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dc.contributor.advisor권오란-
dc.contributor.author이단비-
dc.creator이단비-
dc.date.accessioned2017-08-27T11:08:17Z-
dc.date.available2017-08-27T11:08:17Z-
dc.date.issued2017-
dc.identifier.otherOAK-000000138541-
dc.identifier.urihttp://dcollection.ewha.ac.kr/jsp/common/DcLoOrgPer.jsp?sItemId=000000138541en_US
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/236184-
dc.description.abstract본 연구에서는 상대적으로 간단한 식품 섭취 평가 방법인 Recommended Food Score (RFS)를 이용해 혈중 carotenoid 농도 사이의 상관관계를 확인하였다. 또한 건강상태와 혈중 carotenoid 사이의 상관관계를 확인하였다. 본 연구의 대상자는 2015년 서울대학교 보라매병원 건강 검진 센터에 건강검진을 위해 방문한 성인 남녀 중 연구 참여에 대한 동의를 얻은 850명 (남자 509명, 여자 341명)을 대상으로 연구를 진행하였다. Carotenoid 수치는 plasma에서 high performance liquid chromatography 방법을 통해서 분석하였고, RFS는 식품 또는 식품으로 구성되어 47점 만점으로 계산하였다. 통계 분석은 전체 대상자를 분석하고, 대사증후군을 제외한 후에 산화스트레스와 관련된 질병으로 의약품을 섭취 중인 질병 군과 그렇지 않은 건강 군으로 나누어 진행하였다. 또한 RFS 점수에 따라서 4분위수로 나누어 그 차이를 확인하였다. 그 결과, 전체 대상자의 total carotenoids 와 β-carotene 에서는 model1, model2, 와 model3, lutein. β-cryptoxanthin, 와 α-carotene 에서는 model2 와 model3 에서 유의적으로 증가하였고, 건강 군에서는 lutein의 model1을 제외하고 유사한 관계를 보였다. 또한 전체 대상자에서 zeaxanthin 은 model3 에서 유의적으로 증가했지만, 건강 군에서는 차이를 보이지 않았다. 질병 군에서는 total carotenoids 와 β-carotene 의 model2 와 model3 에서 유의적인 증가를 확인하였고, α-carotene 의 model2 에서만 유의적인 증가를 나타냈다. 다음, RFS 식품 항목에 따른 중요도를 확인하기 위해 진행한 PLS 분석에서는 RFS 가 carotenoid를 함유한 식품을 적절하게 포함하고 있었지만, 시금치와 같이 높은 함량의 식품에서 음의 상관관계를 보이고 있었다. 이를 통해 얻은 coefficient 값을 적용하여 새롭게 계산된 RFS 와 carotenoid 사이의 상관관계를 확인한 결과, 전체 대상자에서 혈중 total β-cryptoxanthin, α-carotene, 와 β-carotene 이 유의적으로 증가하는 관계를 보였고, 건강 군에서는 total carotenoid 와 lutein+zeaxanthin 이 유의적인 양의 상관관계를 보였다. 따라서, RFS와 혈중 carotenoid 농도 사이에 상관관계가 있는 것으로 보이며, 이는 건강한 사람에게 RFS와 carotenoid 농도 사이에 관계가 더욱 잘 반영되는 것으로 보인다.;Consumption of carotenoids has been known to have association with preventing major chronic diseases including type 2 diabetes, cardiovascular disease, and some types of cancer. Most of carotenoids found in human body are absorbed through the diet. Therefore, blood and tissue carotenoid concentrations are considered to be reliable markers for determining dietary carotenoid exposure. Ideal intake of food consumption was promotion of health and prevention of disease. The RFS score was relatively simple dietary quality index that was developed to investigate the associating between oxidative stress and food intakes. Comparision of plasma carotenoids as biological measurement and RFS score as assessment of dietary intake can be helpful to evaluate health in simple way. Therefore, the aim of our study was to validating of association with RFS score and blood carotenoid concentrations in human subjects. In addition, association with RFS score and blood carotenoids concentration according to health condition was investigated. The data was collected from 850 Korea adults (men=509, women=341) undergoing an annual health examination at the Seoul National University Boramae Medical Center in 2015. RFS as dietary intake assessment was calculated by using a food-frequency questionnaire. A high performance liquid chromatography method to determine carotenoids concentration was applied to plasma samples. PLS analysis and regression analysis was used to assess the associations between RFS food items and plasma carotenoids. As results, RFS has significantly positive association with total carotenoids, lutein, zeaxanthin, β-cryptoxanthin, α-carotene, and β-carotene in total participants in total subjects and healthy except zeaxanthin, but diseased subjects has significant association with RFS score only in adjusted model of total carotenoids, α-carotene, and β-carotene. In addition, newly calculated RFS score has association with total carotenoid and lutein+zeaxanthin in healthy and β-cyrptoxanthin, α-carotene, and β-carotene in total subjects. Therefore, higher RFS score was related to plasma carotenoids concentration in total. In addition, health conidition may affect the result of association with RFS and plasma carotenoids concentratioin.-
dc.description.tableofcontentsI. Introduction 1 II. Method 4 1. Study population 4 2. Lifestyle and health data 6 3. Exposure assessment/ RFS 7 4. Measurement of carotenoid concentrations in blood samples 8 4.1. Reagents and chemicals 8 4.2. Standard and sample preparation 8 4.3. HPLC equipment and conditions 9 4.4. Method validation 9 5. Statistics analysis 11 III. Results 13 1. The basic characteristic: all-eligible participants and each group of health condition 13 2. Heatmap-visualization for Carotenoids concentration 16 3. Association of between RFS and carotenoids concentration in blood: all-eligible participants 18 3.1. The general characteristics 18 3.2. The correlation with between RFS and plasma carotenoids concentration 20 3.3. The association of adjusted means between RFS and carotenoids concentration 22 3.4. Identification of contributing food items by PLS regression analysis 24 3.5. Validation of PLS procedure of total subjects 27 4. Association between RFS and blood carotenoids concentration: healthy vs diseased participants 29 4.1. The general characteristics according to health condition 29 4.2. The correlation with between RFS and plasma carotenoids concentration according to health condition 32 4.3. The association between RFS and carotenoids concentration: health vs diseased group 34 4.4. Identification of contributing food items by PLS regression analysis according to health condition 37 4.5. Validation of PLS procedure according to health condition 40 IV. DISCUSSION 42 REFERENCE 46 Appendix 1. Written Informed Consent 50 Appendix 2. General, Health, and RFS questionnaire 52 Appendix 3. HPLC Validation Results 58 국문초록 61-
dc.formatapplication/pdf-
dc.format.extent1077995 bytes-
dc.languageeng-
dc.publisher이화여자대학교 대학원-
dc.subject.ddc600-
dc.titleRelation between blood carotenoids concentration and Recommended Food Score-
dc.typeMaster's Thesis-
dc.title.subtitleHealth examination data in Seoul, Korea-
dc.title.translated혈액 Carotenoids 농도와 Recommended Food Score 사이의 상관관계 : 서울 보라매병원 건강검진 자료-
dc.format.pagevi, 63 p.-
dc.identifier.thesisdegreeMaster-
dc.identifier.major대학원 식품영양학과-
dc.date.awarded2017. 2-
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