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Validation of a Thai Semiquantitative Food Frequency Questionnaire (semi-FFQ) for People at Risk of Metabolic Syndrome

Abstract

Background: Food frequency questionnaires (FFQ) are a useful dietary assessment tool to determine relationships between diet and non-communicable diseases (NCDs). Our purpose was to validate a semiquantitative FFQ (semi-FFQ) for Thais at risk of metabolic syndrome (MS).

Methods: The researchers identified 345 men and women aged 30-65 years who were eligible for the study. Ninety-four participants were finally enrolled (54 in a "urine-collection not-required" group and 40 in a "urine collection" group). They were asked to maintain a 4-day food record for 4 weeks and partook in a semi-FFQ interview during week 4. Urine samples and biochemical results related to MS were collected. Validation results were associated with three primary nutrients for MS (sugar, fat, and sodium) and biochemical results (blood glucose, lipid profiles, blood pressure, and 24-h urine sodium).

Results: The biomarker level of each key MS nutrient significantly increased commensurate with rises in semi-FFQ estimated intakes. Correlation coefficients (r) were as follows: fasting blood glucose, r = 0.221 (fruits) and r = 0.229 (desserts); triglycerides, r = 0.112 (a la carte-dishes); low-density lipoprotein cholesterol, r = 0.205 (rice-with-topping dishes); systolic blood pressure, r = 0.272 (snacks) and r = 0.190 (a la carte dishes). Fasting blood glucose was a significant biomarker associated with the development of metabolic syndrome (OR 1.42, 95% CI 1.12-1.81). We also found that fat (OR 1.28, 95% CI 1.09-1.89), sodium (OR 1.98, 95% CI 1.05-1.95) and energy (OR 1.09, 95% CI 1.01-1.17) from an a la carte meal were significantly associated with the development of metabolic syndrome.

Conclusions: Thai food has a unique characteristic since it often pairs various ingredients and seasoning in one menu. This semi-FFQ is a tool that offers relatively valid ranking for intake of energy, nutrients, single foods, and mixed dishes based on Thai menus associated with a risk for developing metabolic syndrome and NCDs. Using this tool could help identify unhealthy dietary patterns and help develop recommendations for people at risk with the goal of preventing NCDs.

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References
1.
Srikan P, Callen B, Phillips K, Tavakoli A, Brockett R, Hanucharurnkul S . Testing a Model of Sodium Reduction in Hypertensive Older Thai Adults. J Nutr Gerontol Geriatr. 2017; 36(1):48-62. DOI: 10.1080/21551197.2016.1274278. View

2.
Rachmah Q, Kriengsinyos W, Rojroongwasinkul N, Pongcharoen T . Development and validity of semi-quantitative food frequency questionnaire as a new research tool for sugar intake assessment among Indonesian adolescents. Heliyon. 2021; 7(6):e07288. PMC: 8242999. DOI: 10.1016/j.heliyon.2021.e07288. View

3.
Kanehara R, Goto A, Kotemori A, Mori N, Nakamura A, Sawada N . Validity and Reproducibility of a Self-Administered Food Frequency Questionnaire for the Assessment of Sugar Intake in Middle-Aged Japanese Adults. Nutrients. 2019; 11(3). PMC: 6470835. DOI: 10.3390/nu11030554. View

4.
Cowin I, Emmett P . Associations between dietary intakes and blood cholesterol concentrations at 31 months. Eur J Clin Nutr. 2001; 55(1):39-49. DOI: 10.1038/sj.ejcn.1601120. View

5.
Freedman L, Schatzkin A, Midthune D, Kipnis V . Dealing with dietary measurement error in nutritional cohort studies. J Natl Cancer Inst. 2011; 103(14):1086-92. PMC: 3143422. DOI: 10.1093/jnci/djr189. View