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잎채소류 섭취를 통한 마이크로시스틴 위해도 평가: 국민건강영양조사 섭취량과 문헌 기반 오염농도 적용. (Korean)

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  • Additional Information
    • Alternate Title:
      Dietary Risk Assessment of Microcystin Exposure from Leafy Vegetables Using KNHANES Consumption Data and Literature-Based Contamination Levels. (English)
    • Subject Terms:
    • Abstract:
      This study assessed the dietary exposure to microcystins (MCs) through consumption of leafy vegetables in Korea by combining the data on contamination levels reported in published literature with intake and body weight data from the 2023 Korea National Health and Nutrition Examination Survey (KNHANES). The estimated daily intake (EDI) was calculated for lettuce, spinach, napa cabbage, and cabbage, and hazard indices (HI) were derived using tolerable daily intake (TDI) values from the World Health Organization (WHO, 0.04 g/kg bw/day) and the Office of Environmental Health Hazard Assessment (OEHHA, 0.0064 g/kg bw/day). The results showed that under low-contamination conditions, the HI values, remained below 1 across all population groups, suggesting limited current risk. However, under high-concentration scenarios, the HI values exceeded 1 substantially, reaching tens to hundreds of times higher in infants, the elderly, and high-intake groups, underscoring the vulnerability of sensitive subpopulations. Because MC concentrations vary markedly across sites and seasons—even over short periods—continuous, seasonally responsive monitoring is warranted to capture episodic peaks and protect high-risk groups. These findings highlight the importance of integrating Korean dietary patterns into exposure assessment and provide a scientific basis for proactive food-safety management amid climate-driven cyanobacterial blooms. [ABSTRACT FROM AUTHOR]
    • Abstract:
      Copyright of Journal of the Korean Society of Food Culture is the property of Korean Society of Food Culture and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)