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Record W7112773860

Factors affecting the glycemic index of fruits and its application in fruits choice of type 2 DM patients

2010· dissertation· en· W7112773860 on OpenAlexaboutno aff

Bibliographic record

VenueTaipei Medical University Repository · 2010
Typedissertation
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsnot available
Fundersnot available
KeywordsGlycemic indexGI bleedingType 2 diabetesGlycaemic indexGlycemic load
DOInot available

Abstract

fetched live from OpenAlex

目錄 中文摘要 I 英文摘要 III 目錄 IV 表目次 VIII 圖目次 IX 第一章 前言 1 第二章 文獻回顧 3 第一節 第 2 型糖尿病的飲食控制與治療 3 第二節 昇糖指數 5 一、 GI 概論及其定義 5 二、 GI 值與糖尿病 7 三、 GI 值與胰島素 7 四、 GI 值與血脂 8 第三節 餐後血糖的重要性 10 第四節 水果的角色 12 一、 單醣及雙醣 12 二、 膳食纖維 13 三、 甜度與糖度 14 第五節 -GLUCOSIDASE INHIBITOR之介紹 15 第三章 動機與目的 16 第四章 實驗設計與研究方法 18 第一節 水果 GI 值測定及其影響因子之分析 20 一、 受試者之召募與條件 20 二、 水果糖度之測定與篩選 22 三、 水果 GI 值之測定 24 四、 相關因子之分析 25 第二節 探討第2型糖尿病患者對選擇水果的認知及水果 GI 值之分析 28 一、 問卷調查 28 二、 水果 GI 的測定 28 第五章 統計分析 31 第六章 實驗結果 32 第一節 實驗第一部份 32 一、 受試者基本資料 32 二、 各種水果的測定時間及基本特性 2 三、 水果 GI 值及其相關因子之關聯性 5 第二節 實驗第二部份 7 一、 第 2 型糖尿病患者問卷調查結果 7 二、 第 2 型糖尿病患者基本資料 10 三、 第 2 型糖尿病患者水果 GI 值之測定 12 第三節 健康受試者與第 2 型糖尿病患者比較 14 一、 餐後血糖反應、水果之 PII 及 GI 值的結果比較 14 二、 第一部份水果 GI 值及第二部份問卷結果比較 17 第七章 討論 18 第一節 水果 GI 值與相關因子之關聯性 18 一、 醣類與 GI 值之相關性 18 二、 膳食纖維與 GI 值之相關性 19 三、 α-glucosidase inhibitory activity 與 GI 值之關聯性 21 四、 不同季節對水果 GI 值的影響 22 五、 香蕉中澱粉的含量對血糖之影響 22 第二節 健康受試者與第 2 型糖尿病患者之比較 24 一、 健康受試者與第 2 型糖尿病患者餐後血糖反應之比較 24 二、 健康受試者與第 2 型糖尿病患者之水果的 PII 及 GI 值比較 25 三、 第 2 型糖尿病患者之水果選擇認知情形與健康受試者之水果 GI 值比較 25 第三節 糖度與甜度 27 第四節 臨床應用 28 第八章 結論 29 第九章 參考資料 30 附錄一 研究計畫執行許可書 38 附錄二 受試者知情同意書 39 附錄三 第 2 型糖尿病患者之問卷調查 44 附錄四 第 2 型糖尿病患者之綜合問卷 47 表目次 表一、健康受試者基本資料 42 表二、各種水果測定的月份 44 表三、水果基本特性 45 表四、第 2 型糖尿病患者基本資料 52 表五、第 2 型糖尿病患者水果 GI 值之測定 54 表六、健康受試者與第 2 型糖尿病患者之水果的 PII 值 57 圖目次 圖 一、各種水果的糖度 32 圖 二、水果 GI 值及其相關因子之關聯性 47 圖 三、第 2 型糖尿病患者認為最可吃之水果排序 49 圖 四、第 2 型糖尿病患者認為最不可吃之水果排序 50 圖 五、第 2 型糖尿病患者與健康受試者之水果的餐後血糖反應曲線 56 食品工業發展研究所與屏東科技大學 (1988) 台灣地區食品營養成份資料庫,pp.94-113,行政院衛生署,台北市。 Abdulrhman M, El-Hefnawy M, Hussein R, El-Goud AA (2009) The glycemic and peak incremental indices of honey, sucrose and glucose in patients with type 1 diabetes mellitus: effects on C-peptide level-a pilot study. Acta Diabetol 26 [Epub ahead of print]. American Diabetes Association (2008) Nutrition recommendations and interventions for diabetes: a position statement of the American Diabetes Association. Diabetes Care 31: S61-78. Atkinson FS, Foster-Powell K, Brand-Miller JC (2008) International tables of glycemic index and glycemic load values: 2008. Diabetes Care 31: 2281-3. Belzer LM, Smulian JC, Lu SE, Tepper BJ (2009) Changes in sweet taste across pregnancy in mild gestational diabetes mellitus: relationship to endocrine factors. Chem Senses 34: 595-605. Brennan CS (2005) Dietary fibre, glycaemic response, and diabetes. Mol Nutr Food Res 49: 560-70. Chandalia M, Garg A, Lutjohann D, von Bergmann K, Grundy SM, Brinkley LJ (2000) Beneficial effects of high dietary fiber intake in patients with type 2 diabetes mellitus. N Engl J Med 342: 1392-8. Chareoansiri R, Kongkachuichai R (2009) Sugar profiles and soluble and insoluble dietary fiber contents of fruits in Thailand markets. Int J Food Sci Nutr 60: S126-39. Chong MF, Fielding BA, Frayn KN (2007) Mechanisms for the acute effect of fructose on postprandial lipemia. Am J Clin Nutr 85: 1511-20. Creutzfeldt W (1999) Effects of the alpha-glucosidase inhibitor acarbose on the development of long-term complications in diabetic animals: pathophysiological and therapeutic implications. Diabetes Metab Res Rev 15: 289-96. Davidson MH, McDonald A (1988) Fibre: forms and functions. Nutr. Res 18: 617–24. DeFronzo RA (1988) The Triumvirate: p-cell, muscle, liver: a collusion responsible for NIDDM. Diabetes 37: 667-87. DeFronzo RA (2004) Pathogenesis of type 2 diabetes mellitus. Med Clin North Am 88: 787-835. Du H, van der A DL, van Bakel MM, van der Kallen CJ, Blaak EE, van Greevenbroek MM, Jansen EH, Nijpels G, Stehouwer CD, Dekker JM, Feskens EJ (2008) Glycemic index and glycemic load in relation to food and nutrient intake and metabolic risk factors in a Dutch population. Am J Clin Nutr 87: 655-61. Englyst KN, Liu S, Englyst HN (2007) Nutritional characterization and measurement of dietary carbohydrates. Eur J Clin Nutr 61: S19-39. Hallfrisch J (1990) Metabolic effects of dietary fructose. FASEB J 4: 2652-60. Harbis A (2004) Glycemic and insulinemic meal responses modulate postprandial hepatic and intestinal lipoprotein accumulation in obese, insulin-resistant subjects. Am J Clin Nutr 80: 896–902. Harris PJ, Tasman-Jones C, Ferguson LR (2000) Effects of two contrasting dietary fibres on starch digestion, short-chain fatty acid production and transit time in rats. J. Sci. Food Agric 80: 2089–95. Higgins JA, Brand Miller JC, Denyer GS (1996) Development of insulin resistance in the rat is dependent on the rate of glucose absorption from the diet. J Nutr 126: 596-602. Hirsch IB, Brownlee M (2005) Should minimal blood glucose variability become the gold standard of glycemic control? J Diabetes Complications 19: 178-81. Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HA (2008) 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med 359: 1577-89. Jenkins DJ, Wolever TM, Taylor RH, Barker H, Fielden H, Baldwin JM, Bowling AC, Newman HC, Jenkins AL, Goff DV (1981) Glycemic index of foods: a physiological basis for carbohydrate exchange. Am J Clin Nutr 34: 362-6. Jenkins DJ, Kendall CW, Augustin LS, Franceschi S, Hamidi M, Marchie A, Jenkins AL, Axelsen M (2002) Glycemic index: overview of implications in health and disease. Am J Clin Nutr 76: S266-73. Juvonen KR, Purhonen AK, Salmenkallio-Marttila M, Lähteenmäki L, Laaksonen DE, Herzig KH, Uusitupa MI, Poutanen KS, Karhunen LJ (2009 ) Viscosity of oat bran-enriched beverages influences gastrointestinal hormonal responses in healthy humans. J Nutr 139: 461-6. Karhunen LJ, Juvonen KR, Flander SM, Liukkonen KH, Lähteenmäki L, Siloaho M, Laaksonen DE, Herzig KH, Uusitupa MI, Poutanen KS (2010) A psyllium fiber-enriched meal strongly attenuates postprandial gastrointestinal peptide release in healthy young adults. J Nutr 140: 737-44. Kim YM, Jeong YK, Wang MH, Lee WY, Rhee HI (2005) Inhibitory effect of pine extract on alpha-glucosidase activity and postprandial hyperglycemia. Nutrition 21: 756-61. Krishnan S, Rosenberg L, Singer M, Hu FB, Djoussé L, Cupples LA, Palmer JR (2007) Glycemic index, glycemic load, and cereal fiber intake and risk of type 2 diabetes in US black women. Arch Intern Med 167: 2304-9. Laaksonen DE, Toppinen LK, Juntunen KS, Autio K, Liukkonen KH, Poutanen KS, Niskanen L, Mykkanen HM (2005) Dietary carbohydrate modification enhances insulin secretion in persons with the metabolic syndrome. Am J Clin Nutr 82: 1218-27. Lebovitz HE (1998) Postprandial hyperglycaemic state: importance and consequences. 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Nilsson AC, Ostman EM, Granfeldt Y, Bjorck IM (2008) Effect of cereal test breakfasts differing in glycemic index and content of indigestible carbohydrates on daylong glucose tolerance in healthy subjects. Am J Clin Nutr 87: 645-54. Parks EJ (2001) Effect of dietary carbohydrate on triglyceride metabolism in humans. J Nutr 131: S2772–4. Parks EJ, Skokan LE, Timlin MT, Dingfelder CS (2008) dietary sugar stimulate fatty acid synthesis in adults. J Nutr 138: 1039–46. Poppitt SD, van Drunen JD, McGill AT, Mulvey TB, Leahy FE (2007) Supplementation of a high-carbohydrate breakfast with barley beta-glucan improves postprandial glycaemic response for meals but not beverages. Asia Pac J Clin Nutr 16: 16-24. Ramli SB, Alkarkhi AF, Yong YS, Easa AM (2009) The use of principle component and cluster analyses to differentiate banana pulp flours based on starch and dietary fiber components. Int J Food Sci Nutr 60: S317-25. Riby JE, Fujisawa T, Kretchmer N (1993) Fructose absorption. Am J Clin Nutr 58: S748-53. Rioux LE, Turgeon SL, Beaulieu M (2009) Effect of season on the composition of bioactive polysaccharides from the brown seaweed Saccharina longicruris. Phytochemistry 70: 1069-75. Samanta A, Burden AC, Jones GR (1985) Plasma glucose responses to glucose, sucrose, and honey in patients with diabetes mellitus: an analysis of glycemic and peak incremental indices. Diabet Med 2:371–3 Schulze MB, Liu S, Rimm EB, Manson JE, Willett WC, Hu FB (2004) Glycemic index, glycemic load, and dietary fiber intake and incidence

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.252
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2010
Admission routes1
Has abstractyes

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