1-validation of a semi-quantitative adolescent food freq quest

ORIGINAL COMMUNICATION

Validation of a semi-quantitative adolescent foodfrequency questionnaire applied at a public schoolin Sao Paulo, Brazil

B Slater1*, ST Philippi1, RM Fisberg1 and MRDO Latorre2

1Department of Nutrition, School of Public Health, University of Sao Paulo, Sao Paulo, Brazil; and 2Department of Epidemiology,School of Public Health, University of Sao Paulo, Sao Paulo, Brazil

Objective: To develop a food frequency questionnaire for adolescents (AFFQ) and demonstrate its relative validity.Design: The final version of the AFFQ was composed of 76 food items previously identified according to their contribution innutrients and overall importance within the eating habits of this population group. The validation study, which was undertakenduring a 6 month period (June to November 1999), was administered to a sample of 79 who answered at least three 24 h dietaryrecalls (R24 h) applied at intervals of 45 days and one AFFQ at the end of the study. Applying the paired t-test and calculatingPearson correlation coefficients on nutrient data, differences in the mean of nutrients were obtained. Correlation coefficientsbetween the mean energy-adjusted nutrients computed by the two methods were calculated, and correction was made forwithin-person variability. Agreement was evaluated by distribution of the adolescents according to quartiles of consumption.Locus: A public school within the metropolitan region of Sao Paulo city.Results: A high variability in the dietary intake of adolescents was observed, with high rates of variability for cholesterol, retinaland vitamin C. The Pearson correlation coefficients, after being adjusted and corrected for variability, ranged from 0.10 to 0.72among females and from 0.16 and 0.91 among males. The mean correlation coefficient for the entire group was 0.52.Conclusions: These results indicate that the AFFQ provides a potentially reliable scale for categorizing individuals by level of pastintake of most nutrients, excluding retinol and iron.European Journal of Clinical Nutrition (2003) 57, 629 – 635. doi:10.1038=sj.ejcn.1601588

Keywords: nutritional assessment; food frequency questionnaire; adolescents

IntroductionIn the last few years, evidence has emerged concerning the

possible relations between diets of children and adolescents

and chronic diseases in adult life (Ludwig et al, 2001).

Adolescent eating habits are highly influenced by family

patterns, habits and the peer group, and by the growing

concern with body image. Habits such as skipping a meal

(particularly breakfast), consuming high-energy foods which

are poor in nutrients and the tendency, among girls, to make

dietetic restrictions are part of the repertoire of Brazilian

adolescents’ eating behavior (Fisberg et al, 2000).

Since longitudinal studies that evaluate adolescent food

intake are non-existent in Brazil, we have relied solely on

cross-sectional studies that make use of dietary records or

24 h recalls. These methods are accepted conceptually as

means of providing valid information about present diet

(Thompson & Byers, 1994), however an important

limitation is that a single day of application does not repre-

sent habitual diet.

Food frequency questionnaires (FFQ) are widely accepted

in epidemiological studies which associate diet with

chronic diseases for two reasons: first because they substi-

tute the measurement of one or several days of food intake

for global information on a wider period of time and,

*Correspondence: B Slater, Departamento de Nutricao da Faculdade de

Saude Publica=USP, Av. Dr Arnaldo, 715-CEP: 01246-904, Cerqueira Cesar,

Sao Paulo, SP, Brazil.

E-mail: [email protected]

Guarantor: B. Slater

Contributors: BS responsible for research design, conduction of the

study and for the writing the document. STP was the advisor of

the study. RMF collaborated in the interpretation and discussion

of the study’s results. MRDOLT collaborated in the statistical

analyses and interpretation of the results.

Received 27 February 2002; revised 1 July 2002;

accepted 2 July 2002

European Journal of Clinical Nutrition (2003) 57, 629–635� 2003 Nature Publishing Group All rights reserved 0954–3007/03 $25.00

www.nature.com/ejcn

European Journal of Clinical Nutrition (2003) 57, 629–635� 2003 Nature Publishing Group All rights reserved 0954–3007/03 $25.00

www.nature.com/ejcn

second, because they are relatively inexpensive when self-

administered (Jimenez & Martın-Moreno, 1995; Ocke et al,

1997). The literature indicates that studies which utilize

FFQs in order to evaluate children’s and adolescent’s food

intake are scarce. There is, therefore, a need to develop new

instruments which can be easily administered to large

groups and which are simple so they can be self-administered

and which will be able to evaluate habitual diet among

adolescents.

The main objective of this study was to develop a food

frequency questionnaire for adolescents, AFFQ , and evaluate

the relative validity of the estimates of energy, macronutri-

ents, retinal, cholesterol, dietary fiber, vitamin A, calcium

and iron consumption.

MethodsDevelopment of the AFFQ structure

Data concerning food habits registered in a study on nutri-

tional evaluation conducted by Nuzzo (1998) was utilized in

the elaboration of the AFFQ list of foods. The information

regarding diet in the former study corresponds to the appli-

cation of 2 days of the dietary record method in 200 adoles-

cents of both sexes. The foods were grouped together

according to their physical characteristics and nutritive

value in 140 food items. Based upon this grouping, the

foods that made a greater contribution, both energetically

and in terms of their nutrients, were identified (Block et al,

1985a,b).

Having defined a food list, the AFFQ was tested in a pilot

study, in which 76 food items were included. This question-

naire evaluated the quantity of foods and nutrients con-

sumed during the preceding 6 month period. The frequency

of consumption was evaluated by means of simple questions

and closed answers in which different time units were

established. The seven categories of responses for each food

item were: never, less than once a month, 1 – 3 times a

month, once a week, 2 – 4 times a week, once daily, and

twice daily or more (see Figure 1).

The size of the portions of food express mean intake in

grams for each food item except for 10 items which pre-

sented differences in intake between males and females

participating in the study. For these items, the median

value of side portion of food was utilized.

Validation study

Description of the population and of the design of the

validation study. The validation study was conducted

between June and December 1999, the period during

which data were collected. The population study consisted

of 106 adolescent volunteers of both sexes, aged 14 – 18 y and

11 months, registered in the first year of a junior high school

located in the western region of Sao Paulo city. The relative

validity of the study was evaluated by comparing the stan-

dard measure with the data collected by the AFFQ. During

this period the students completed three 24 h dietary recalls

administered on nonconsecutive days including one day

during a weekend, with 45 day intervals between them and

one AFFQ applied at the end of the period.

Data processing

Once the data was collected, the food intake registered by

the 24 h dietary recall and the AFFQ were converted into

energy and nutrients by the Virtual Nutri program (Philippi

et al, 1996).

Figure 1 Format of the adolescent food frequency questionnaire.

Validation of semi-quantitative adolescent FFQB Slater et al

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European Journal of Clinical Nutrition

Statistical analysis

The differences in mean consumption of energy and nutri-

ents obtained by the AFFQ and by the 24 h dietary recalls

were analyzed using paired t-test. The correlation coeffi-

cient (r), which compared the energy and nutrient values

obtained by both methods, was calculated before and after

adjustment for total energy intake (Willett & Stampfer,

1986).

Within-person variance (ie day-to-day variation in diet)

estimated in the recalls could attenuate correlations between

the AFFQ and the 24 h recalls, due to the relatively low

number of replicates. In order to obtain a measure of validity,

the correlation coefficient was multiplied by factor

(1þ (sw2 =sb

2)n)0.5) where n represents the number of replicate

measurements, sw2 is the within-person variation and sb

2 is

the between person variation. The result thus obtained is the

de-attenuated correlation coefficient (Willet, 1998). To eva-

luate the agreement of classification according to the levels

of nutrient intake between the AFFQ and the 24 h-dietary

recall, we compared the quartile classification obtained by

both methods. The cut-off point was determined separately

for the questionnaire and for the mean of the three 24 h

dietary recalls. In this way, agreement and disagreement

between categories were evaluated by the total proportion

of participants correctly classified in the same quartile and in

opposite quartiles.

ResultsWithin the study period, from June to November 1999, 79 of

the 106 students completed three 24 h dietary recalls and the

AFFQ. Among the students who participated in this study,

50.6% were female and 49.4% were males. The average age

was 15.8 y (s.d.¼1.09).

No statistically significant differences were found between

the mean values estimated by the three 24 h recalls and the

AFFQ for energy intake, total fat, vitamin C and calcium. On

the other hand, the AFFQ overestimated the values of carbo-

hydrates and fiber and underestimated those of proteins,

cholesterol, unsaturated fat and iron (Table 1). Upon

Table 1 Mean, standard deviation and median daily intake assessed by three 24 h recall and AFFQa among 79 adolescentsattending public high school in Sao Paulo, Brazil

24 h recall AFFQ Median

Nutrients Mean s.d. Mean s.d. 24 h recall AFFQ Pb

Energy (kcal) 2004.87 728.76 2023.59 563.36 1927.28 1920.47 0.560

Female 1731.94 572.58 1763.71 451.10 1686.84 1681.79 0.407

Males 2284.79 766.87 2290.11 546.46 2125.93 2270.48 0.919

Total proteın (g) 79.52 34.83 69.14 20.04 77.29 65.34 0.001

Female 66.12 28.10 62.27 17.95 62.48 63.27 0.213

Males 93.27 35.80 76.18 19.83 86.61 74.39 0.001

Total carbohydrates (g) 242.18 90.23 265.40 75.96 222.78 264.94 0.001

Female 210.89 78.22 226.82 61.96 206.77 218.90 0.029

Males 274.29 90.73 304.97 68.76 253.05 318.34 0.001

Total fat (g) 78.63 39.02 76.60 24.83 74.72 72.28 0.370

Female 67.87 30.60 68.52 19.96 62.91 66.68 0.826

Males 89.65 43.53 84.90 26.78 82.25 79.91 0.167

Polyunsaturated fat (g) 31.63 20.79 25.74 9.54 28.49 24.87 0.001

Female 26.08 16.41 22.93 7.82 23.92 22.32 0.061

Males 37.33 23.21 28.62 10.35 36.21 28.00 0.001

Dietary fiber (g) 10.56 6.32 11.70 4.40 9.95 10.90 0.012

Female 7.87 4.82 10.31 4.08 7.11 9.86 0.001

Males 13.31 6.50 13.13 4.30 12.26 12.47 0.787

Cholesterol (mg) 239.70 153.50 204.56 83.38 222.74 198.16 0.003

Female 204.60 138.75 182.98 89.30 182.11 175.34 0.197

Males 275.70 160.02 226.70 71.35 249.78 221.99 0.003

Retinal (mg ER) 745.64 831.98 614.94 243.50 612.66 581.04 0.048

Female 608.28 830.23 596.55 272.89 547.53 511.91 0.895

Males 886.52 813.39 633.80 211.06 695.74 611.98 0.010

Vitamin C (mg) 69.83 86.59 79.91 41.62 55.33 74.35 0.103

Female 64.28 81.43 69.84 33.43 44.23 61.82 0.526

Males 75.52 91.58 90.24 46.83 57.69 81.44 0.096

Calcium (mg) 584.88 384.17 561.40 223.49 577.55 569.07 0.386

Female 481.30 301.13 507.00 232.67 421.44 471.23 0.387

Males 691.12 429.83 617.20 201.63 622.18 597.04 0.105

Iron (mg) 11.73 5.62 8.43 2.49 11.04 8.63 0.001

Female 9.09 4.18 8.44 2.49 8.84 7.89 0.209

Males 14.45 5.62 10.15 2.79 13.45 9.39 0.001

aAFFQ, adolescent food frequency questionnaire.

bPaired student’s t-test (P<0.05).


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examining the 11 dietetic variables, it was found that only

two of them presented different mean intakes among the

female participants of this study, being the overestimation of

dietetic fiber in approximately 30% (P>0.001) the most

relevant difference found. Among the male participants,

five nutrients presented different mean intakes, these were:

protein, carbohydrate, dietetic fiber, unsaturated fat, choles-

terol and iron (P<0.05).

The ratio of the components of within-person and

between-person variability which ranged from 1 to 2 for

energy, protein, carbohydrates, dietetic fiber and iron for

all individuals and which was greater than 2 for the rest of

the nutrients studied, being that patterns of within-person

variability were more pronounced among the adolescent

boys than among the adolescent girls. However, retinol was

an exception for the pattern of within-person variability

being, in this case, more pronounced among the girls. The

ratios for cholesterol and vitamin C among the adolescent

boys caught our attention, as they were extremely high

(Table 2).

The unadjusted values were loge transformed since the

observed distribution was asymmetric for all nutrients stu-

died. Analysis of the correlation between the values of the

nutrients estimated by the AFFQ and those estimated by the

average of the three 24 h recalls demonstrated a high correla-

tion for energy (r¼0.87) and reasonable correlations for

macro and micronutrients (r¼0.42 – 0.77). Retinal was the

only exception, presenting a low correlation, r¼0.28

(Table 3).

All the values of the correlation coefficients tended to

decrease after being adjusted for energy. The adjusted values

were 50% lower than the unadjusted values, however, when

adjusted, the correlation coefficients of cholesterol, retinol

and iron were no longer significant. The correlations ranged

from 70.07 to 0.49 for the adolescent girls and from 0.11 to

0.62 for the adolescent boys.

Adjustment for within-person variability increased all

values of the correlation coefficients. Whereas the unad-

justed value for retinal was r¼0.06, the adjusted value was

r¼ 0.10 and, as for fiber, the unadjusted value was r¼0.54

Table 2 Variance components of the nutrient intakes estimated by three 24 h recalls among 79adolescents attending public high school in Sao Paulo, Brazil

24 h dietary recalls

Nutrients Variance ratiosa

Within-person variance Between-person variance

Energy (kcal) 1.4 311 761.95 221 210.21

Female 1.3 189 326.37 140 889.1

Males 2.9 437 336.91 153 400.34

Total protein (g) 1.7 772.93 444.05

Female 2.1 533.38 260.64

Males 3.8 1018.64 267.79

Total carbohydrates (g) 1.2 4383.26 3790.12

Female 1.4 3542.82 2619.84

Males 1.7 5245.24 3040.60

Total fat (g) 2.5 1090.01 426.41

Female 2.5 673.40 267.95

Males 4.1 1517.30 383.97

Polyunsaturated fat (g) 2.5 310.55 122.78

Female 2.9 200.58 69.91

Males 3.6 423.33 117.36

Dietary fiber (g) 1.6 24.74 15.33

Female 2.6 16.91 6.52

Males 3.4 32.77 9.60

Cholesterol (mg) 5.9 20 186.06 3411.42

Female 7.6 17 056.30 2232.16

Males 10.4 23 396.08 225 013

Retinal (mg ER) 4.7 571 837.34 121 374.90

Female 26.4 664 563.15 25 135.21

Males 2.5 476 333.94 88 109.09

Vitamin C (mg) 8.2 6687.93 816.73

Female 5.1 5554.74 1094.60

Males 14.35 7850.17 546.97

Calcium (mg) 2.7 107 741.82 40 183.66

Female 3.2 69 433.99 21 610.00

Males 3.8 147 031.90 38 379.83

Iron (mg) 1.4 18.51 13.17

Female 2.4 12.37 5.21

Males 3.6 24.80 6.95

al¼ Sw2=Sb

2.


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and the adjusted value was 0.67. Relatively high values

were also observed for fiber and vitamin C among the

adolescent boys.

Table 4 demonstrates that, on average, 33% of the

individuals were classified in the same quartile and 5%

were misclassified. The proportion of individuals classified

in the lowest quartile both by the 24 h recalls and the AFFQ

appear in the first column of the same table. This propor-

tion ranged form 16% for iron to 63% for calcium. Agree-

ment within this category for the different nutrients

averaged 37%.

DiscussionThe AFFQ was judiciously designed following the recom-

mendations of Block et al, (1985a,b), Willett (1998), and

Nelson (1997) for determining a list of foods and portions

sizes according to gender and coherent with dietary patterns

and eating habits of the population group which was the

object of this study.

Comparing the AFFQ with the 24 h dietary recalls, similar

values for energy, carbohydrates, total fat and calcium intake

were observed, suggesting a high consistency in estimating

these nutrients. However there was a significant difference

Table 3 Pearson correlation coefficients between daily intake of energy and nutrients assessed by three 24 h recalls and AFFQa among 79adolescents attending public high school in Sao Paulo, Brazil

Correlation coefficients

Non-adjusted b r Energy-adjusted r De-attenuatedc r

Nutrients Total Female Male Total Female Male Total Female Male

Energy (kcal) 0.87** 0.86** 0.82** — — —

Total protein (g) 0.63** 0.47** 0.66** 0.31** 0.17 0.21 0.38 0.22 0.32

Total carbohydrates (g) 0.77** 0.70** 0.71** 0.58** 0.12 0.43** 0.68 0.15 0.53

Total fat (g) 0.72** 0.68** 0.69** 0.40** 70.07 0.33* 0.54 70.10 0.51

Polyunsaturated fat (g) 0.57** 0.46** 0.60** 0.35** 0.26 0.37* 0.48 0.36 0.55

Dietary fiber (g) 0.59** 0.48** 0.56** 0.56** 0.48** 0.62** 0.69 0.66 0.91

Cholesterol (mg) 0.44** 0.33* 0.44** 0.26 0.20 0.30 0.52 0.37 0.64

Retinol (mg ER) 0.28* 0.18 0.39* 0.06 0.01 0.18 0.10 0.03 0.24

Vitamin C (mg) 0.42** 0.27 0.56** 0.47** 0.37 0.56** 0.91 0.61 —

Calcium (mg) 0.61** 0.60** 0.50** 0.51** 0.50** 0.46** 0.70 0.72 0.69

Iron (mg) 0.46** 0.30 0.43** 0.17 0.10 0.11 0.22 0.13 0.16

Mean 0.57 0.48 0.58 0.37 0.23 0.36 0.52 0.34 0.51

aAFFQ, adolescent food frequency questionnaire.bNutrient values were transformed (loge) to improve normality.cThe de-attenuated correlation coefficients was calculated using the ratio of the within- to between-person variability measured from three 24 h dietary

recalls. The formula used was: rc¼ ro(1 þ (sw2= sb

2)n)

0.5.

*P< 0.05; **P< 0.01.

Table 4 Cross-classification of nutrient distribution quartiles from 24 h recalls and AFFQa calculated from energy-adjusted nutrient intake (exceptfor total calories), Sao Paulo, Brazil

Lowest quartile 24 h recall Highest quartile 24 h recall Overall

Nutrients

Lowest quartile

AFFQ (%)

Highest quartile

AFFQ (%)

Highest quartile

AFFQ (%)

Lowest quartile

AFFQ (%)

Exact

agreement (%)

Opposite

(%)

Total protein (g) 26 16 30 20 30 9

Total carbohydrates (g) 42 11 45 10 35 5

Total fat (g) 32 16 25 10 28 6

Polyunsaturated fat (g) 37 5 30 20 29 6

Dietary fiber (g) 47 0 45 5 39 1

Cholesterol (mg) 26 16 30 5 23 5

Retinal (mg ER) 32 21 30 10 25 8

Vitamin C (mg) 47 0 55 5 43 1

Calcium (mg) 63 11 55 10 56 5

Iron (mg) 16 10 25 20 20 8

Mean 37 11 37 12 33 5

aAFFQ, adolescent food frequency questionnaire.


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for the seven remaining nutrients (protein, polyunsaturated

fat, dietary fiber, cholesterol, retinal, vitamin C and iron).

The results of this validation study explain why there is

such considerable variability in the daily consumption calcu-

lated by means of the 24 h recalls. Our results are similar to

those of Beaton et al (1983), Sempos et al (1985) and Field et al

(1999), although only the latter was administered to children.

Patterns of within-person variability derive primarily from

individual’s social behavior, although other factors are also

responsible. Harbottle and Duggan (1994), Tsubono et al

(1998) and Friis et al (1997) suggest that nutrients which

are part of the daily diet, that is, which are consumed on a

regular basis (eg macronutrient intake) have smaller variance

ratios (l) than those nutrients with a high within-person

variability, as in the of retinol, vitamin C and cholesterol in

the present study.

Considering the unadjusted correlation, higher values

(mean r¼0.57) were observed compared with studies con-

ducted by Rockett et al (1997), r¼39, and Field et al (1999),

r¼0.28.

The fact that the correlation diminished considerably

after adjustment for total energy intake led us to search for

possible answers. According to Willet (1998), this procedure

increases the correlation coefficient when variability of

nutrient consumption is related to energy intake, but

decreases when variability of the nutrient depends on sys-

tematic errors of overestimation and underestimation. In

studies focusing on adults by Willett et al (1985), Overvad

et al (1991) and Rimm et al (1992), this procedure confers

more relevant r values. In studies conducted in Greece, by

Gnardellis et al (1994) and in the USA by Munger et al (1992),

the two effects (increasing and decreasing the correlation)

happen simultaneously for the different nutrients analyzed.

On the other hand, in the study conducted by Martın-

Moreno et al (1993), in Spain, the effect is particularly

insignificant.

Although the 24 h recall is conceptually different from the

AFFQ , both methods have a common characteristic, namely,

they share some of the same sources of errors such as the sub

under- or overestimation of the quantities of foods con-

sumed due to memory flaws. In this sense, artificially high

correlations, as is the case with energy (female, r¼0.87;

male, r¼0.82), may be explained.

Given a situation in which all elements of the diet are

informed proportionally, we can presume that energy adjust-

ment may compensate for errors in general information. The

modest correction using the strategy of energy adjustment in

Flegal and Laarkin’s study, and the correlation coefficient

decrease in this study, led us to question the validity of this

statement. We may suppose that the subject in this study did

not report the nutrients in a similar way when answering

both instruments. Therefore, although energy adjustment

has made it possible to remove general and common differ-

ences between the methods, it did not permit differences

resulting from disproportional information to be removed

(Flegal & Laarkin, 1990; Flegal, 1999).

Other aspects to be considered in dietetic studies carried

out among children and adolescents are the additional

difficulties related to cognitive skills in registering and recal-

ling what food they have eaten (Rockett & Colditz, 1997).

Subjective aspects must also be taken into consideration: the

perception and quantification of the portion size and the

social value associated with some foods. According to Goran

(1998), children and adolescents tend to have better recall of

the preferred foods, informing that they have consumed

large portions. However, they tend to forget or underesti-

mate those items which they do not like.

The values of energy-adjusted correlation coefficients

were corrected afterwards by variance. After this procedure,

more precise estimates were obtained for all nutrients,

mainly for fiber, vitamin C and calcium, for which there

were very good correlations. The increased values may be

attributed to elevated within-person variability observed,

particularly for retinol among the adolescent girls and vita-

min C among the adolescent boys.

One of the arguments for adopting the cross-classification

procedure is that correlation coefficients do not capture

differential under- and over-reporting. The extent of such

biases, however, are difficult to address or quantify (Friis et al,

1997). This form of presentation of the data provides com-

pact information concerning the capacity of both methods

to allocate individuals according to dietary intake distribu-

tion, being considered, in this sense, more adequate than the

correlation coefficient, which merely produces information

concerning the possible relations between the variables esti-

mated by both methods.

A recent study by Cardoso et al (2001) among women

of Japanese ancestry living in Brazil showed similar propor-

tion of subjects in the same quartile (exact agreement

mean¼36%) and the extreme opposite quartile (4%). Nutri-

ents such as protein, retinal and iron, displayed the highest

percentages of disagreements between the two methods in

the present study (9 and 8%, respectively), even 3 days of

24 h dietary recalls were insufficient to measure accurately

the habitual diet of this group of adolescents.

This fact illustrates an important component of variation

within the diet, particularly for this group of adolescents

where high rates of within-person variance were also

observed. This study demonstrated the questionnaire’s capa-

city to classify individuals according to their past intake of the

nutrients studied, excepting of retinol and iron. The AFFQ did

not perform as well for the females as it did for the males in

adequately classifying individuals according to their total fat

and protein intake. The procedure of energy adjustment, as

well as correction by within-person variance, allowed us to

obtain more precise estimates of the validity coefficient.

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