Development of a Seaweed Consumption Survey Tool for Dietary Exposure Assessment to Heavy Metals
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Abstract
Seaweed products are widely consumed due to their perceived health benefits. Nonetheless, they can serve as sources of toxic contaminants, particularly heavy metals such as lead and cadmium, which may accumulate from their aquatic environments. To accurately assess dietary exposure to these contaminants, it is essential to obtain detailed information on seaweed consumption patterns, including type and quantity consumed. However, existing data often lack such specificity, as prior studies did not differentiate between seaweed types, thereby complicating the classification of sources, particularly in distinguishing between freshwater and marine varieties. This study focused on the development and validation of a semi-quantitative food frequency questionnaire (SQ-FFQ) for evaluating seaweed consumption patterns. To fill the gap, the four steps were performed: (1) conducting a market survey (2) compiling a detailed list of seaweed types, seaweed-based products, and commonly consumed menus, (3) developing an online SQ-FFQ via google form, and (4) evaluating the tool’s content validity through expert review using the Index of Item-Objective Congruence (IOC), as well as assessing internal consistency reliability with Cronbach’s alpha coefficient (α-coefficient). The market survey identified 103 nori items, 5 zi-cai items, and 29 wakame items. Based on this, a total of 16 seaweed-based menu items were selected and incorporated into the questionnaire, comprising 10 nori-based menus, 1 zi-cai-based menu, and 5 wakame-based menus. The SQ-FFQ showed acceptable content validity (IOC = 0.6-1.0) and high reliability (α = 0.954), confirming its suitability for assessing seaweed consumption in dietary exposure to heavy metals.
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References
Wu JY, Tso R, Teo HS, et al. The utility of algae as sources of high value nutritional ingredients, particularly for alternative/ complementary proteins to improve human health. Front Nutr 2023; 10: 1277343.
Chen Q, Pan XD, Huang BF, et al. Distribution of metals and metalloids in dried seaweeds and health risk to population in southeastern China. Sci Rep 2018; 8(1): 3578.
Filippini M, Baldisserotto A, Menotta S, et al. Heavy metals and potential risks in edible seaweed on the market in Italy. Chemosphere 2021; 263: 127983.
FAO/WHO. Report of the expert meeting on food safety for seaweed–current status and future perspectives, 2021. Available at https://openknowledge.fao.org/server/api/core/bitstrems/43575678-4f1c-4e24-a452-3fc3c07fa4e7 /content, accessed on Jun 13, 2025.
Kumar A, Dey PK, Singla PN, et al. Blood lead levels in children with neurological disorders. J Trop Pediatr 1998; 44(6): 320-2.
FAO/WHO. Safety evaluation of certain food additives and contaminants: prepared by the seventy-third meeting of the joint FAO/WHO expert committee on Food Additives (JECFA), 2011. Available at https://www.who.int/ publications/i/item/9789241660648, accessed on Jun 13, 2025.
Tanaviyutpakdee P, Karnpanit W. Exposure assessment of heavy metals and microplastic-like particles from consumption of bivalves. Foods 2023; 12(16): 3018.
FAO/WHO. Principles and methods for the risk assessment of chemicals in food. Environmental Health Criteria 240, 2009. Available at https://www.who.int/ publications/i/item/9789241572408, accessed on Jun 14, 2025.
ACFS. Database of food consumption of Thai people, 2010. Available at http://consump-tion.acfs.go.th/main;jsessionid=44F0F45858CFB3F0602939D1FFEA0568, accessed on Jun 10, 2025.
Nirdnoy N, Sranacharoenpong K, Mayurasa-korn K, et al. Development of the Thai semiquantitative food frequency questionnaire (semi-FFQ) for people at risk for metabolic syndrome. J Health Popul Nutr 2021; 31(1): 1-8.
Martin-Moreno JM, Boyle P, Gorgojo L, et al. Development and validation of a food frequency questionnaire in Spain. Int J Epidemiol 1993; 22(3): 512-9.
Sierra-Ruelas É, Bernal-Orozco MF, Macedo-Ojeda G, et al. Validation of semiquantitative FFQ administered to adults: a systematic review. Public Health Nutr 2021; 24(11): 3399-418.
Cade JE, Burley VJ, Warm DL, et al. Food-frequency questionnaires: a review of their design, validation and utilisation. Nutr Res Rev 2004; 17(1): 5-22.
Chatprem T, Puntumetakul R, Yodchaisarn W, et al. A screening tool for patients with lumbar instability: a content validity and rater reliability of Thai version. J Manipulative Physiol Ther 2020; 43(5): 515-20.
Moore CG, Carter RE, Nietert PJ, et al. Recommendations for planning pilot studies in clinical and translational research. Clin Transl Sci 2011; 4(5): 332-7
Bujang MA, Omar ED, Foo DHP, et al. Sample size determination for conducting a pilot study to assess reliability of a questionnaire. Restor Dent Endod 2024; 49(1): e3.
Ab Rahman Z, Hashim A, Mohamed M, et al. Translation, validity, and reliability of the Malay version of the adolescent healthy lifestyle questionnaire. J Popul Soc Stud 2022; 31: 132-51.
Trangcasanchai P, Thiyajai P, Sridonpai P, et al. Development and validation of a semi-quantitative food frequency questionnaire for assessing prebiotic and probiotic intake among Thai adults. J Nutr Assoc Thailand 2024; 59(2): 67-80.
Turner RC, Carlson L. Indexes of item-objective congruence for multidimensional items. Int J Test 2023; 3(2): 163-71.
Dunn TJ, Baguley T, Brunsden, V. From alpha to omega: a practical solution to the pervasive problem of internal consistency estimation. Br J Psychol 1953; 105(3): 399-412.
Brown JD. Statistics Corner: questions and answers about language testing statistics: reliability of surveys. Shiken 1997; 1(2): 17-9. Available at http://jalt.org/test/bro_2.htm, accessed on Jun 22, 2025.
Alarsan SF, Mohd Saat NZ, Abd Talib R, et al. Validity and reliability of a questionnaire assessing changes in dietary behaviors among school children amid the covid-19 pandemic in Jordan. Cureus 2024; 16(8): e66980.
Kordas K, Cantoral A, Desai G, et al. Dietary exposure to toxic elements and the health of young children: methodological considerations and data needs. J Nutr 2022; 152(11): 2572-81.
Miclean M, Cadar O. Dietary metals (Pb, Cu, Cd, Zn) exposure and associated health risks in Baia Mare area, Northwestern Romania. J Biomed Res Environ Sci 2021; 2(7): 580-92.
MacIntosh DL, Williams PL, Hunter DJ, et al. Evaluation of a food frequency questionnaire-food composition approach for estimating dietary intake of inorganic arsenic and methyl-mercury. Cancer Epidemiol Biomarkers Prev 1997; 6(12): 1043-50.