• Title/Summary/Keyword: 기능성건강식품

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Systematic Review of the Effect of Glucosamine on Joint Health while Focused on the Evaluation of Claims for Health Functional Food (건강기능식품의 기능성을 중심으로 한 글루코사민의 관절건강 기능성에 대한 체계적 고찰)

  • Kim, Joohee;Kim, Ji Yeon;Kwak, Jin Sook;Paek, Ju Eun;Jeong, Sewon;Kwon, Oran
    • Journal of the Korean Society of Food Science and Nutrition
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    • v.43 no.2
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    • pp.293-299
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    • 2014
  • Although the functional ingredient has been evaluated based on scientific evidence by the Ministry of Food and Drug Safety (MFDS), the levels of scientific evidence and consistency of the results might vary according to the emerging data. Therefore, a periodic re-evaluation may be needed in some functional ingredients. In this study, we re-evaluated the scientific evidence for the joint health of glucosamine as a functional ingredient in health functional food. Literature searches were conducted using Pubmed, Cochrane, KISS, and IBIDS databases with the search term of glucosamine in combination with osteoarthritis. The search was limited to human studies published in English, Korean and Japanese. Using the MFDS's evidence based evaluation system for scientific evaluation of health claims, 34 human studies were identified and reviewed in order to evaluate the strength of the evidence supporting the relation between glucosamine and joint health. Among the 34 studies, significant effects for joint health were reported in 28 studies, and their daily intake amount was 1.5 to 2 g. Eleven out of 34 studies were identified, excluding severe radiographic osteoarthritis, and ten from those eleven studies reported significant effects for joint health. Based on this systematic review, we concluded that there was possible evidence to support a relation between glucosamine intake and joint health.

The Perceptions and Purchase Intentions of Health Food Consumers (건강기능식품에 대한 인식 및 구매의도 연구)

  • Lee, Jeung-Yun;Chae, Soo-Kyu;Kim, Kyu-Dong
    • Food Science and Preservation
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    • v.18 no.1
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    • pp.103-110
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    • 2011
  • We investigated consumer perceptions of and purchase intentions for health foods. Data were collected from 454 adults over the age of 20 years living in Seoul and Gyeonggi province, from May 10 to June 5, 2010. Those that "hardly ever drink" (41.4%) were most prevalent in terms of drinking activity, whereas 80.8% of respondents did not smoke. Also, those who responded "hardly ever exercise" ranked highest; although 43.8% in fact exercised frequently. Of all respondents, 44.5% admitted to suffering slightly from stress. A total of 59.5% of respondents opined "I am healthy but I do worry about health", and "exercise" topped the list of approved (37.2% of respondents) health care methods. We also found that 83.5% of respondents claimed to have tried health foods, whereas in the case of having no taking experience, 60% had not purchased such foods because, in their view, this was unnecessary. The extent of concerns about health foods scored 3.09, and the level of purchase intentions for health food was high, with a score of 3.40. Therefore, all of government, producers, distributors, and academic researchers must provide consumers with accurate and complete information, and need to collaborate in the development of consumer education programs on health foods. This will enhance consumer interest in such foods, and empower logical choices.

Analysis of Multiple Pesticide Residues in Raw Materials Used in Dietary Supplements by GC/ECD and NPD (GC/ECD와 NPD를 이용한 건강기능식품 주요 원료 중 다성분 잔류농약 분석)

  • Park, Sun-Young;Oh, Sang-Suk
    • Korean Journal of Food Science and Technology
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    • v.36 no.6
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    • pp.863-871
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    • 2004
  • Analyses of residual pesticides in raw materials used for dietary supplements were performed using multi-ingredients simultaneous analysis method. Pesticides such as BHC, chlorpyrifos, and quintozene were detected in 12 domestic and 7 imported samples, suggesting need for monitoring pesticides in domestic and imported raw materials and establishing residual limit of each pesticide.

Analytical Method Development for Determination of Coenzyme Q10 by LC-MS/MS in Related Health Functional Foods (건강기능식품에서 LC-MS/MS를 이용한 코엔자임Q10 분석법 연구)

  • Lee, Jin Hee;Oh, Mihyune
    • Journal of Food Hygiene and Safety
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    • v.34 no.6
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    • pp.519-525
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    • 2019
  • The Ministry of Food and Drug Safety (MFDS) is amending its test methods for health functional foods (dietary food supplements) to establish regulatory standards and specifications in Korea. In this regard, we are continuing our research on analytical method development for the items listed in the Korean Health Functional Food Codex. In this study, we have developed a sensitive and selective test method that could simultaneously separate and determine coenzyme Q10 based on liquid chromatographic-tandem mass spectrometry (LC-MS/MS). Calibration curves showed linearity with a correlation coefficient (R2) of > 0.999 and the limits of detection (LODs) and limits of quantitation (LOQs) were in the range of 26.0 ㎍/L and 78.9 ㎍/L, respectively. The recovery results ranged between 98.6-107.0% at 3 different concentration levels with relative standard deviations (RSDs) less than 5%. The proposed analytical method was characterized with high resolution of the coenzyme Q10 and the assay was fully validated as well.

A Method of Machine Learning-based Defective Health Functional Food Detection System for Efficient Inspection of Imported Food (효율적 수입식품 검사를 위한 머신러닝 기반 부적합 건강기능식품 탐지 방법)

  • Lee, Kyoungsu;Bak, Yerin;Shin, Yoonjong;Sohn, Kwonsang;Kwon, Ohbyung
    • Journal of Intelligence and Information Systems
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    • v.28 no.3
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    • pp.139-159
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    • 2022
  • As interest in health functional foods has increased since COVID-19, the importance of imported food safety inspections is growing. However, in contrast to the annual increase in imports of health functional foods, the budget and manpower required for inspections for import and export are reaching their limit. Hence, the purpose of this study is to propose a machine learning model that efficiently detects unsuitable food suitable for the characteristics of data possessed by government offices on imported food. First, the components of food import/export inspections data that affect the judgment of nonconformity were examined and derived variables were newly created. Second, in order to select features for the machine learning, class imbalance and nonlinearity were considered when performing exploratory analysis on imported food-related data. Third, we try to compare the performance and interpretability of each model by applying various machine learning techniques. In particular, the ensemble model was the best, and it was confirmed that the derived variables and models proposed in this study can be helpful to the system used in import/export inspections.