Original Article
Validity of a food frequency questionnaire varied by age and body mass index

https://doi.org/10.1016/j.jclinepi.2006.01.002Get rights and content

Abstract

Background and Objective

The validity of food frequency questionnaires (FFQs) in measuring food consumption and nutrient intake has to be assessed. The objective of this study was to assess the validity of a 128-item FFQ in specific subgroups of Finnish adults.

Methods

The study included 294 subjects (137 men and 157 women). A 3-day food record was used as the reference method.

Results

The mean intake of all nutrients except alcohol was higher measured with the FFQ than with the food records. In general, the Pearson correlations for energy adjusted nutrients between the FFQ and the food records were higher in women than in men. The correlations ranged from 0.14 (retinol) to 0.66 (fiber and alcohol) in men, and from 0.20 (long-chain n−3 fatty acids) to 0.70 (alcohol) in women. The results in subgroups showed that measuring nutrient intakes is more difficult among younger (30–50 years) women and overweight men and women than among others.

Conclusions

The study showed that the FFQ is a useful tool in epidemiologic studies in measuring the diet of Finnish adults given that the problems among specific subgroups are taken into account in interpretation.

Introduction

The food frequency questionnaire (FFQ) has been established as the primary method for estimating long-term food consumption in large epidemiologic studies. Structured dietary data is easy and inexpensive to process compared to data gathered with an open method. Furthermore, no interviewers are needed if the study subjects fill in the questionnaires themselves. However, the FFQ has its limitations. The information is based on the subjects' memory, and because of the predefined food list, some information about the foods actually eaten may be missed. Therefore, it is essential to examine the validity of the FFQs against another dietary assessment method [1], [2], [3], [4], [5], [6], [7], [8], [9], [10].

It has been recommended that in study populations including both genders, validity has to be examined separately for men and women [11]. In studies in which the correlations between the FFQ and food records (the reference method) were analyzed separately by gender, obvious differences were not observed [6], [8], [12]. However, in a Danish validation study, contrary to the researchers' expectations, the correlations were mostly higher in men than in women [13]. In the Danish study the FFQ was slightly shorter than in the three other studies (92 vs. 116–350 foods).

There is evidence that gender, age, and obesity are associated with underreporting energy intake [14], [15], [16], [17]. In a Finnish study among subjects aged 25–64 years, underreporting was most common among women and overweight [body mass index (BMI) >25 kg/m2] subjects and among subjects older than 45 years [14]. Thus far, only a few validation studies for FFQs that measure the intake of a large variety of foods or nutrients with a food record as the reference method and including more than 100 subjects have shown results for subgroups other than by gender. Some validation studies have included only young [18] or elderly [19], [20] subjects or subjects from a specific profession, for example, nurses [1] or tin miners [21]. A validation study that was part of a study on selenium intake in relation to health status in the United States found that the correlations did not notably differ between the subjects with a high school education or less and the subjects with more than a high school education [6]. The study included 138 subjects with a mean age of 49 years. In another study in the United States, the correlations were reported separately for gender and race [22]. The correlations were higher for White subjects, and the correlations of Black men tended to be the lowest. The reference method was a combined 24-hr recall and food record and included food consumption data for 16 days (4 × 24-hr recall and 4 × 3-day food record).

The objective of our study was to assess the validity of a semiquantitative FFQ among an adult Finnish population with a 3-day food record as the reference method. To deepen our knowledge on the possible effect of the characteristics of the subjects on reporting food consumption, we also examined whether there are differences in the validity by age or BMI. The FFQ was developed for the Health 2000 Survey in Finland.

Section snippets

Study design and subjects

This validation study is a part of a nationally representative survey, the Health 2000 Survey (n = 8,028), which was carried out at 160 study locations in Finland from fall 2000 to spring 2001 [23]. The survey consisted of various health interviews, self-administered questionnaires, and a comprehensive health examination. The main aim of the survey was to estimate health and functional capacity and to gather information on major diseases, their causes, and treatment circumstances. Some basic

Results

In general, the mean nutrient intakes were higher measured with the FFQ than with the food records (Table 1). The only nutrient that was underestimated with the FFQ was alcohol. Overestimation was more prominent in women than in men. In women the intake of 17 of the 21 nutrients included in the validation study was over 40% higher measured with the FFQ than with the food records. The most overestimated nutrients were polyunsaturated fatty acids, long-chain n−3 fatty acids (LC n−3 FA),

Discussion

This validation study was a part of the Health 2000 Survey. The FFQ was specifically designed for the survey to assess the subjects' diet during the previous year, and to classify the subjects according to food consumption and nutrient intake. The validation sample included both genders aged 30–79 years. Although the subjects had participated in a number of interviews and examinations in the main survey before the administration of the FFQs and food records, the response rate in the validation

Acknowledgments

The authors thank all those who contributed to the data collection. Special thanks are due to Tommi Korhonen, M.Sc., and Heli Tapanainen, M.Sc., for assistance with the data management.

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