This study examined the reliability and validity of a SFFQ to assess dietary intake among physical examination adults in southwest region of China. In this study,3 day diet record (3R24) were used as a reference method11. Results of usual food intake and correlation coefficients suggest that the SFFQ was reproducible and performed well compared with 3R24.
The validation of food assessment tools is essential to understand the relationships between the food and nutrition − related diseases. To assess validity, although always imperfect, 24h dietary recalls is used for comparison widely. In this study, we assessed the validity of a simplified FFQ (SFFQ) by comparing estimates of dietary intake from the 3 day dietary records (3R24) among adults who were taking physical examination in southwest of China. Overall, the SFFQ demonstrated good reproducibility for the estimation of intakes of food groups. The crude Pearson coefficients for the correlations between daily intakes of various food groups derived from two measures ranged from − 0.086 to 0.93 and the mean correlation is 0.44. After adjusted by total energy intake, the adjusted Pearson coefficients for the correlations improved, from 0.31 to 0.96, and mean correlation is 0.63. The correlation coefficients in our study and other studies were very similar for many food groups, which had reported correlations of 0.19 − 0.8412−13.
A recent systematic review reported that the validity of FFQs should be re − evaluated because energy, carbohydrate, calcium, and vitamin C intakes were overestimated, especially in females14. Some scholars' research reported FFQs tended to have a larger measurement error for underestimating energy and nutrient intake compared with the error associated with DR or 24 − hour dietary recalls, using biomarkers included doubly labeled water and urine collection as a reference15. And simplified dietary survey questionnaires tend to underestimate energy and nutrient intake compared with that of longer questionnaires and DR16. The SFFQ and the 3R24 recall questionnaire have some differences in their error sources. Two methods of investigation are sufficiently independent17. Both questionnaires are prone to memory bias (SFFQ vs. the 3R24) and have differences in the perception of portion sizes. The 3R24 method is based on open − ended questions; while the SFFQ is usually close − ended questions. In our study, the SFFQ considered 3R24 as reference that was underestimated energy and nutrient intake, consisted with previous research. The amount of nutritional intake can often be biased by individuals' inability to correctly estimate daily intake. Some individuals are unwilling to acknowledge the intake of foods that might be harmful to health, such as internal organs, fatty meat, processed meat products, etc.Therefore, this SFFQ do not provide accurate and precise estimates for some nutrients (i.e., vitamin B, dietary fiber, protein and fat). However, for foods with low frequency of usual intake, DR is likely to underestimate food intake. For example, in this study, tubers, poultry, aquatic products, phytocomycetes, etc.(in Table 4), the frequency intake of which was only 1 − 2 times a week or less than once a week, the results obtained by the 3R24 method were obviously less than those obtained by SFFQ. Although the correlation after adjusted by total energy intake was still higher than 0.3, it seemed more reliable to analyze and collect such data by SFFQ method. In this study, the amount of food, energy, and nutrients in the repetitive SFFQ2 were increased(Table 3), which might be related to the higher recall and higher attention of the subjects when the questionnaire was completed for the first time. Repeatedly completing SFFQ if possible might improve the authenticity of SFFQ. A more accurate estimate 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. Concerning fruits, the correlations generally ranged between 0.5 and 0.7,18−19 which was similar to those obtained in our study (fruits: r = 0.65). Vegetables, eggs,bread and noodle, dairy and read meat were observed stronger correlation (r = 0.96, 0.86, 0.78, 0.71,0.72), consistent with other studies reported 13, 20. Moreover, the correlation and dietary intake of phytocomycetes, aquatic products, and nuts seemed lower than studies abroad. The intakes of cereal and soy product were lower than the average level reported in China. While the intakes of fruit, poultry and read meat were higher. Other foods were similar to those obtained in earlier studies in China health and nutrition survey (CHNS) 21. It might be that the dietary and living habits of the population in southwest China caused a certain difference between the dietary outcome and the average situation of the national population, which was caused by the particularity of the samples. The low frequency of intake of certain foods in this area might affect the results. We analyzed collecting 3 days of dietary records were not enough to fully reflect the individual is the overall situation of food intake, being mentioned in the previous studies9. Of course, increasing the days of dietary record can effectively reduce the deviation.Some scholars had collected 7 days or more longer dietary records for research, 22 but this would undoubtedly increase the difficulty of the scale, which was not conducive to large − scale data collection and organization in the physical examination customers.
There are no “golden standard” dietary investigations in China. Several types of instruments are used to assess both the present and previous diet: the 24 hour dietary recall, food − intake record, and the food frequency questionnaire 19−22. All of those instruments show either advantageous or limiting results. Which food intake methodology is used depends on the questions to be probed, the settings and participants, and the outcomes required. A best methods would be simple and quick, comprehensive and of high resolution, accurate and precise, and amenable to efficient and reliable data management. 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 have been used in Chinese epidemiological studies were included more than 160 food items, such as China Health and Nutrition Survey (CHNS) 21−22. It would take about 30 minutes to finish one survey. However, A length questionnaire is less likely to be completed and returned23. The enduring participation rates of respondent effects the validation of the questionnaires24. Given that longer questionnaires may cause respondent fatigue and poorer quality of gathered information. Maybe it is not suitable for promotion in the physical examination adults. With reference to Chinese Residents Dietary Guidelines’ selections, we classified those food items into 14 food groups. We focused on nutrient − rich frequently consumed foods, shortened the time required to fill the questionnaire and decreased participants boredom and increased accuracy of dietary intake assessment. As a result, it would take 5 − 8 minutes to finish one survey. It had improved operability and practicability significantly.
As generally portion sizes are poorly estimated, the inclusion of portion sizes in FFQs is still controversial. For a country as complex as China in terms of food, it appears to be difficult to collect dietary information accurately using FFQ. It seems that the large percentage of between − persons variation could be explained by consumption frequency, rather than portion sizes. Estimating portion size of foods is difficult for most participants25. Some investigators have suggested to use the commonly consumed portion sizes for calculating nutrient intakes in case of missing portion sizes in a FFQ. This method has apparently resulted in reasonable estimates of nutrient intakes26. It is important for the validation to recognize the portion size of food intakes accurately. In this study, investigators assisted to fill in the questionnaire with the help of standard food map and hand measuring.In addition, based on the results, we could infer that foods with certain size or servings exhibited higher correlation. For example, dairy, fruits, vegetables, and eggs, always with a certain size, showed higher correlation(Table 4),which consisted with previous research results27.
It was important to mention the higher number of male participants and the losses(Table 2). In this study, fewer men refused to fill in the questionnaire generally and most could stick to return questionnaires by telephone. However, women seemed difficult to complete all questionnaires. The reason for such losses, were the absence of 3R24, SFFQ incorrect record filling, and/or lacking of the Informed consent. It was possible that this percentage might have influenced the results concerning the viewing the final sample size.
The major strengths of this study include a high participation rate, streamlined questionnaire, data collection by trained interviewers, and using standard food map and hand measuring for estimating portion size and intake amount. An additional strenghth of this study is the normative design at the time of investigation of 3R24. The three consecutive days` 24h DRs were designed on Saturday, Monday, and Tuesday, which covered two weekdays and one weekend day to account for intraindividual variation between day types. Although diet records are recognized as the golden standard, errors in recording as well as changes in dietary habits as a result of keeping a record are inevitable, especialy in weekend and holiday. The 3R24 collection method used in this study can be more objectively collect dietary data of participants on work days and rest days, which could more comprehensive comparison with the data collected by SFFQ. The SFFQ in this study has good reliability and validity in the physical examination population in southwest China, and has a good application prospect in the future for analyzing the relationship between various physical examination indicators and dietary factors.Collect the health indicators and big data of the diet questionnaire through the physical examination link, conduct horizontal analysis and longitudinally monitor the health status of the population. This will provide evidence − based basis for adjusting the diet structure and promoting the health status of the population in the region.
The purpose of the present SFFQ is to evaluate dietary patterns, i.e., food groups and nutrients, among the physical health examination adults. There are, however, several limitations in the design of this SFFQ and the validity appraisal. Firstly, it is of short length and consists of 14 food groups rather than single food items or dishes. In addition, the reference period is only three months rather than the more usual one year which would be more representative of a person’s long − term dietary intake. There are seasonal variations in dietary and food intake, but these greatest seasonal variation occurs between summer and winter. Therefore, there may be a seasonal difference in the results of the SFFQ and the 3R24. Second, it is difficult to achieve an accurate estimatation of individual nutrients by an SFFQ as short or as of limited period of enquiry as that in physical health examination adults. In this study, SFFQ and 3R24 are both dependent on memory. The repeated 24 − hour recalls were collected within two weeks of SFFQ completion. Therefore, we cannot avoid the possibility that the validity may be higher than it should be. Along with all dietary assessment methods, some potential disadvantages could also be noted about this SFFQ including recall bias, overestimation of dietary intakes particularly for rarely − consumed and healthy − perceived foods (e.g., fruit and vegetables), and bias of current intake, misclassification and bias of pre − established food listing. Third, the sample size may not reflect the mean energy intake of the population in present study. Further study is needed for some nutrients(i.e., 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. There are regional disparity considerations in different Chinese area. One question is how universal these findings are among Chinese in southwest China, as in other area. One way to address this question would be to finish more evaluation studies to compare and validate Chinese food cultural instruments in other area.