This study examined the reliability and validity of an SFFQ that assessed the dietary intake among physical examination adults in southwest region of China. The results of usual food intake and correlation coefficients suggested that SFFQ was reproducible and well performed when compared to 3R24.
The validation of food assessment tools is essential to understand the relationships between food and nutrition-related diseases. To assess the validity, although it is always imperfect, a 24 h dietary record is used for comparing widely. In this study, the validity of SFFQ was assessed by comparing the estimates of dietary intake from a 3R24 among adults who was undergoing physical examination in southwest of China. Overall, the SFFQ demonstrated good reproducibility in estimating the intake of food groups. The crude Pearson coefficients for the correlations between daily intake of various food groups derived from the two measures ranged from -0.086 to 0.93 and the mean correlation was 0.44. The adjusted Pearson coefficients for the correlations showed improvement from 0.31 to 0.96, and the mean correlation was 0.63. The correlation coefficients in our study and other studies were found to be very similar for many food groups, showing correlations of 0.19- 0.84 [14,15,16].
The SFFQ and 3R24 showed some differences in their error sources, and the two methods of investigation are sufficiently independent . Both questionnaires are prone to memory bias and have differences in the perception of portion sizes. The 3R24 method is based on open-ended questions, while SFFQ usually involves close-ended questions. The amount of nutritional intake can often be biased by the individuals' inability in accurately estimating the daily intake. Few other individuals showed unwillingness in acknowledging the intake of foods that might be harmful to health, such as internal organs, fatty meat, processed meat products, etc. Therefore, this SFFQ did not provide accurate and precise estimates of some nutrients (such as vitamin B, dietary fiber, protein and fat). However, for foods with low frequency of usual intake, the diet records (DRs) likely underestimates the intake of food. For example, the intake of low-frequency foods obtained by 3R24, such as tubers, poultry, aquatic products, phycomycetes, etc. in this study (in Table 4), was obviously less than those obtained by SFFQ. Although the correlation after adjusting the total energy intake was still higher than 0.3, the analysis and collection of such data seemed to be more reliable by SFFQ method. In this study, the amount of food, energy, and nutrients in repetitive SFFQ2 was increased (Table 3). This might be related to greater recall and higher attention of the subjects when the questionnaire was completed for the first time. Repeated completion of SFFQ might improve the authenticity of SFFQ. A more accurate estimation of these nutrients requires comparison of biomarkers as a reference for further study.
Fruit is the most frequently studied group in the literature and most FFQs. The correlations with regard to fruits generally range between 0.5 and 0.7, [18,19,, 19] and this was similar to those obtained in our study (fruits: r = 0.65). Vegetables, eggs, bread and noodles, dairy and red meat showed stronger correlation (r = 0.96, 0.86, 0.78, 0.71, 0.72), which was consistent with other studies reported [13, 20]. The intake of cereal and soy products was lower than the average levels reported in China, while the intake of fruits, poultry and red meat remained higher. Other foods were similar to those obtained in the earlier studies of China health and nutrition survey (CHNS) . This might be due to certain differences in the dietary and living habits of the population in southwest China The low frequency of intake of certain foods in this area might affect the results of the study. 3R24 was used to analyze, but it does not fully reflect the overall situation ofindividual`s food intake as mentioned in the previous studies . Of course, increasing the days of dietary record can effectively reduce the deviation. Some scholars have collected 7 days or more longer dietary record for research . But this undoubtedly increased the difficulty of the scale, which was not conducive to large-scale data collection in individuals undergoing physical examination.
There are no “gold standard” dietary investigations till date in China. Several types of instruments are used to assess both present and previous diets: the 24 h dietary recall, food-intake record, and food frequency questionnaire [19,20,21,22]. All these instruments had their own advantages and limitations. Which food intake methodology depends on the questions to be probed, the settings and participants, and the outcomes required should be investigated. A best method would be simple and quick, comprehensive and with high resolution, accurate, precise, and amenable to produce efficient and reliable data. Moreover, the main objective of the current study was to develop an easy-to-use FFQ for future epidemiological studies in China. Earlier FFQs that are used in Chinese epidemiological studies included more than 160 food items, such as CHNS [21,22,, 22]. It would take about 30 min to finish a survey, but a lengthy questionnaire is less likely to be completed and returned . The enduring participation rates of respondent effects the validation of the questionnaires , as longer questionnaires may cause respondent fatigue and poorer quality of gathered information. So, this might be not suitable for promotion to adults undergoing physical examination. With reference to Chinese Residents Dietary Guidelines’ selections, the FFQ was simplified, which would take 5–8 min to complete a survey, improving the operability and practicability significantly.
Generally the portion sizes are poorly estimated, and the inclusion of portion sizes in FFQs still remained controversial. For complex country such as China in terms of food, it is difficult to collect dietary information accurately using FFQ. Estimating the portion size of foods is difficult for most of the participants . Some investigators have suggested the use of commonly consumed portion sizes for calculating the nutrient intake in FFQ . For validating, it is important to recognize the portion size of food intake accurately. The results of this study inferred that foods with certain size or servings exhibited higher validity. For example, dairy, fruits, vegetables, and eggs, always in a certain portion size showed a higher correlation (Table 4), which was consistent with that of the previous study results .
It is important to mention that there are higher number of male participants and their losses (Table 2). In this study, fewer men refused to fill in the questionnaire and most of them answered the questionnaires by telephone. However, it seemed more difficult for women to complete all the questionnaires. The reason for such losses was due to the absence of 3R24, SFFQ incorrect record filling, and/or lack of informed consent. It is possible that this percentage might have influenced the results due to the final sample size.
The major strengths of this study include high participation rate, streamlined questionnaire, data collection by trained interviewers, and use of standard food map for estimating the portion size. An additional strength of this study is the normative design at the time of investigation of 3R24. The three consecutive days 24 h DRs were designed on Saturday, Monday, and Tuesday, which covered two weekdays and one weekend day, accounting for intraindividual variation between day types. Although DRs are recognized as golden standard, recording errors as well as changes in dietary habits are inevitable, especially during the weekend and holiday. The 3R24 collection method used in this study can assist in more objectively collecting the dietary data of participants on work days as well as rest days. This could help in more comprehensively comparing with the data collected by SFFQ. The SFFQ in this study has good reliability and validity in the population. It has a good application prospect in the future for analyzing the relationship between various physical examination indicators and dietary factors. It is imperative to collect health indicators and data of diet questionnaire through physical examination, conduct horizontal analysis and longitudinally monitor the health status of the population. This provides evidence-based practice for adjusting the diet structure and would promote health status of the population in the region.
The purpose of the present SFFQ is to evaluate the dietary patterns, i.e., food groups and nutrients, among adults undergoing physical health examination. The convergent validity and test–retest reliability was evaluated, but the internal consistency and discriminant validity still remained unclear. However, there are several limitations in the design of this SFFQ and validity appraisal. Firstly, it is of short length and consisted of only 14 food groups rather than single food items or dishes. Participants should classify their foods into simplified food groups, which subsequently increase the risk of misclassification. Also analysis of intake of certain special nutrients(such as anthocyanin, lycopene) might cause deviations. In addition, the reference period is only three months, which is more than one year and would be more representative of a person’s long-term dietary intake. There are seasonal variations in dietary and food intake, but the greatest seasonal variation occurs between summer and winter. Therefore, there might be a seasonal difference in the results of SFFQ and 3R24. Secondly, the repeated 24-h recalls were collected within two weeks of SFFQ1 completion. It has become difficult to predict the degree to which the divergences between the data can be attributed to questionnaire bias vs. differences in what individuals have actually ate during the two different time periods. While the unadjusted correlations between the items of the two questionnaires showed statistically significant differences, and some of them remained low. If the data was collected at the same time, then the unadjusted correlations might be either higher or lower. Along with all dietary assessment methods, some potential disadvantages could also be observed with regard to this SFFQ, such as recall bias, overestimation of dietary intake (particularly for rarely-consumed or healthy-perceived foods e.g., fruit and vegetables), bias of current intake and bias of pre-established food listings. Thirdly, the sample size might not reflect the mean energy intake of the population in the present study. Further study is needed for some nutrients (such as saturated and unsaturated fats, animal proteins and plant proteins, dietary fiber, vitamin B2 and vitamin B1). Finally, the problem of extrapolation within and between different food sub-groups in physical health examination adults is worth noting. Regional disparities should be taken into consideration in different areas of China. One question is that how these findings among Chinese in southwest China can be generalizable in other areas. One way to address this question is to conduct more evaluation studies to compare and validate the Chinese food cultural instruments in other areas.