionnaire response Q3 Q7 Q14 Q14FR Q14EX Notes:
r
-0'59* 0,50* 0,49* 0,70* 0·11
* p < 0·001.
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SALTINTAKE BY QUESTIONNAIRE
Q14FR. Inclusion of other variables in a multiple regression did not significantly increase the degree of prediction of table salt use since these variables are all correlated together (see principal components analysis above). The regression equation for Q14FR against table salt was used to predict table salt use: table salt (g NeCl/day) = 0·05 +0·40 x Q14FR
(1)
Cooking salt Similar correlations were calculated between cooking salt use and questionnaire responses (Table 5). Q8 was a question on the frequency of eating away from home and was included since it was felt that this might affect the amount of cooking salt used at home. Although this correlation was negative, as expected, it was small and not statistically significant (p > 0'05). Likewise, the other questionnaire items expected to be related to cooking salt use were not statistically significant. Q9FR was used to predict cooking salt use but the prediction using this question is not likely to be of practical value. cooking salt (g NeCl/day) = 0·81 + 0·0032 x Q9FR
(2)
Food content The correlation was calculated between the weighed intake and the estimate of intake from questions 1 and 15. This gave r = 0·57 (n = 23) with the regression equation: ~
food content (g NaCI/day)=4'95 + 1·45 x Q1ANDQ15
(3)
Although it is possible to calculate an estimate of salt intake from food from Q1ANDQ15, it was decided to use this regression equation since it might be that the questionnaire consistently over- or underestimates the contribution.
Total salt intake An estimate of total salt intake was calculated by adding the estimates from equations (1), (2) and (3), which was then correlated with urinary excretion (r = 0,66, n = 33), the regression equation being: salt excretion (g Na Cl/day) = -1,08 + 1·03 x estimate
(4)
A separate multiple regression was also calculated between the subjects' principal components analysis scores and their total sodium excretion. This gave a multiple correlation of 0·69 (n = 33) with the regression equation: salt excretion (g NaCl/day) = 7·96 + 0·21 x component 1 + 1·06 x component 2
(5)
Hence the degree of prediction is approximately equal to that using the previous analysis.
5 Correlations between cooking salt use and questionnaire responses (n=47) TABLE
Questionnaire response
Q7 Q8 Q9FR
r ~26
-0,21 0·17
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R. SHEPHERD ET AL.
6 T est-retest correlations for questionnaire items and estimates of total intake (n = 22) TABLE
Questionnaire items and estimates
r
Individual questions Q1 Q3 Q7 Q9FR 1 Q14FR 1 Q15 Q1ANDQ15 1
0,72* 0,73* 0'78"* 0,70* 0,78* 0,72* 0,71*
Principal components Component 1 Component 2
0,88* 0·71 *
Total salt intake Estimate from equations (1), (2) and (3) Estimate from PCA scores
0'75* 0,75*
Notes: Items marked 1 were used in regressions to calculate total intake. * p
T est-retest Reliability The correlations between the two occasions for the individual questions relating to salt intake are shown in Table 6. Also shown are the test-retest correlations for the subjects' scores on the two components from the principal components analysis, and for the estimates of total salt intake.
Correction for Attenuation When the correlation between two variables is calculated there is a limit on the magnitude of the correlation, which is dependent on the reliability of the measurements of the variables (Guilford, 1954). If the calculated correlation between variables x and y is rxy and the test-retest reliabilities of the two variables are rxx and ryy respectively, an estimate of the true correlation between the variables (i.e. the correlation if both had been measured with perfect reliability) is given by the equation:
In the present study, the test-retest reliabilities of the questionnaire items have been measured. From other studies we have performed using the same techniques, it is possible to calculate the reliability of the measures of usage involving table and cooking salt pots, weighed intake and urine excretion. These test-retest reliabilities are shown in Table 7. Using these values, the correlations between the questionnaire estimates and the various criterion variables have been adjusted, and these are also shown in Table 7.
Comparison with Single 24-hour Urine In-order to compare the usefulness of the present questionnaire with that of a single 24-h urine sample, the correlation was calculated between the subjects' first 24-h sodium excretion and the mean over the following six days. This gave a value ofr = 0·39
229
SALT INTAKE BY QUESTIONNAIRE TABLE
7
Correlations of questionnaire estimates with criterion variables after correction for attenuation (n = 33) Criterion variable
Reliability r
Table salt Cooking salt Weighed intake Sodium excretion
(n = 33) compared with r
0·92 0·90 0·87 0·83
Questionnaire variable Q14FR Q9FR Q1ANDQ15 Estimate from equations (1), (2) and (3)
Reliability r
Corrected correlation with criterion r
0·78 0·70 0·71 0·75
0·83 0·22 0·72 0·84
= 0·66 for the questionnaire estimate. Hence, although the
questionnaire estimate is not perfect at an individual level, it is a better predictor of intake (estimated from excretion) than a single 24-h urine collection. DISCUSSION
If it is desired to measure accurately the salt intake of individual subjects, then it is necessary to collect urine samples over several days and analyze these for sodium. However, in other circumstances such a degree of accuracy is either impracticable or not necessary. In large epidemiological studies, in studies where only group data are required or where subjects are to be classified into broad groups on the basis of their salt intake, it would be preferable to use a simpler method. The aim of this study was to develop a questionnaire for this purpose. The reliability of the questionnaire was tested and found to give a test-retest correlation of 0·75 for the estimate of total intake, and correlations of between 0·70 and 0·88 for the individual questionnaire items. These values would be as expected for this type of procedure (e.g. Maller et al., 1982) and demonstrate that the responses from subjects are reasonably stable. Some of the variation in response to some items may be due to seasonal variation in foods consumed, since the two presentations were separated by two months. , Whilst it would be possible to test the degree of prediction of total intake by using a multiple regression of individual questionnaire items against urinary excretion, this was not done in the present study. Nunnally (1978) has argued that with questionnaires with multiple items expected to relate to some criterion, the relationships of the items to each other should be investigated rather than regressing individual items against a criterion variable. This is because, if there is an underlying common component, the items relating well to that component will themselves be correlated. Principal components analysis (or factor analysis) demonstrates the existence of such common underlying components and represents the original data in terms of these components. Item-wise multiple regression on the other hand, having fitted one dependent variable to the criterion variable, then increases the degree of prediction by adding in further dependent variables which are least correlated with the first-entered dependent variable. This approach assumes a collection of dependent variables which are only slightly related to each other, whereas in the design of multiple item questionnaires the
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R. SHEPHERD ET .AL.
aim is generally to find items which are related and hence measure the underlying component. In the present experiment the structure of the questionnaire responses was investigated using principal components analysis. The questions thought to relate to salt use were found to be measuring some common component. If the responses to these questions had not been related, then they could not reflect some common underlying behaviour and therefore could not be measuring simply the salt use. The responses to the question on frequency of eating high sodium foods were independent of this salt use component giving rise to the second component. Using multiple regression analysis to predict total salt intake from these two components gave a multiple R of 0·69, showing comparatively good prediction of intake. Predictions of salt intake from different sources from the sodium present in foods were relatively successful for table salt use and food intake, but the prediction of cooking salt use was not. The question expected to be related to cooking salt use was not very predictive of usage, even when modified by the frequency of eating foods expected to be salted in cooking. This may relate to the relative difficulty of estimating the proportion of cooking salt ingested by the individual. Although usage had a negative correlation with the reported frequency of eating away from the home, this association was small and not statistically significant. In order to get a better estimate of cooking salt use, it may be more informative to ask subjects to estimate the amounts of salt added to a list offoods in a form similar to the question on salt added at the table. In the case of table salt use, the best predictor was Q14FR which gave a higher correlation than the simple sum of the number of items salted (i.e. Q14) not modified by the stated frequency of consumption of the items. Q14FR was also a better predictor than the "salting before tasting" question (Q3) which Maller et al. (1982) found to be the best predictor of use in the more controlled experimental setting used in their study. In the present study where use of table salt in ordinary life was measured, Q3 was less useful. However, the extended question on items salted (question 14) proved more useful than Maller's original version. The prediction of sodium intake from foods was also good. Since this source provides the major contribution to total intake, such a prediction is obviously important. Weighting individual food items according to estimates of sodium content and average portion sizes for males and females offers an improvement on the system used by Pietinen et ale (1982), where a small number of food items were used and weighted equally. Although the present questionnaire might be improved if estimates of portion sizes were made by individual subjects, this would be difficult to incorporate in the questionnaire in its present form. It could be done by the use of model foods which would then require an interviewer to administer the questionnaire, rather than selfadministration, and would become a more time-consuming exercise. Estimation of total intake calculated from the different sources proved relatively successful (r = 0·66). This would therefore be useful in trying to differentiate subjects into groups on the basis of their intake. One of the factors limiting the correlations reported is the test-retest reliabilities of both the questionnaire and the criterion variables. Taking these into account gives an indication of the underlying relationship between the variables if both had been measured with perfect reliability; this was found to be r = 0·84. This approach of assessing the frequency of consumption of specific foods which are large contributors to salt intake, along with obtaining quantified estimates of table and cooking salt use, offers an improvement on previous attempts to estimate intake by questionnaire.
SALT INTAKE BY QUESTIONNAIRE
231
Hence the questionnaire described provides a quick and simple estimate of a subjects' intake of salt, taking only about 10 min to complete. It gave a better estimate of total intake (estimated by 7-day urine sodium) than a single 24-h urine collection. Although it would not give as good an estimate as collection of several complete urine samples, it has the advantage of being simple for subjects to complete and requires none of the commitment necessary to take part in extended urine collection. One problem with validating the questionnaire against urine sodium and measured table and cooking salt use is that taking part in these measurements may influence the intake of the individual (see discussion in Stockley, 1985). Thus these measures may not reflect habitual intake. It may be that a questionnaire on intake is less reactive than these measures, but then there is the need to validate the questionnaire against some criterion. This problem is difficult to resolve, given the impossibility generally of weighing the amount of salt used by an individual without their being aware of this process. Thus, even if estimation of intake by questionnaire is less affected by changes from the habitual diet, it is difficult to demonstrate this if the criterion measures used are affected. There would be problems in using the present questionnaire with subjects not having a normal British diet, e.g. ethnic groups, but the same format and approach could be used. If the foods consumed differed greatly, it would be necessary to include those foods which would be major contributors to salt intake for the target group and then to validate the new form of the questionnaire with this group. Likewise, variations in salting habits in cooking and at the table would modify the regression equations, but the same basic method of assessment could be used in these cases. Further work using modifications of this questionnaire with subjects not connected with research on food has shown generally good agreement with the present results (Shepherd & Farleigh, Note 2). It should be emphasized, however, that the validation presented here is on a limited and specific groups of subjects and the equations presented may not generalize to other groups. Use with substantially differing groups of subjects would require further validation.
REFERENCE NOTES
1. Nelson, M. A dietary survey method for measuring family food purchases and individual nutrient intakes concurrently, and its use in dietary surveillance. Unpublished PhD Thesis, University of London, 1983. 2. Shepherd, R. & Farleigh, C. A. Salt intake assessment by questionnaire and urinary sodium excretion. 1985, in preparation. REFERENCES
Bass, B. M., Cascio, W. F. & O'Connor, E. J. Magnitude estimations of expressions of frequency and amount. Journal of Applied Psychology, 1974, 59, 313-320. Beevers, D. G., Hawthorne, V. M. & Padfield, P. L. Salt and blood pressure in Scotland. British Medical Journal, 1980, 281, 641-642. Chauncey, H. H., Wallace, S. & Alman, J. E. Salivary chloride levels, taste thresholds for salt, and food ingestion. In M. R. Kare, M. J. Fregly & R. A. Bernard (Eds.), Biological and behavioral aspects of salt intake. Pp. 113-125. New York: Academic Press, 1980. Dahl, L. K. Evidence for an increased intake of sodium in hypertension based on urinary excretion of sodium. Proceedings of the Society of Experimental and Biological Medicine, 1957, 94, 23-26.
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Dahl, L. K. & Love, R. A. Evidence for relationship between sodium (chloride) intake and human essential hypertension. Archives of Internal Medicine, 1954, 94, 525-531. Dahl, L. K. & Love, R. A. Etiological role of sodium chloride intake in essential hypertension in humans. Journal of the American Medical Association, 1957,167,397-400. Dawber, T. R., Kannel~ W. B., Kagan, A., Donabedian, R. K., McNamara, R. M. & Pearson, G. Environmental factors in hypertension. In 1. Stamler, R. Stamler & T. N. Pulman (Eds.), The epidemiology of hypertension. Pp.255-288. New York: Grune and Stratton, 1967. Farleigh, C. A., Shepherd, R. & Land, D. G. Measurement of sodium intake and its relationship to blood pressure and saliva sodium concentration. Nutrition Research, 1985 (in press). Faust, H. S. Effects of drinking water and total sodium intake on blood pressure. American Journal of Clinical Nutrition, 1982,35, 1459-1467. Fregly, M. S. & Fregly, M. J. The estimates of sodium intake in man. In M. J. Fregly & M. R. Kare (Eds.), The role ofsalt in cardiovascular hypertension. Pp. 3-17. New York: Academic Press, 1983. Guilford, 1. P. Psychometric methods. New York: McGraw-Hill, 1954. Hankin, J. H., Messinger, H. B. & Stallones, R. A. A short dietary method for epidemiologic studies. IV. Evaluation of questionnaire. American Journal of Epidemiology, 1970, 91, 562-567. Hankin, J. H., Reynolds, W. E. & Margen, S. A short dietary method for epidemiologic studies. II. Variability of measured nutrient intakes. American Journal of Clinical Nutrition, 1967, 20, 935-945. Hankin, 1. H., Stallones, R. A. & Messinger, H. B. A short dietary method for epidemiologic studies. III. Development of questionnaire. American Journal of Epidemiology, 1968, 87, 285-298. Hill, L. L., Montandon, C. M., Scott, L., Hammond, G. S., Tristan, M. P. & Baer, P. E. Validation of a salt intake questionnaire by urinary electrolyte excretion. Preventive Medicine, 1980,9, 436. James, W. P. T., Bingham, S. A. & Cole, T. J. Epidemiological assessment of dietary intake. Nutrition and Cancer, 1981, 2, 203-212. Maller, 0., Cardello, A., Sweeney, J. & Shapiro, D. Psychophysical and cognitive correlates of discretionary usage of table salt and sugar by humans. In 1. E. Steiner & J. R. Ganchrow (Eds.), Determination of behaviour by chemical stimuli. Pp.205-218. London: IRL Press, 1982. Marr, 1. W. Individual dietary surveys: Purposes and methods. World Review of Nutrition and Dietetics, 1971, 13,105-164. Medeiros, D. M. & Borgman, R. F. Blood pressure in young adults as associated with dietary habits, body conformation, and hair element concentrations. Nutrition Research, 1982, 2, 455-466. Meneely, G. R. & Battarbee, H. D. High sodium-low potassium environment and hypertension. American Journal of Cardiology, 1976, 38, 768-785. Nunnally, 1. C. Psychometric theory (2nd ed.). New York: McGraw-Hill, 1978. Pangborn, R. M. & Pecore, S. D. Taste perception of sodium chloride in relation to dietary intake of salt. American Journal of Clinical Nutrition, 1982, 35, 510-520. Paul, A. A. & Southgate, D. A. T. McCance and Widdowson's The Composition ofFoods. London: HMSO, 1978. Pietinen, P., Tanskanan, A. & Tuomilehto, J. Assessment of sodium intake by a short dietary questionnaire. Scandinavian Journal of Social Medicine, 1982,10,105-112. Scheffeldt, P. & Blumenthal, A. The influence ofdifferent salt concentrations in the cooking water on the mineral and trace element contents of prepared vegetables. Alimenta, 1982, 21, 41-50. Stockley, L. Changes in habitual food intake during weighed inventory surveys and duplicate diet collection. A short review. Ecology of Food and Nutrition, 1985 (in press). Swaye, P. S., Gifford, R. W. & Berrettoni, 1. N. Dietary salt and essential hypertension. American Journal of Cardiology, 1972,29,33-38. Teply, L. J. & Derse, P. H. Nutrients in cooked frozen vegetables. Journal ofthe American Dietetic Association, 1958, 34, 836-840. Tobian, L. The relationship of salt to hypertension. American Journal ofClinical Nutrition, 1979, 32, 2739-2748.
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Tuomilehto, J., Karppanen, H., Tanskanen, A., Tikkanen, J. & Vuori, 1. Sodium and potassium excretion in a sample of normotensive and hypertensive persons in Eastern Finland. Journal of Epidemiology and Community Health, 1980, 34, 174-178. 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. Human Nutrition: Applied Nutrition, 1983, 37 A, 103-112.
Received 20 July 1984, revisions 24 January 1985 and 30 May 1985
Estimation of Salt Intake by Questionnaire R. SHEPHERD, C. A. FARLEIGH and D. G. LAND A.F.R.C. Food Research Institute, Norwich
A questionnaire designed to assess salt intake was tested. This involved principal components analysis of responses from 155 subjects to find the underlying components related to the questions. Validation of the questionnaire used 7-day urinary sodium excretion for 33 subjects, along with table and cooking salt usage over 7-days. This gave comparatively good prediction for total intake (r = 0'66) and table salt use (r = 0'70) but not for cooking salt use (r = 0,17). Test-retest reliability for the estimate of total intake was r = 0·75. This method would therefore offer a useful estimate of total intake, especially where group means are required rather than accurate estimates of individual intakes.
INTRODUCTION
In recent years there has been a great deal of research on the relationship between high blood pressure and salt intake (Meneely & Battarbee, 1976; Tobian, 1979). In studies of this type it is necessary to estimate the salt, or sodium, intake of individuals or groups. Several different methods may be used, depending on the type of study undertaken and the importance of factors such as required level of accuracy, inconvenience to subjects, or the number of subjects involved. The most popular method of estimating sodium intake is by measuring sodium excretion. Most studies seeking to relate salt intake to high blood pressure have used single 24-h urine collections (e.g. Dawber, Kannel, Kagan, Donabedian, McNamara & Pearson, 1967; Swaye, Gifford & Berrettoni, 1972). Although excretion is a good indicator of intake, it is variable over days within subjects and so, in order to classify subjects accurately, it is necessary to obtain several complete 24..h urine collections (James, Bingham & Cole, 1981; Farleigh, Shepherd & Land, 1985). However, it would be impossible to collect several samples in a large-scale epidemiological study. There have been many attempts at estimating nutrient intake using questionnaires based on the frequency of eating foods (e.g. Marr, 1971; Yarnell, Fehily, Milbank, Sweetnam & Walker, 1983). Such questionnaires on general food consumption do not generally give good estimates for particular nutrients. One method of overcoming this problem is to design questionnaires individually for specific nutrients, and include
The authors would like to thank Dr. M. Nelson of the MRC Epidemiology Unit, Southampton for making available data on weighed intakes from which the estimates of average portion sizes were calculated. We would also like to thank Lynn Stockley for making available data on weighed intakes which were used to validate the food content portion of the questionnaire. Reprint requests should be addressed to Dr. R. Shepherd, A.F.R.C. Food Research Institute, Colney Lane, Norwich NR4 7UA. 0195-6663/85/030219+ 15 $03'00/0
© 1985 Academic Press Inc. (London) Limited
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questions only on those foods which are major contributors to the intake of the particular nutrient. In the case of sodium intake, there is also the problem of salt added to food at the table and in cooking, which cannot be estimated by such frequency of consumption questionnaires. There have been several studies reported using questionnaires designed specifically to assess salt intake. Some have included no external validation of the questionnaire (Dahl & Love, 1954; Dahl & Love, 1957; Pangborn & Pecore, 1982), whilst others report the use of questionnaires where the validation has not been published (Chauncey, Wallace & Alman, 1980). Several studies have involved a single 24-h urine collection to estimate total salt intake, along with the Dahl & Love (1954) classification by table salt use, or a modification of this to include questions on eating salty foods. Whilst Dahl (1957) and Swaye et ale (1972) found groups of subjects to differ in sodium excretion, Dawber et ale (1967) and Beevers, Hawthorne & Padfield (1980) found no difference. Tuomilehto, Karppanen, Tanskanen, Tikkanen & Vuori (1980) did not test for a statistical difference between the groups. There are two problems with these studies. The first is the use of a single 24-h urine collection, which will be a very poor indicator of habitual sodium intake for individuals (James et al., 1981). Secondly, there is the use of urinary sodium, which is a measure of total intake, as a criterion for a classification by table salt use, whereas table salt use is only a small contributor to total intake (Fregly & Fregly, 1983). Questionnaires have been devised which include the frequency of consumption or liking for foods high in salt. This is likely to be a more successful procedure, since a much larger proportion of total intake derives from this source than from table salt use (Fregly & Fregly, 1983). Again, not all of these have been validated (Medeiros & Borgman, 1982). Hankin, Reynolds & Margen (1967), using a 7-day weighed intake, found consumption of a small number of foods predicted salt intake in a group of Japanese-Americans, but this may relate only to the specific diet of this particular ethnic group. A questionnaire based on these foods was constructed (Hankin, Stallones & Messinger, 1968) but a subsequent test of the questionnaire on a subsample of the original subjects showed it to be much poorer at estimating sodium intake, with a correlation of 0·33 (Hankin, Messinger & Stallones, 1970). Hill, Montandon, Scott, Hammond, Tristan & Baer (1980) used. two '24-h urine collections and found no .prediction for sodium excretion from their questionnaire. Faust (1982) found no general relationship (although there was' a correlation for a subgroup of 6 subjects). Pietinen, Tanskanen & Tuomilehto (1982) found significant but very small correlations using a single 24-h urine sample (males r = 0·18, females r = 0·20). Maller, Cardello, Sweeney & Shapiro (1982) described a questionnaire designed specifically to assess table salt use. They measured table salt use at standard meals and found their questionnaire to be a good predictor of usage (for best single question, r = 0·73; for best 2 questions, multiple R = 0·88). However, this was in a controlled setting, rather than in normal life, and the number of subjects was small (N = 12). Although previous questionnaires provide a relatively good estimate of table salt use in a controlled setting, they are not so useful for estimating intake in ordinary life, and particularly so for total salt intake. However, within a health context, interest is usually centred on total salt intake. The aim of the present study was to develop a relatively short questionnaire designed specifically to measure sodium intake and to assess intake from different sources. It was hoped that this would allow reasonably accurate assessment without the inconvenience of collecting urine samples.
SALT INTAKE BY QUESTIONNAIRE
221
METHOD
Design The questionnaire included questions on table salt use, cooking salt use and the frequency of eating foods high in sodium. Other questions were included, mainly on the use of sugar, in order to disguise the purpose of the questionnaire which was entitled "Survey of Food Intake". The questions relating to salt use are shown in Figure 1. The responses to the extra questions were not analyzed. More recent work using modifications of the questionnaire does not show any differences in responses between the questionnaire with these extra questions included or excluded (Shepherd & Farleigh, Note 2). Cooking use was assessed in question 9. The distance along the scale was modified by the frequency of eating foods expected to be salted during cooking (cooked fresh vegetables, boiled potatoes, rice, spaghetti) giving Q9FR. There were two questions relating to the use of table salt (questions 3 and 14). Question 3 on salting food at the table before tasting was found by Maller et ale (1982) to be the best predictor of table salt use from among 12 questions. Their second-best predictor was a question on how often subjects added salt to hamburger, french fries and/or popcorn. This was modified in question 14 where subjects ticked whether they added salt to each of a list of foods, the total giving Q 14. The foods were changed from the original American version because of differences between the two cultures in foods normally salted. The response to each food was modified by how often it is eaten to give Q14FR. Subjects could write in any other foods salted, the number of foods giving Q14EX. One further question was included from the Maller et ale (1982) questionnaire on the importance of salt to the subject's enjoyment offood (question 7), the distance along the scale giving Q7. This is a more general question on attitude rather than actual behaviour, and might be related to the use of salt both at the table and in cooking. Question 15 was on the frequency of eating 24 foods. These were 14 foods high in sodium, the nine foods from question 14, and the extra one being "cooked fresh vegetables". The frequency of eating responses was on a 100 mm graphic scale, as in the earlier questions, but the anchors were labelled "Never", "Monthly", "Weekly", "Daily" and "Six times per day", and were spaced logarithmically along the line ("Never" would correspond to less than once a year). An example for one food is shown in Figure 2. The distance along the scale was then converted to a frequency, making use of the logarithmic nature of the scale. This does not involve the difficulties in quantifying responses on scales with labels such as "often", "frequently", etc., found by Bass, Cascio & O'Connor (1974). The 14 high sodium foods in question 15 are shown in Table 1 (along with milk which was assessed separately in question 1). Portion sizes were not included in the questionnaire, but instead average portion sizes were estimated from data collected by Nelson (Note 1). This involved 7-day semiweighed intakes by 100 men and 111 women, i.e. most of the foods were weighed but standard measures were used for some foods. The portion sizes were calculated separately for males and females. The mean portion size was calculated from every occasion a subject in Nelson's study ate one of the foods which would fall into one of the categories in the present questionnaire. The average sodium content for the questionnaire items were weighted according to how often the subjects in Nelson's study had eaten the individual foods. The calculated average sodium values for the 14 items in
222
R. SHEPHERD ET AL. 14 )
Do you usually add salt to the following foods at the table?
Yes
(i)
Chips
(ii)
Boiled eggs
(ii n
Eggs
(iv)
Tomatoes
(v)
Boi led potatoes
(vi)
Baked potatoes
(vii)
Boiled rice
( viii)
Spaghetti or other pasta
( ix)
Porridge
( x)
Other foods -
Not eaten
No
(other than boiled)
please specify
(a)
1)
How much milk do you drink in an average week?
None
3)
2.5 pints
5 pints
7.5 pints
Do you salt food at the table before tasting it?
Never
Always
7)
How important is salt to your enjoyment of food?
Not important
9)
10 pints
Very important
How much salt is added during cooking to the vegetables you eat at home?
Very much
None
(b) FIGURE
1.
Questionnaire items on table and cooking salt use.
223
SALT INTAKE BY QUESTIONNAIRE Breakfast cereals (except Puffed Wheat, Sugar Puffs, Shredded Wheat and Muesli)
Never
Monthly
Weekly
Daily
I
I
I
6 times per day
I
FIGURE 2. Example of form of items in question 15 for assessing the frequency of eating foods high in salt. TABLE
1
Estimates of sodium content and portion sizes used to calculate sodium intake from question 15 Average Na content both male and female (g/100 g) Milk (from question 1) Breakfast cereals (except Puffed Wheat, Sugar Puffs, Shredded Wheat and Muesli) Bread Margarine or salted butter Cheese (except cottage cheese) Bacon Sausages Meat pies, pate, luncheon meat, etc. Oxo, Marmite, Bovril, etc. (in foods or drinks) Tinned vegetables (including baked beans) Crisps, etc. Salted peanuts Soups (packet or tinned) Shellfish (e.g. prawns, cockles, shrimps) Pickles and sauces (including salad cream)
Portion sizes (g) Males
Females
0·050
Multiplication factor for Q15 Males
Females
0·00406
0·00406
0·776 0·564
33·33 74·02
30·16 51·83
0·259 0·417
0·234 0·293
0·838
16·13
12·06
0·135
0·101
0·705 1·832 1·034
45·22 62·74 87·16
34·45 45·47 65·63
0·319 1·149 0·901
0·243 0·833 0·679
0·906
79·65
66·70
0·722
0·604
5·252
5·36
6·15
0·282
0·323
0·381 0-550 0-440
114·11 28·0 31·0
91-98 28-21 25-30
0-435 0-154 0-136
0-350 0-155 0-111
0·383
229-8
243-64
0-880
0-933
1-840
33-83
40·1
0·622
0-738
1-069
22·99
22·91
0-246
0-245
question 15 are shown in Table 1. Also shown are the estimates of portion sizes for males and females, and the factors used in the calculation of g Na/day from the frequency of eating. The sum of the estimated intake from the items in question 15 was then calculated (Q15).
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Question 1 asked the number of pints of milk drunk per week. This was asked separately since it was felt this would be easier to respond to than a question on frequency of use where portion size for milk varies greatly. The sodium from this source was calculated from the food composition tables, and added to that from question 15 (QIANDQI5). Using the National Food Survey and McCance and Widdowson's Composition of Foods (Paul and Southgate, 1978), it was calculated that the food categories used in this questionnaire account for approximately 83% of average sodium intake (other than table and cooking salt).
Distribution The questionnaires were distributed to 254 staff at the A.F.R.C. Food Research Institute, Norwich, and 169 (67%) were returned. Excluding questionnaires not completed adequately (e.g. "Don't know" answers, no name), along with three which were returned after data analysis, left 155 questionnaires (61 % of those distributed). Seventy-eight of the analyzed responses were from males and 77 from females.
Validation Subjects differed in each section of the validation and sothe number of subjects in each case is different. This is because the results have been combined from several studies where subjects followed the same procedures.
Table salt Fifty-three subjects used salt pots which were weighed at the beginning and end of a 7-day period. Cooking salt Forty-seven of the subjects were also given a salt pot for use in cooking. This was not so straightforward since the salt could not easily be used for cooking food for only the individual studied. In order to get over this problem, the subject was instructed to use the salt normally in cooking for the family but to note the number of meals in which it was used and for how many people each meal was cooked. This allowed the proportion relating to the individual to be calculated. Some of the salt added to vegetables during cooking is thrown away after cooking, only a proportion being absorbed by the food. The estimate of the amount actually consumed was two-thirds of that used in cooking; this is of course an arbitrary estimate and will depend upon the type of foods consumed (Teply & Derse, 1958; Scheffeldt & Blumenthal, 1982). Food content Twenty-three subjects took part in a weighed-intake study for 7 consecutive days. The intake of sodium from food (not added as table or cooking salt) was then calculated using the McCance and Widdowson food composition tables, to give the subject's mean daily sodium intake from this source.
SALT INTAKE BY QUESTIONNAIRE
225
Total salt intake Total intake was estimated from urinary excretion of sodium. Thirty-three subjects collected complete 24-h urine samples over 7 consecutive days. Subjects were asked if any samples were incomplete and these samples were excluded. The urine was analyzed for sodium content by flame photometry (Farleigh et al., 1985), and the mean daily sodium excretion was calculated for each subject.
Reliability Twenty-two subjects completed the same questionnaire for a second time approximately two months after the first; these subjects were among those who had taken part in the validation. The scoring and calculations were identical in both cases.
Data Analysis Principal components analysis was performed on the 155 questionnaire responses. The analysis included a varimax rotation. The relationships between questionnaire items and intake were tested using linear multiple or simple regression analysis, and the reliability using correlations. RESULTS
Intake from Different Sources Correlations were calculated between the salt intake derived from different sources for those subjects who took part in the urine collections. These correlations are shown in Table 2.
Principal Components Analysis The purpose of this analysis was to investigate whether the responses to questions expected to be related to salt use were correlated, and hence have some underlying component in common. If there are several items expected to relate to a particular criterion variable (e.g. salt use) then the responses on those items should be correlated. The principal components analysis attempts to represent the original data on those several items by scores on a small number of components. If the original items correlate well then they will be combined into a single component. In the present analysis a twocomponent solution was found to represent the original data reasonably well, the first
TABLE
2
Correlations between salt from different sources
Urine Na Table Cooking
Table
Cooking
"Food"
0·48*
0·28 0-24
0-91 ** 0-23 -0-11
Notes: For these subjects, the amount from food has been estimated as the total (from urinary sodium) minus table and cooking salt (n = 33)_ * p
226
R. SHEPHERD ET AL.
component accounting for 41% of the original variance and the second accounting for a further 17%. The relationship of the components to the original items can be judged by the size of the loadings for the items on the components (Table 3). High loadings (close to 1) mean that the component is closely related to the original item, and hence will represent that item reasonably well, whereas a loading close to zero means the component is unrelated to the original item. The pattern ofloadings shows which of the original items are related, so that on component 1 Q3, Q7 and Q14FR tend to be very closely related to each other and to component 1. Q9FR and Q14EX are less related to component 1, and Q1ANDQ15 is completely independent of this component. On the second component, only Q1ANDQ15 has a high loading and so relates closely to this component. This would imply that there is a common underlying component of adding salt to food (component 1) and an independent component of eating foods high in sodium (component 2). The present analysis included a varimax rotation which aims to maximize the variance accounted for by the two components. Following this procedure, the components need not be perfectly orthogonal (i.e. uncorrelated) and in this case the components were correlated at r=0·25.
Validation Table salt Correlations were calculated between the amount of table salt used and the responses to questions relating to table salt use (Table 4). Although table salt use was found to be related to Q3, Q7, Q14 and Q14FR, the best predictor of table salt use is TABLE
3
Loadings ofthe variables on the two components from the principal components analysis Component 1
Component 2
0·78 0·86 0·43 0·83 0·47 0·03
-0,08 -0,04 -0,09 0·12 0·06 0·99
Q3 Q7 Q9FR Q14FR Q14EX Q1ANDQ15
Notes: A high loading means that the component relates closely to the original variable.
4 Correlations between table salt use and questionnaire responses (n = 53) TABLE
Questionnaire response Q3 Q7 Q14 Q14FR Q14EX Notes:
r
-0'59* 0,50* 0,49* 0,70* 0·11
* p < 0·001.
227
SALTINTAKE BY QUESTIONNAIRE
Q14FR. Inclusion of other variables in a multiple regression did not significantly increase the degree of prediction of table salt use since these variables are all correlated together (see principal components analysis above). The regression equation for Q14FR against table salt was used to predict table salt use: table salt (g NeCl/day) = 0·05 +0·40 x Q14FR
(1)
Cooking salt Similar correlations were calculated between cooking salt use and questionnaire responses (Table 5). Q8 was a question on the frequency of eating away from home and was included since it was felt that this might affect the amount of cooking salt used at home. Although this correlation was negative, as expected, it was small and not statistically significant (p > 0'05). Likewise, the other questionnaire items expected to be related to cooking salt use were not statistically significant. Q9FR was used to predict cooking salt use but the prediction using this question is not likely to be of practical value. cooking salt (g NeCl/day) = 0·81 + 0·0032 x Q9FR
(2)
Food content The correlation was calculated between the weighed intake and the estimate of intake from questions 1 and 15. This gave r = 0·57 (n = 23) with the regression equation: ~
food content (g NaCI/day)=4'95 + 1·45 x Q1ANDQ15
(3)
Although it is possible to calculate an estimate of salt intake from food from Q1ANDQ15, it was decided to use this regression equation since it might be that the questionnaire consistently over- or underestimates the contribution.
Total salt intake An estimate of total salt intake was calculated by adding the estimates from equations (1), (2) and (3), which was then correlated with urinary excretion (r = 0,66, n = 33), the regression equation being: salt excretion (g Na Cl/day) = -1,08 + 1·03 x estimate
(4)
A separate multiple regression was also calculated between the subjects' principal components analysis scores and their total sodium excretion. This gave a multiple correlation of 0·69 (n = 33) with the regression equation: salt excretion (g NaCl/day) = 7·96 + 0·21 x component 1 + 1·06 x component 2
(5)
Hence the degree of prediction is approximately equal to that using the previous analysis.
5 Correlations between cooking salt use and questionnaire responses (n=47) TABLE
Questionnaire response
Q7 Q8 Q9FR
r ~26
-0,21 0·17
228
R. SHEPHERD ET AL.
6 T est-retest correlations for questionnaire items and estimates of total intake (n = 22) TABLE
Questionnaire items and estimates
r
Individual questions Q1 Q3 Q7 Q9FR 1 Q14FR 1 Q15 Q1ANDQ15 1
0,72* 0,73* 0'78"* 0,70* 0,78* 0,72* 0,71*
Principal components Component 1 Component 2
0,88* 0·71 *
Total salt intake Estimate from equations (1), (2) and (3) Estimate from PCA scores
0'75* 0,75*
Notes: Items marked 1 were used in regressions to calculate total intake. * p
T est-retest Reliability The correlations between the two occasions for the individual questions relating to salt intake are shown in Table 6. Also shown are the test-retest correlations for the subjects' scores on the two components from the principal components analysis, and for the estimates of total salt intake.
Correction for Attenuation When the correlation between two variables is calculated there is a limit on the magnitude of the correlation, which is dependent on the reliability of the measurements of the variables (Guilford, 1954). If the calculated correlation between variables x and y is rxy and the test-retest reliabilities of the two variables are rxx and ryy respectively, an estimate of the true correlation between the variables (i.e. the correlation if both had been measured with perfect reliability) is given by the equation:
In the present study, the test-retest reliabilities of the questionnaire items have been measured. From other studies we have performed using the same techniques, it is possible to calculate the reliability of the measures of usage involving table and cooking salt pots, weighed intake and urine excretion. These test-retest reliabilities are shown in Table 7. Using these values, the correlations between the questionnaire estimates and the various criterion variables have been adjusted, and these are also shown in Table 7.
Comparison with Single 24-hour Urine In-order to compare the usefulness of the present questionnaire with that of a single 24-h urine sample, the correlation was calculated between the subjects' first 24-h sodium excretion and the mean over the following six days. This gave a value ofr = 0·39
229
SALT INTAKE BY QUESTIONNAIRE TABLE
7
Correlations of questionnaire estimates with criterion variables after correction for attenuation (n = 33) Criterion variable
Reliability r
Table salt Cooking salt Weighed intake Sodium excretion
(n = 33) compared with r
0·92 0·90 0·87 0·83
Questionnaire variable Q14FR Q9FR Q1ANDQ15 Estimate from equations (1), (2) and (3)
Reliability r
Corrected correlation with criterion r
0·78 0·70 0·71 0·75
0·83 0·22 0·72 0·84
= 0·66 for the questionnaire estimate. Hence, although the
questionnaire estimate is not perfect at an individual level, it is a better predictor of intake (estimated from excretion) than a single 24-h urine collection. DISCUSSION
If it is desired to measure accurately the salt intake of individual subjects, then it is necessary to collect urine samples over several days and analyze these for sodium. However, in other circumstances such a degree of accuracy is either impracticable or not necessary. In large epidemiological studies, in studies where only group data are required or where subjects are to be classified into broad groups on the basis of their salt intake, it would be preferable to use a simpler method. The aim of this study was to develop a questionnaire for this purpose. The reliability of the questionnaire was tested and found to give a test-retest correlation of 0·75 for the estimate of total intake, and correlations of between 0·70 and 0·88 for the individual questionnaire items. These values would be as expected for this type of procedure (e.g. Maller et al., 1982) and demonstrate that the responses from subjects are reasonably stable. Some of the variation in response to some items may be due to seasonal variation in foods consumed, since the two presentations were separated by two months. , Whilst it would be possible to test the degree of prediction of total intake by using a multiple regression of individual questionnaire items against urinary excretion, this was not done in the present study. Nunnally (1978) has argued that with questionnaires with multiple items expected to relate to some criterion, the relationships of the items to each other should be investigated rather than regressing individual items against a criterion variable. This is because, if there is an underlying common component, the items relating well to that component will themselves be correlated. Principal components analysis (or factor analysis) demonstrates the existence of such common underlying components and represents the original data in terms of these components. Item-wise multiple regression on the other hand, having fitted one dependent variable to the criterion variable, then increases the degree of prediction by adding in further dependent variables which are least correlated with the first-entered dependent variable. This approach assumes a collection of dependent variables which are only slightly related to each other, whereas in the design of multiple item questionnaires the
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aim is generally to find items which are related and hence measure the underlying component. In the present experiment the structure of the questionnaire responses was investigated using principal components analysis. The questions thought to relate to salt use were found to be measuring some common component. If the responses to these questions had not been related, then they could not reflect some common underlying behaviour and therefore could not be measuring simply the salt use. The responses to the question on frequency of eating high sodium foods were independent of this salt use component giving rise to the second component. Using multiple regression analysis to predict total salt intake from these two components gave a multiple R of 0·69, showing comparatively good prediction of intake. Predictions of salt intake from different sources from the sodium present in foods were relatively successful for table salt use and food intake, but the prediction of cooking salt use was not. The question expected to be related to cooking salt use was not very predictive of usage, even when modified by the frequency of eating foods expected to be salted in cooking. This may relate to the relative difficulty of estimating the proportion of cooking salt ingested by the individual. Although usage had a negative correlation with the reported frequency of eating away from the home, this association was small and not statistically significant. In order to get a better estimate of cooking salt use, it may be more informative to ask subjects to estimate the amounts of salt added to a list offoods in a form similar to the question on salt added at the table. In the case of table salt use, the best predictor was Q14FR which gave a higher correlation than the simple sum of the number of items salted (i.e. Q14) not modified by the stated frequency of consumption of the items. Q14FR was also a better predictor than the "salting before tasting" question (Q3) which Maller et al. (1982) found to be the best predictor of use in the more controlled experimental setting used in their study. In the present study where use of table salt in ordinary life was measured, Q3 was less useful. However, the extended question on items salted (question 14) proved more useful than Maller's original version. The prediction of sodium intake from foods was also good. Since this source provides the major contribution to total intake, such a prediction is obviously important. Weighting individual food items according to estimates of sodium content and average portion sizes for males and females offers an improvement on the system used by Pietinen et ale (1982), where a small number of food items were used and weighted equally. Although the present questionnaire might be improved if estimates of portion sizes were made by individual subjects, this would be difficult to incorporate in the questionnaire in its present form. It could be done by the use of model foods which would then require an interviewer to administer the questionnaire, rather than selfadministration, and would become a more time-consuming exercise. Estimation of total intake calculated from the different sources proved relatively successful (r = 0·66). This would therefore be useful in trying to differentiate subjects into groups on the basis of their intake. One of the factors limiting the correlations reported is the test-retest reliabilities of both the questionnaire and the criterion variables. Taking these into account gives an indication of the underlying relationship between the variables if both had been measured with perfect reliability; this was found to be r = 0·84. This approach of assessing the frequency of consumption of specific foods which are large contributors to salt intake, along with obtaining quantified estimates of table and cooking salt use, offers an improvement on previous attempts to estimate intake by questionnaire.
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Hence the questionnaire described provides a quick and simple estimate of a subjects' intake of salt, taking only about 10 min to complete. It gave a better estimate of total intake (estimated by 7-day urine sodium) than a single 24-h urine collection. Although it would not give as good an estimate as collection of several complete urine samples, it has the advantage of being simple for subjects to complete and requires none of the commitment necessary to take part in extended urine collection. One problem with validating the questionnaire against urine sodium and measured table and cooking salt use is that taking part in these measurements may influence the intake of the individual (see discussion in Stockley, 1985). Thus these measures may not reflect habitual intake. It may be that a questionnaire on intake is less reactive than these measures, but then there is the need to validate the questionnaire against some criterion. This problem is difficult to resolve, given the impossibility generally of weighing the amount of salt used by an individual without their being aware of this process. Thus, even if estimation of intake by questionnaire is less affected by changes from the habitual diet, it is difficult to demonstrate this if the criterion measures used are affected. There would be problems in using the present questionnaire with subjects not having a normal British diet, e.g. ethnic groups, but the same format and approach could be used. If the foods consumed differed greatly, it would be necessary to include those foods which would be major contributors to salt intake for the target group and then to validate the new form of the questionnaire with this group. Likewise, variations in salting habits in cooking and at the table would modify the regression equations, but the same basic method of assessment could be used in these cases. Further work using modifications of this questionnaire with subjects not connected with research on food has shown generally good agreement with the present results (Shepherd & Farleigh, Note 2). It should be emphasized, however, that the validation presented here is on a limited and specific groups of subjects and the equations presented may not generalize to other groups. Use with substantially differing groups of subjects would require further validation.
REFERENCE NOTES
1. Nelson, M. A dietary survey method for measuring family food purchases and individual nutrient intakes concurrently, and its use in dietary surveillance. Unpublished PhD Thesis, University of London, 1983. 2. Shepherd, R. & Farleigh, C. A. Salt intake assessment by questionnaire and urinary sodium excretion. 1985, in preparation. REFERENCES
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Received 20 July 1984, revisions 24 January 1985 and 30 May 1985