reliability and relative validity of a quantitative food-frequency questionnaire for use among...

Reliability and relative validity of a quantitativefood-frequency questionnaire for use among adultsin Italian population

GIOVANNA TURCONI, ROSELLA BAZZANO, CARLA ROGGI &

HELLAS CENA

Department of Applied Health Sciences, Section of Human Nutrition and Dietetics,

Faculty of Medicine, University of Pavia, Italy

Abstract

Our objective was to assess the reliability and relative validity of a food frequency questionnaire(FFQ) among adult people. In a cross-sectional study carried out in northern Italy, 112 adultswere recruited. A total of 189 food and drink items were selected according to those typicallyconsumed by Italians. FFQ reliability was assessed by two repeated administrations at 6 weeks.The FFQ was validated using four 24-h recalls repeated in the same period of time. For thevalidation study, classification into quartiles from the two methods and Bland–Altman plot werealso performed. The reliability study showed a good correlation between the two methods.Bland–Altman plots showed that the two methods are very likely to agree for individual energyand macronutrient intakes. The reliability and relative validity of this FFQ was good, supportingits use in assessing dietary intakes of Italians in nutritional surveillance programs and inepidemiological dietary surveys.

Keywords: Reliability, validity, quantitative FFQ, 24-h recall, interviewer administration,

Italian adults

Introduction

Food-frequency questionnaires (FFQs) have become widely used tools for measuring

usual consumption of energy and nutrient intakes in surveillance studies and

epidemiological surveys (Decarli et al. 1996, Bingham et al. 1997, Ocke et al. 1997a,

1997b, Bohlscheid-Thomas et al. 1997a, 1997b, Boeing et al. 1997, Kaaks et al. 1997,

Kroke et al. 1999, Johansson et al. 2001, Ogawa et al. 2003, Bingham 1997, Jackson

et al. 2001, Erkkola et al. 2001, Rodriguez et al. 2002, Kumanyika et al. 2003), namely

for assessing the relationship between habitual diet and diseases. Indeed, elucidation of

diet–disease relationships requires dietary assessment methods that adequately

describe and quantify intakes, minimize systematic errors and provide reasonably

precise estimates of variability between individuals and/or groups (Jackson et al. 2001).

Some investigations (Cade et al. 2002) show that this instrument provides equally

ISSN 0963-7486 print/ISSN 1465-3478 online q 2010 Informa UK, Ltd.

DOI: 10.3109/09637486.2010.495329

Correspondence: Giovanna Turconi, Department of Applied Health Sciences, Section of Human Nutrition and Dietetics,

Faculty of Medicine, University of Pavia, Via Bassi 21, I-27100 Pavia, Italy. Tel: 39 0382 987544. Fax: 39 0382 987570.

E-mail: [email protected]

International Journal of Food Sciences and Nutrition,

December 2010; 61(8): 846–862

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accurate estimates of both group and individual intakes, and it is considered

appropriate for categorizing persons accurately according to levels of consumption as

well as identifying subjects at the extremes of intake (Erkkola et al. 2001, Jackson et al.

2001). The theory underlying FFQs relates to dietary consumption investigation for a

certain period, longer than that referred to using dietary recalls or dietary records,

therefore avoiding collecting data for many days. Twenty four-hour recalls and dietary

records seem to estimate more accurately the individual intakes in a short period of

time, and thus they investigate the current intakes, not the habitual ones. In addition,

more days of data collection are required due to the variability within a person

(Willet 1998). On the other hand, FFQs are used for the assessment of dietary

consumption over long-term periods, generally for 12 months.

Widespread use of FFQs was ascribed also to its relative ease of administration,

coding and analysis, leading to lower collecting and data processing costs when

compared with other methods of dietary assessment (Jackson et al. 2001, Cade et al.

2002). In addition, they impose less burden on subjects than most other dietary

assessment methods.

Typically, the respondent is presented with a list of foods and is required to report

how often each food is eaten in broad terms, such as x times per day, per week, or per

month (Margetts and Nelson 1997). Foods lists are usually constructed to reflect

region-specific, cultural dietary habits, and food most commonly consumed for the

nutrients of interest.

Like any other type of dietary intake measurements, FFQs suffer from systematic

and random errors (Johansson et al. 2001). For example, it may be difficult for

respondent to recall frequencies of intake over a given period of time. Since such errors

generally cause bias in relative risk assessment, it is crucial to evaluate the reliability and

relative validity of the instrument, so as to enhance the interpretation of estimated

diet–disease associations and to improve the translation of such associations into

dietary recommendations.

Reliability is the degree to which a method provides similar results for different

occasions (Lee-han et al. 1989); an instrument is reliable if individual measurements

obtained on different occasions, or carried out by different interviewers, produce the

same results. Validity is defined as the determination of how well a method measures

what it is intended to measure.

Unfortunately, there is no ‘ideal method’ for dietary intake measurements, nor there

is any ‘gold standard’ for directly assessing the validity of FFQs (Cade et al. 2002). As a

result, most investigators report relative validity; that is, comparing the FFQ with

another analogous, although not necessarily more accurate, assessment method

(Willet 1998). FFQs are often validated against 24-h recalls (Munger et al. 1992,

Bohlscheid-Thomas et al. 1997b, Boeing et al. 1997, Voss et al. 1998, Johansson et al.

2001, Rodriguez et al. 2002, Fornes et al. 2003, Kumanyika et al. 2003, Tseng and

Hernandez 2005, Block et al. 2006) or dietary records (Cade et al. 2002, Kelemen et al.

2003, Kumanyika et al. 2003, Ogawa et al. 2003, Sasaki et al. 2003, Chen et al. 2004,

Khani et al. 2004, Xu et al. 2004, Bautista et al. 2005, Date et al. 2005, Ke et al. 2005,

Nath and Huffman 2005, Shatenstein et al. 2005, Lee et al. 2006, Ahn et al. 2007).

When used as reference methods, 24-h recalls or dietary records must be repeated

more times to represent average intake and over a period of time. Twenty-four-hour

recalls are less demanding than diet recording, and do not influence the current diet

nor require literacy of the participants. Their sources of error tend to be more

Reliability and relative validity of a FFQ 847

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correlated with the error in a dietary questionnaire (i.e. reliance upon memory,

conceptualization of portion sizes and distortion of reported diet) (Cade et al. 2002).

If cooperation or literacy of the subjects is limited, 24-h recalls may be more

appropriate than dietary records (Cade et al. 2002).

In the present study we developed a FFQ for the Italian adults, hypothesizing it as a

tool for assessing the habitual diet in nutritional surveillance programs and

epidemiological surveys. The objective of the present study was to evaluate the

reliability of this FFQ for energy, alcohol and macronutrient intakes and its relative

validity of the estimates of total energy, protein, fat, carbohydrates, alcohol, vitamin C,

retinol, iron, zinc and calcium consumption.

Methods and materials

Development of the FFQ

The FFQ was developed providing a list of common foods and beverages chosen

among those commonly consumed by the adult Italian population identified from the

INRAN-SCAI 2005–2006 food consumption survey (Leclerq et al. 2009), the most

recent Italian National Survey, considering age and gender. Italian recipe books were

consulted to determine typical ingredients used in mixed dishes. Subsequently

standard recipes were developed to estimate the nutrient composition of these varied

dishes.

If fruit and vegetable consumption differed between season, the frequency in the

season in which they were consumed within a year was asked.

The foods have been then grouped into 10 categories according to their similarity in

relevant nutrients and their customary use; the final list of foods is reported in Table I.

The table shows that starch-containing products served as first courses (61 items) are

the most represented in comparison with the other food categories according to the

Italian traditional dietary habits.

Food frequency was evaluated using three categories: daily, weekly and monthly, and

from one to six for number of items (e.g. twice a day, four times a week, five times a

month). The questionnaire was completed by the dietitian filling in the appropriate

boxes with a pen.

The FFQ was pre-tested by a panel of eight dietitians in order to check its

acceptability and comprehension. In its final form, the list consisted of 189 food and

drink items deemed necessary to capture dietary intake for a 1-year period.

Frequency of usual food consumption was asked by inviting the respondents to

report their consumption as ‘never consumed’, or to indicate the ‘number of occasions’

per day, week or month, rather than to be restricted to specific frequency ranges.

Reference standard

As the reference standard, we chose to administer a 24-h recall repeated four times at

2-week intervals from the beginning of the study.

Subjects

The study was conducted among a convenience sample of subjects recruited in a

university cafeteria in Pavia, northern Italy. Information on the study design, purpose

and inclusion criteria was given in the cafeteria in order to recruit the subjects.

848 G. Turconi et al.

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The inclusion criteria were: age 20–60 years, both sexes, in good health, not

undergoing any weight-loss program. One hundred and thirty individuals were

enrolled. All the subjects, volunteers, were: students, staff working at the university,

and other members of the general population, in good health, stable weight as

self-reported. Written informed consent was obtained from all participants prior to

their inclusion in the study, which was performed in accordance with the ethical

standards laid down in the appropriate version of the 1994 Declaration of Helsinki and

approved by the University of Pavia’s Faculty of Medicine Ethical Committee.

Information about education level, residence area and marital status were obtained

by interview.

Study design

The study was carried out between January and July 2006. The FFQ and the 24-h

recall were administered twice, first at the beginning of the study (FFQ1 and 24-h rc1)

and then after 6 weeks (FFQ2 and 24-h rc4). The FFQs and 24-h recall have been

administered on the same day, randomly switching the order such that one-half of the

sample got the FFQ first and the 24-h recall second, and vice versa. Two intermediate

Table I. List of foods included in the FFQ.

First courses (61) Bread (27)

Pasta, not filled (11) Bread (4)

Pasta made with white flour and potatoes (8) Breadsticks and crackers (3)

Rice (10) Breakfast cereals (3)

Filled pasta with meat (9) Sandwiches (12)

Filled pasta with cheese and spinach (9) Salty snacks (5)

Pasta or rice with vegetables and/or legumes (5) Sweet foods (14)

Pizza and focaccia (9) Biscuits (5)

Main courses (37) Cakes and pastries (5)

Beef meat (5) Ice cream (2)

Poultry meat (3) Jam and honey (1)

Pork meat (3) Sugar (1)

Offal (1)* Milk and dairy products (8)

Fish and seafood products (9) Milk (5)

Canned fish and meat (5) Yogurt (3)

Meat products (salami, ham, sausages, etc.) (4) Coffee and tea (2)

Eggs (4) Mineral water, beverages and soft drinks (3)

Fresh cheese (1) Alcoholic drinks (6)

Matured cheese (2) Salad dressing (4)

Vegetables and fruit (29)

Raw vegetables (2)

Cooked vegetables (5)

Mixed salads (5)

Potatoes, boiled and fried (4)

Legumes, fresh and dried (1)

Winter fruit (5)†

Summer fruit (3)‡

Fruit juice (1)

Nuts and dried fruits (1)

Number of items for each food category presented in parentheses. * Veal liver. † Citrus fruits, apple, pear,

banana, kiwi. ‡ Peach, apricot, strawberry.


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24-hour recalls (24-h rc2, 24-h rc3) were conducted at an interval of 2 weeks between

the two FFQs, for a total of four 24-h recall administrations.

Data collection (FFQ and 24-h recall)

Data were collected by interview conducted by trained nutritional personnel

(three dietitians) who had received 18 h of instruction aimed at administering both

the questionnaires in a standardized way (inter-rater reliability) and at assessing

whether repeated administration by the same interviewer yielded the same answers

(intra-rater reliability) (Cade et al. 2002).

Questionnaires may be either interviewer administered or self-administered

according to the needs of the study. We chose to administer the questionnaire by

interview to avoid problems that may rise with self-administration, such as incomplete

responses, despite the same interviewer administering both instruments (FFQ and

24-h recall) can bias the participant’s recall.

All of the interviews were performed at the University Department of Human

Nutrition and Dietetics where the subjects were invited to present by appointment.

Additional questions, concerning individual fat intake pattern, were used to adjust the

composition of various recipes.

The 24-h recalls were conducted with the help of a ‘quick list’ of foods that the

interviewer listed to the respondents in order to improve their memory in recalling food

consumption. The quick list was generated taking into account the food items

commonly consumed by Italian adults during main meals and snacks and reported in

the FFQ.

Portion sizes were quantified with a color food photography atlas (Turconi and Roggi

2007) that has been previously validated (Turconi et al. 2005). For all 189 foods, three

portion sizes (small ¼ B, medium ¼ D and large ¼ F) are displayed. The respondent

was asked to quantify food and beverage items for both the FFQ and 24-h recall using

this tool. If a food was reported in the 24-h recall that was not a part of the atlas, or if

the size was not appropriate for the amount consumed, the respondent was asked to

select a virtual portion size (extra small ¼ A, small–medium ¼ C, medium–large ¼ E

and extra large ¼ G). In this way, each subject could choose among seven portion sizes

(three depicted and four virtual). All the 189 foods and beverages listed in the FFQ are

depicted in the photography atlas, which includes 434 food and beverage items of the

Italian diet.

At the end of the first interview, the dietitian gave the subjects the list of the

subsequent appointments for interviewing, instructing them not to change their food

habits and consumption in the subsequent period until the end of the study.

Data analyses

Food consumption data from the FFQs and the 24-h recalls were analyzed for energy,

alcohol, macronutrient and a few micronutrient intakes using a pre-existent computer

program including the Italian Food Composition Tables published by the European

Institute of Oncology (Salvini et al. 1998) as the nutritional database, as well as the

photographs of the food atlas in the different portion sizes, coded in relation to their

energy and nutrient contents (the four virtual portions were also included).

Daily energy, alcohol and nutrient intakes from FFQs were computed for each

subject; they were calculated by multiplying the frequency of consumption by the


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nutrient composition specified for each food item and its portion size, and by dividing

by 7, 31 and 365 for week, month and year frequency, respectively, in order to compute

daily consumption. Energy, alcohol and nutrient content from all foods and beverages

were summed to obtain a total nutrient daily intake for each subject.

Data from each FFQ were used for studying reliability, while the mean of the two

FFQs were used for studying relative validity. Energy and nutrient intakes were

computed for each 24-h recall and the mean of the four recalls were used for the

validation study.

Data were analyzed using the Statistical Package for the Social Sciences version 10

for PC (SPSS Inc., Chicago, IL, USA).

Reliability study. We examined the reliability of the questionnaire by means of two

assessments (FFQ1 and FFQ2) for total energy, alcohol, and macronutrient intakes.

Total energy and all the macronutrients have been selected since they are widely

investigated in most validation studies reported in the literature, while data on alcohol

consumption are very useful in epidemiological research.

Pearson’s correlation coefficients (95% confidence intervals for R, CI) between the

two FFQs resulting from energy, alcohol and macronutrient intakes were used to study

the reliability of the instrument. The coefficients for alcohol and nutrients were also

computed after adjusting for total energy intake. In addition, the paired t-test was used

to compare the mean values of intake derived from the two administrations.

Validity study. Relative validity was evaluated by analyzing the association between the

mean energy, alcohol and nutrient intakes estimated by the two FFQs in agreement

with recent studies (Fornes et al. 2003, Malekshah et al. 2006) and the mean values

obtained from the four 24-h recalls as a reference standard. Calcium and iron have

been chosen because their recommended dietary intake is often unsatisfied, leading to

deficiency of these elements; vitamin C, retinol and zinc have been included as

antioxidants representatives.

Pearson’s correlation coefficients (95% confidence intervals for R, CI) were used to

investigate the correlation between the two instruments. The coefficients for alcohol

and nutrients were also computed after adjusting for total energy intake. Mean dietary

intakes estimated from the two instruments were compared using a paired t-test.

To evaluate the agreement of classification according to the levels of energy, alcohol

and nutrient intakes between the two methods, we categorized the distributions of

dietary intakes into quartiles and then we compared the quartile classifications

obtained by both instruments. In this way, agreements and disagreements between

categories were evaluated by the total proportion of individuals correctly classified

across quartiles.

Finally, we generated a Bland–Altman plot (Bland and Altman 1999) to visually

assess the agreement between the two methods across the range of intakes. It can

determine (Cade et al. 2002) whether there is any systematic difference between the

two different administrations (bias) and to what extent the two administrations agree

(limits of agreements). It also provides a method of assessing whether the difference

between the methods is the same across the range of intakes, and whether the extent of

agreement differs for low intakes compared with high intakes. These may be assessed

by plotting the difference between the methods against the average of the two

administrations. The overall mean difference indicates whether one method tends


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to overestimate or underestimate, and the limits of agreements (mean difference ^1.96

standard deviation) (Bland and Altman 1999) show how well the two administrations

agree.

Results

Subjects

Of the 130 subjects initially recruited, a sample of 112 individuals (52 males and 60

females) from a wide variety of social backgrounds completed all of the questionnaires

(86% of respondents). The mean age of the sample was 39.4 ^ 12.7 years; subjects

characteristics are shown in Table II. Most of them were from urban area and were

married. No weight changes during the whole study period were self-reported by

the subjects.

Questionnaire administration

Completing the FFQ took about 50 min, while answering the 24-h recall took about

20 min. Subjects reported that the FFQ was clear, easy to answer, and a reasonable

length. The color food photography atlas was attractive and appeared to hold the

subjects’ attention.

Reliability study

Intakes of energy, alcohol and nutrients analyzed for both the questionnaires were

normally distributed.

Average daily nutrient intakes measured by the two FFQ administrations were very

similar (all comparisons P $ 0.05, by paired t-test). Pearson’s R values ranged from

0.78 for alcohol to 0.87 for energy, while P was highly significant for all the variables

investigated (P , 0.0001). Adjusting for total energy intake lowered the coefficients

only for proteins and carbohydrates (Table III).

Reliability data for micronutrients have not been reported.

Validity study

Intakes of energy, alcohol and nutrients analyzed for both the questionnaires were

normally distributed.

Average daily nutrient intakes measured by the FFQs were not different from the

intakes assessed by the 24-h recalls (all comparisons P $ 0.05, by paired t-test).

Pearson’s R values ranged from 0.70 for zinc to 0.93 for energy, and associations were

highly significant for all the variables investigated (P , 0.0001). Adjusting for total

energy intake lowered the coefficients for fat, carbohydrates, alcohol and calcium

(Table IV).

The proportion of individuals classified by the FFQ and the 24-h recall into the same

quartile for energy, alcohol and nutrient intakes ranged from 89% for iron to 95% for

carbohydrates. Misclassification to adjacent quartile was rare (2–5%), while the

percentage of subjects grossly misclassified (those classified in the highest quartile by

one method and in the lowest quartile by the other one) was equal to zero.

Figure 1 shows regression lines of Pearson’s correlation for mean FFQ and 24-h

recall for energy and macronutrient intakes, while Figure 2 reports the concordance


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Tab

leII

.C

hara

cter

isti

csof

the

sub

ject

s.

Res

iden

ce

are

a(%

)

Mari

tal

statu

s

(%)

Ed

uca

tion

leve

l(%

)

Age

(yea

rs)

Nu

mb

erof

sub

ject

s(%

)U

rban

Ru

ral

Marr

ied

Sin

gle

Pri

mary

sch

ool

Sec

on

dary

sch

ool

Cu

rren

tly

enro

lled

inu

niv

ersi

tyU

niv

ersi

tygra

du

ate

Male

s

20-4

028

(25.0

)17.9

7.1

7.1

17.9

–9.8

8.9

6.3

41-6

024

(21.4

)17.0

4.5

16.1

5.3

2.7

9.8

–8.9

Fem

ale

s

20-4

035

(31.3

)25.0

6.3

19.6

11.7

–12.6

9.8

8.9

41-6

025

(22.3

)19.6

2.6

18.7

3.6

1.8

11.6

–8.9


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Tab

leII

I.F

FQ

1an

dF

FQ

2co

rrel

ati

on

sto

mea

sure

reliab

ilit

y.

FF

Q1

FF

Q2

Die

tary

inta

ke

Mea

nS

D%

of

ener

gy

inta

ke

Mea

nS

D%

of

ener

gy

inta

ke

Pair

edt-

test

P*

95%

CI

forR

R†

valu

esP

*†

En

ergy

(kca

l)2,1

82

335

2,1

70

357

0.2

1(N

S)

0.8

1–

0.9

10.8

7,

0.0

001

Pro

tein

(g)

73.6

9.2

13.5

72.1

10.6

13.3

0.2

5(N

S)

0.7

6–

0.8

80.8

3,

0.8

0‡

,0.0

001

Fat

(g)

67.1

12.3

27.7

65.8

12.2

27.3

0.1

8(N

S)

0.7

3–

0.8

60.8

1,

0.8

1‡

,0.0

001

Carb

ohyd

rate

s(g

)309.0

37.7

53.1

308.3

38.2

53.3

0.2

3(N

S)

0.7

9–

0.9

00.8

6,

0.8

1‡

,0.0

001

Alc

ohol

(g)

17.8

6.9

5.7

19.0

8.7

6.1

0.2

4(N

S)

0.6

9–

0.8

30.7

8,

0.7

8‡

,0.0

001

*Psi

gn

ifica

nce

.†P

ears

on

’sco

rrel

ati

on

test

.‡A

fter

ad

just

men

tfo

rto

tal

ener

gy

inta

ke.


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Table

IV.

FF

Qan

d24-h

reca

llco

rrel

ati

on

sto

mea

sure

rela

tive

valid

ity.

FF

Q‡

24-h

ou

rre

call{

Die

tary

inta

ke

Mea

nS

D%

of

ener

gy

inta

ke

Mea

nS

D%

of

ener

gy

inta

ke

Pair

edt-

test

P*

95%

CI

forR

R†

valu

esP

*†

En

ergy

(kca

l)2176

322

2156

316

0.2

5(N

S)

0.9

0–

0.9

50.9

3,

0.0

001

Pro

tein

(g)

72.8

8.0

13.4

71.9

8.1

13.3

0.2

3(N

S)

0.6

5–

0.8

20.7

5,

0.7

5§

,0.0

001

Fat

(g)

66.5

11.5

27.5

65.4

9.8

27.3

0.2

1(N

S)

0.8

0–

0.9

00.8

5,

0.8

1§

,0.0

001

Carb

ohyd

rate

s(g

)308.6

36.9

53.2

306.7

39.7

53.4

0.1

4(N

S)

0.7

1–

0.8

50.8

0,

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8§

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Alc

ohol

(g)

18.4

7.1

5.9

18.5

8.3

6.0

0.1

8(N

S)

0.6

5–

0.8

20.7

4,

0.7

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Ret

inol

(mg)

785

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125

–0.1

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S)

0.6

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20.7

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Vit

am

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(mg)

94

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–0.1

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0.8

00.7

4,

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Calc

ium

(mg)

895

187

–882

151

–0.2

2(N

S)

0.6

8–

0.8

00.7

8,

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4§

,0.0

001

Iron

(mg)

15

4–

13

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0.2

6(N

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0.8

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6,

0.7

6§

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Zin

c(m

g)

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93

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between the two methods using Bland–Altman plots. These plots show that the two

methods are very likely to agree for individual energy and macronutrient intakes, since

the range obtained for the 95% limits of agreement was 2269.7 þ 185.0 kcal for

energy, 212.5 þ 10.6 g for protein, 212.9 þ 10.6 g for fat and 242.3 þ 38.5 g

for carbohydrates.

Discussion

Accurate assessment of dietary intakes plays a central role in nutritional studies,

especially when it is aimed at investigating the relationship between diet and diseases.

Therefore, development of an accurate measurement instrument is obviously a critical

step in designing an epidemiological study. Each tool used to evaluate dietary intakes

has some strengths as well as limitations; in addition, all dietary assessments methods

used as standard are subjected to bias (Cade et al. 2002).

We developed a FFQ, consisting of 189 food and drink items, aimed at assessing the

diet of Italian adults. Foods and beverages, typical of the Italian diet and consumed

reasonably often by adults, were included. Although long FFQs may overestimate

dietary intakes, we did not observe such a discrepancy when the results were compared

with those obtained by the 24-h recalls.

Our sample size depended on the statistical methods used to assess reliability and

relative validity as widely suggested by the literature (Cade et al. 2002). A sample size

1000 1500 2000 2500 3000

3000

2800

2600

2400

2200

2000

1800

1600

1400

Energy 24h rc

Ene

rgy

FF

Q

50 60 70 80 90 100

100

95

90

85

80

75

70

65

60

55

Protein 24h rc

Pro

tein

FF

Q

40 50 60 70 80 90 100 110

110

100

90

80

70

60

50

40

Fat 24h rc

Fat

FF

Q

200 250 300 350 400

400

350

300

250

200

CHO 24h rc

CH

O F

FQ

R = 0.93P < 0.0001

R = 0.75P < 0.0001

R = 0.85P < 0.0001

R = 0.80P < 0.0001

Figure 1. Pearson’s correlations for energy, protein, fat and carbohydrate (CHO) intakes assessed by the

mean of four 24-h recalls (24hrc) and the mean of two FFQs.


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of at least 50, and preferably much larger, is indicated as desirable for the Bland–

Altman method. In addition, in our sample, the percentage of respondents was high.

Although they were from a wide variety of social backgrounds, they cannot be

considered representative of the population as a whole, especially for the slightly higher

educational level, but they represent a good cross-section of the Italian adults.

The reliability of the FFQ was quite good; the nutritional data obtained from the two

administrations were very similar, with Pearson’s mean R values being very high and P

highly significant for all the variables investigated. Adjusting for total energy intake

slightly lowered some Pearson’s coefficients that, however, remain quite high.

Our results showed greater agreement between the two FFQs than those obtained by

Johansson et al. (2001) among northern Sweden people, by Ogawa et al. (2003) among

rural Japanese people, by Jackson et al. (2001) among Jamaicans of African origin, by

Fornes et al. (2003) among low-income Brazilian workers, by Tseng and Hernandez

(2005) in a sample of US Chinese women, by Malekshah et al. (2006) among Iranian

people, and by Boucher et al. (2006) in a sample of Canadian women, but they were

quite similar to those obtained by Ocke et al. (1997b) among people in the

Netherlands. Our stronger correlation may probably be due to a relatively short period

of time between the two administrations (6 weeks) compared with the other

1500 2000 2500 3000 3500

300

200

100

0

–100

–200

–300

AVERAGE of Energy 24h rcand Energy FFQ

Ene

rgy

24h

rc –

Ene

rgy

FF

Q

Mean–42.4

–1.96 SD–269.7

+1.96 SD185.0

50 60 70 80 90 100 110

15

10

5

0

–5

–10

–15

–20

AVERAGE of Protein 24h rcand Protein FFQ

Pro

tein

24h

rc

– P

rote

int F

FQ

Mean–1.0

–1.96 SD–12.5

+1.96 SD10.6

40 50 60 70 80 90 100 110

15

10

5

0

–5

–10

–15

AVERAGE of Fat 24h rcand Fat FFQ

Fat

24h

rc–

Fat

FF

Q

Mean–1.2

–1.96 SD–12.9

+1.96 SD10.6

200 250 300 350 400 450

80

60

40

20

0

–20

–40

–60

AVERAGE of CHO 24h rcand CHO FFQ

CH

O 2

4h r

c –C

HO

FF

Q

Mean–1.9

–1.96 SD–42.3

+1.96 SD38.5

Figure 2. Bland–Altman plots comparing energy, protein, fat and carbohydrate (CHO) intakes assessed by

24-h recall (24h rc) and FFQ.


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administrations that took place approximately 1 year apart. This could be considered a

possible limitation of our study.

The relative validity of the questionnaire was quite good, since the mean nutritional

data obtained from the comparison between the two methods, also for micronutrient

intakes, were very similar, P values for paired t-test being not significant and mean

R values very high for all of the variables investigated despite within-person variance;

that is, day-to-day variation in diet, estimated in the recalls, might attenuate

correlations between the FFQ and the 24-h recall, due to the relative low number of

recall replicates. Adjusting for total energy intake slightly lowered some Pearson’s

coefficients that, however, remain quite high.

Our results showed greater agreement between FFQs and reference methods than

those obtained by other authors (Ocke et al. 1997b, Johansson et al. 2001, Sevak et al.

2004, Shu et al. 2004, Kusama et al. 2005, Tseng and Hernandez 2005, Block et al.

2006, Boucher et al. 2006, Fornes et al. 2006, Malekshah et al. 2006). This might be

due to the timing of administration since the first and the last administration of the two

instruments were done at the same time and responses from one may have influenced

the other; as well as the same serving sizes tool being used in both instruments may have

biased the results. Besides, the quick list used for the 24-h recall generated taking into

account the food items reported in the FFQ may have helped to improve the

correlation between the two methods.

Energy intakes measured by the FFQ and the 24-h recall may reflect the consistency

of Italian diets compared with other western populations since a more limited number

of foods are routinely eaten. Our results supported a strong association between the

FFQ and the 24-h recall, despite the short time of investigation, but similar to the one

of other studies (Goulet et al. 2004, Boucher et al. 2006). Nevertheless, some authors

(Rodriguez et al. 2002) carried out a validation study shorter than ours. We think that

good results were achieved by using the set of photographs in both dietary assessment

methods, aiding performance to the instruments.

Mean energies from the two instruments were very similar to those reported by

Turrini et al. (2001) in the Italian INN-CA 1995 survey (mean energy intake ¼ 2,162

kcal), showing a decrease in energy consumption compared with a previous study

conducted in 1980–1984 (Turrini et al. 2001). Fat consumption ranged from 27.3%

(24-h recall) to 27.5% (FFQ) of the total energy. In order to accurately estimate fat

consumption, additional questions concerning individual fat intake pattern were used

to adjust the composition of various recipes. Our results were in agreement with fat

consumption reduction in the Italian diet from the years 1980–1984 to 1994–1996

(Turrini et al. 2001) (lower intakes of whole milk, fat cheese, oil and fats). Our data

were not surprising since the Italian INN-CA 1995 survey (Turrini et al. 1999, 2001)

showed that, according to a quartile distribution of fat consumption, the 25% of the

Italian adults consumed less than 30% of energy from total fats. Finally, regarding

alcohol intakes, our data were similar to those of a previous study (Ferraroni et al.

1996) conducted on 395 Italian subjects (17.5 g, 21.4 g, and 20.3 g estimated from

7-day dietary records and two FFQs, respectively).

Our study compared two different methods one with another, rather than one

method with a true gold standard. Therefore, the mean of the four 24-h recalls might

not represent an individual’s true intake, but, despite the relative low number of recall

replicates, within-person variance did not seem to attenuate correlations between the


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FFQ and the 24-h recall, since we obtained high Pearson’s R correlation coefficient

values also for micronutrient intakes and after adjusting for total energy.

The FFQ had a good ability in classifying individuals according to intakes of energy,

alcohol and other nutrients in the same quartile as the 24-h recall. We demonstrated

stronger between-method agreement than other studies (Rodriguez et al. 2002,

Sevak et al. 2004, Shu et al. 2004); this might reflect a good sensitivity of the

instrument(s).

Bland–Altman plots performed for macronutrient and energy intakes showed that

the difference between the two methods was the same across the range of intakes, as

well as that the extent of agreement did not differ for low intakes compared with high

intakes. Our results supported previous data obtained by Bautista et al. (2005) in a

Colombian population. In addition, the overall mean differences, as well as their limits

of agreements, were very small for all the variables investigated. Therefore, we might

say that these results could be acceptable as well as very satisfactory for the assessment

of individual intake.

Our study has a few limitations that must be considered. The final sample of

subjects consisted of 112 individuals, reducing our ability in analyzing the data for

men and women separately. In addition, 4 days of recalls might not be a gold

standard, especially for micronutrients that require more days of record to

satisfactorily dampen day-to-day variability, although other researchers used even

less than four recalls (Rodriguez et al. 2002, Kusama et al. 2005, Tseng and

Hernandez 2005, Block et al. 2006, Boucher et al. 2006). Nevertheless, our

concordance between the two methods was quite good also for the micronutrient

intakes and after adjusting for total energy. It also should be pointed out that this

validation study does not apply to the FFQ when it is self-administered, since the

FFQ is often self-administered in large populations for epidemiological studies, where

interview administration is cost-inefficient.

The recalls were fixed by appointment and, even though the participants were

instructed not to change their food habits and consumptions until the end of the study,

the announced interview might have influenced the subjects’ answers, since they might

have become aware of their diet.

Reliability was assessed administering the FFQ at a fairly short interval (6 weeks)

contributing to increased reproducibility. Moreover, although the time frame of the

study covered 7 months, the instruments could not examine all season variations on

food consumption.

Finally, we did not use biological markers for the validation of the questionnaire in

alignment with many other authors (Khani et al. 2004, Xu et al. 2004, Bautista et al.

2005, Date et al. 2005, Ke et al. 2005, Shatenstein et al. 2005, Block et al. 2006,

Lee et al. 2006, Ahn et al. 2007).

The FFQ that we developed to estimate average daily energy, alcohol and nutrient

intakes in Italian adult subjects is a reliable and valid tool for dietary intake assessment.

Nutritional consumption was estimated accurately by this FFQ compared with the four

24-h recalls. The proportions of individuals correctly classified in the same quartile of

energy, alcohol and nutrient intakes were higher than those of other FFQs developed

for different populations. It will be that the FFQ was administered by dietitians trained

to ensure a standardized administration of the instrument was important to optimize

the reproducibility and relative validity of the method.


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In conclusion, this FFQ will be useful to assess dietary intakes in Italian adult

individuals in nutritional surveillance programs as well as to examine the association

between diet and health in epidemiological dietary surveys.

Declaration of interest: The authors report no conflicts of interest. The authors

alone are responsible for the content and writing of the paper.

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