基于血糖负荷概念的食物交换份法用于妊娠期糖尿病饮食干预的研究

目的:建立以控制血糖负荷和总能量为特征,体现食物血糖应答差异的新型食物交换系统,探讨其在妊娠期糖尿病(GDM)孕妇饮食干预中的应用价值。方法:将在河北医科大学第四医院住院分娩的120例GDM孕妇随机分成实验组和对照组,每组各60例。实验组根据食物血糖生成指数与碳水化合物含量计算血糖负荷,实施血糖负荷概念的食物交换份法饮食教育;对照组实施传统饮食指导。比较两组孕妇饮食行为改变情况、空腹血糖、餐后2 h血糖、糖化血红蛋白以及两组产妇新生儿出生体重情况。结果:两组孕妇饮食行为改变情况、空腹血糖、餐后2 h血糖、糖化血红蛋白以及两组产妇新生儿出生体重比较差异有统计学意义。结论:实验组实施血糖负荷概念的食物交换份法饮食教育后,GDM孕妇饮食更加科学化和合理化,各项糖代谢指标及新生儿出生体重明显低于对照组,降低了巨大儿和母婴并发症的发生,改善了母婴预后。     

厦门市城区居民膳食血糖负荷和膳食胰岛素负荷的 现况调查

摘要:目的　了解厦门市城区居民碳水化合物消费情况及膳食血糖负荷及膳食胰岛素负荷的现状,调查膳食血糖负荷及膳食胰岛素负荷与生化指标。方法　根据全国营养调查方案,2010年10-12月对厦门市城区的6个社区居委会成年居民进行调查,采用连续3 d 24 h回顾法对其中的291人进行膳食调查、身体测量及生化指标测量;根据膳食血糖生成指数（GI）和碳水化合物摄入量计算膳食血糖负荷（GL）;根据膳食胰岛素指数（II）和能量及食用频率计算膳食胰岛素负荷（IL）。结果　被调查的厦门市城区成年居民的平均膳食血糖指数为75.2;平均膳食血糖负荷为179.1;平均膳食胰岛素指数为30.4,平均膳食胰岛素负荷为247.2。粮谷类对膳食GL、IL的贡献达92.0%、83.1%。不同GL、IL水平的被调查人群的身体测量及生化指标间的差异无统计学意义;通过多元线性回归分析并未发现膳食GI、GL、II、IL与糖尿病的患病风险有明显的相关性。结论　粮谷类食物是厦门市城区居民膳食GL、IL的主要来源,低膳食GL的人群粮谷类消费低,脂肪消费高,膳食结构不合理;并未发现膳食GL、IL与身体测量及生化指标之间的联系。     

大豆发酵制品唐可肽对血糖生成指数的影响

目的测定大豆发酵制品唐可肽的血糖生成指数,并探讨唐可肽对于血糖生成指数以及血糖应答的影响。方法根据唐可肽碳水化合物的含量计算出相当于25g碳水化合物的唐可肽量,用25g葡萄糖为对照量,将受试者分为唐可肽组和葡萄糖组,每组10人,测定他们的空腹血糖后分别服用唐可肽和葡萄糖,测定2h内不同时点的血糖水平。根据Wolver方法计算食物的血糖生成指数(GI)值。结果测定了唐可肽血糖生成指数为54.86。结论唐可肽为低血糖生成指数值的食物。具有很好的降血糖、平稳血糖的作用。     

燕麦和荞麦加工食品血糖生成指数与血糖负荷测定

<正>食物中碳水化合物的性质和含量均会对机体血糖造成影响,而食物血糖生成指数(glycemic index,GI)和血糖负荷(glycemic load,GL)值则是反映该影响的生理指标。大量研究均证实低GI和低GL膳食干预对防治肥胖、糖尿病、心血管疾病等慢性代谢性疾病具有重要价值[1]。本研究应用国际认可的食物GI值标准化测定方法,对20种燕麦、荞麦加工食品GI和GL值进行测定,旨在填补目前食物GI和GL值数据库中燕麦、荞     

维吾尔族常用传统食品和血糖生成指数测定

目的确定新疆维吾尔族常用传统食品的种类,测定其血糖生成指数（GI）。方法运用食物频率调查法进行问卷调查确定维吾尔族传统特色食品;根据食物碳水化合物的含量计算含有50克碳水化合物的食物量,用50克葡萄糖为对照量。受试者民族为维吾尔族,共分4个批次,每个批次为10人,测定他们的空腹血糖后服用试验物,测定2h内不同时点的血糖水平。根据Wolver方法计算食物的GI值。结果确定了15种新疆维吾尔族特色食品,并测定了其GI值。结论GI数据从一定程度上提示新疆维吾尔族糖尿病高发的原因。     

饮食调节血糖新概念

在传统的观念中，医生们认为，可利用的碳水化合物对血糖的影响是一致的，但是，最新的研究表明，不同的碳水化合物对血糖的影响并不相同，这就是“食物血糖生成指数”。掌握好食物血糖生成指数有利于糖尿病的血糖控制。     

怎样正确理解血糖生成指数

食物中的碳水化合物进入人体后经过消化分解成单糖，而后进入血液循环，进而影响血糖水平。由于食物进入胃肠道后消化速度不同，吸收程度不一致，葡萄糖进入血液速度有快有慢，数量有多有少，因此即使含等量碳水化合物的食物，对人体血糖水平影响也不同。专家提出用“食物血糖生成指数”（GI）的概念来衡量某种食物或膳食组成对血糖浓度影响的程度。     

膳食碳水化合物和生糖负荷与成人血脂异常危险关系的研究

目的探讨膳食碳水化合物和生糖负荷与中国成人血脂水平及血脂异常患病危险的关系,为膳食防治提供科学依据。方法使用2002年中国居民营养与健康状况调查数据,根据食物血糖生成指数(glycemic index,GI)和碳水化合物摄入量计算膳食生糖负荷(glycemic load,GL)。以膳食GL作为指标,采用单相关分析和多元回归分析探讨膳食碳水化合物与中国成人血脂水平的关系;采用趋势分析和Logistic回归分析探讨膳食碳水化合物与中国成人血脂异常患病危险的关系。结果膳食GL与人群血浆总胆固醇(TC)水平和低密度脂蛋白胆固醇(LDL-C)水平呈负相关,高GL可降低高TC血症和高LDL-C血症患病危险;膳食GL与人群高密度脂蛋白胆固醇(HDL-C)水平呈负相关,高GL可增加低HDL-C血症患病危险;膳食GL与血浆甘油三酯(TG)水平呈负相关,但未见高GL对高TG血症患病风险有显著影响。结论以粮谷类食物为主,碳水化合物为主要能量来源的中国传统膳食模式有利于预防血脂异常的发生。     

孕期低血糖负荷膳食干预效果评价

<正>在中国,肥胖已经成为主要的公共卫生问题,迄今为止公布的国际建议引起了在临床和公共卫生领域控制孕妇体重和葡萄糖水平的关注~([1])。血糖生成指数(glycemic index,GI)是含碳水化合物的食物的特性,其描述了人体对餐后血糖的调节能力~([2]),已用于临床实践超过三十年,以区别不同的食物对血糖反应的影响。血糖负荷(glycemic load,GL)是平均膳食GIX消耗的     

食物血糖指数对糖尿病患者餐后血糖的影响

碳水化合物对糖尿病膳食影响已引起关注。限制碳水化合物的摄入，已成为营养治疗的首选措施。但以往对碳水化合物的应用，是以食物成分表的数据为准，凡是含量高的则指导病人少吃，反之则可多用。1981年Jenkins等提出血糖指数（Glycemic Index，GI）作为评价食物升血糖效应的指标，使人们对碳水化合物及糖尿病营养治疗有了新的认识。本观察不同GI食物对糖尿病患餐后血糖的影响，以指导糖尿病人合理选择碳水化合物食品。     

中国成人膳食生糖负荷现状调查

目的了解目前中国居民碳水化合物的消费情况与成人膳食生糖负荷的现状。方法使用2002年中国居民营养与健康状况调查数据,根据食物血糖生成指数(glycemic index,GI)和碳水化合物摄入量计算膳食生糖负荷(glycemic load,GL)。分析中国成人膳食GL的性别、年龄和城乡分布,分析不同膳食GL/4184kJ水平居民的膳食结构,探索中国成人膳食GL/4184kJ的合理范围。结果我国成人膳食GL92%来源于粮谷类。每人每日膳食GL平均为269.5,农村287.3,城市233.0,农村高于城市。青年平均为279.0,中年272.2,老年238.8,青年最高,其次是中年,最低是老年。男性平均为292.8,女性249.0,男性高于女性。低膳食GL/44184kJ的人群膳食碳水化合物供能比低,脂肪供能比高,粮谷类消费低,脂肪消费高,超重和肥胖发生率高。结论粮谷类是我国成人膳食GL的最主要来源。我国居民低膳食GL/4184kJ的人群粮谷类消费过低,脂肪消费过高,膳食结构不合理。城市居民较农村居民更为严重。以人群粮谷类食物摄入量、碳水化合物供能比、脂肪供能比在推荐的合理范围为依据,初步认为中国成人的膳食GL/4184kJ适宜范围为80~120。     

Glycemic index and glycemic load: measurement issues and their effect on diet-disease relationships

Glycemic index (GI) describes the blood glucose response after consumption of a carbohydrate containing test food relative to a carbohydrate containing reference food, typically glucose or white bread. GI was originally designed for people with diabetes as a guide to food selection, advice being given to select foods with a low GI. The amount of food consumed is a major determinant of postprandial hyperglycemia, and the concept of glycemic load (GL) takes account of the GI of a food and the amount eaten. More recent recommendations regarding the potential of low GI and GL diets to reduce the risk of chronic diseases and to treat conditions other than diabetes, should be interpreted in the light of the individual variation in blood glucose levels and other methodological issues relating to measurement of GI and GL. Several factors explain the large inter- and intra-individual variation in glycemic response to foods. More reliable measurements of GI and GL of individual foods than are currently available can be obtained by studying, under standard conditions, a larger number of subjects than has typically been the case in the past. Meta-analyses suggest that foods with a low GI or GL may confer benefit in terms of glycemic control in diabetes and lipid management. However, low GI and GL foods can be energy dense and contain substantial amounts of sugars or undesirable fats that contribute to a diminished glycemic response. Therefore, functionality in terms of a low glycemic response alone does not necessarily justify a health claim. Most studies, which have demonstrated health benefits of low GI or GL involved naturally occurring and minimally processed carbohydrate containing cereals, vegetables and fruit. These foods have qualities other than their immediate impact on postprandial glycemia as a basis to recommend their consumption. When the GI or GL concepts are used to guide food choice, this should be done in the context of other nutritional indicators and when values have been reliably measured in a large group of individuals.     

Compiling glycemic index and glycemic load values for addition to a food composition database

The glycemic index (GI) provides an indication of a food's carbohydrate quality by measuring the blood glucose response to consuming the food. The glycemic load (GL) is calculated as the GI times the available carbohydrate in a fixed amount of the food. GI and GL are currently of interest for the study of associations of diet and chronic disease including diabetes, cardiovascular disease, cancer and obesity. An international table of GI values is available and provides a compilation of currently available data. The purpose of this project was to use these data, as well as other available references, to expand the Cancer Research Center of Hawaii Food Composition Table (FCT) to include GI and GL values. All of the individual foods in the FCT (n=1592) were assigned GI values as a direct match (n=181), imputation (n=948), calculated value (n=208), or assigned a zero value (n=255). GL per 100 g was then calculated using the assigned GI and available carbohydrate per 100 g of food. The addition of GI and GL values to the FCT will allow researchers to estimate the effect of dietary carbohydrate quality on various health outcomes.     

基于血糖负荷概念的营养治疗对糖尿病合并高脂血症的影响

[目的]以控制总能量和血糖负荷为主要手段,探讨营养治疗在糖尿病合并高脂血症患者中的作用。[方法]选取71名糖尿病合并高脂血症的患者,随机分为两组,在控制总能量和食物交换份的前提下,除主食外,两组选择的其他食物相同。对照组的36人只进行简单的健康教育,自由选择主食;低血糖负荷组35人,用血糖指数和血糖负荷指导选择主食,实验为期16周。实验前后测身高、体重、腰围(WC)、臀围(HC),计算体质指数(BMI)、腰臀比(WHR),测量三头肌皮褶厚度(TSF)、收缩压(SBP),检测空腹血糖(FBG)、甘油三酯(TG)、总胆固醇(TC)、高密度脂蛋白(HDL-C)和糖化血红蛋白(HbAc)等各项指标。[结果]低血糖负荷组经饮食干预后,BMI、WC、WHR、TSF、SBP比干预前及对照组均有明显下降,除HDL-C外,血中TG、TC、FBG、HbAc均比对照组明显降低(P﹤0.05)。[结论]基于血糖负荷的营养治疗有助于合理选择食物,有效改善患者血糖、血脂和体脂水平。     

Glycemic impact, glycemic glucose equivalents, glycemic index, and glycemic load: definitions, distinctions, and implications

Glycemic impact, defined as "the weight of glucose that would induce a glycemic response equivalent to that induced by a given amount of food" (American Association of Cereal Chemists Glycemic Carbohydrate Definition Committee, 2007), expresses relative glycemic potential in grams of glycemic glucose equivalents (GGEs) per specified amount of food. Therefore, GGE behaves as a food component, and (relative) glycemic impact (RGI) is the GGE intake responsible for a glycemic response. RGI differs from glycemic index (GI) because it refers to food and depends on food intake, whereas GI refers to carbohydrate and is a unitless index value unresponsive to food intake. Glycemic load (GL) is the theoretical cumulative exposure to glycemia over a period of time and is derived from GI as GI x carbohydrate intake. Contracted to a single intake of food, GL approximates RGI but cannot be accurately expressed in terms of glucose equivalents, because GI is measured by using equal carbohydrate intakes with usually unequal responses. RGI, on the other hand, is based on relative food and reference quantities required to give equal glycemic responses and so is accurately expressed as GGE. The properties of GGE allow it to be used as a virtual food component in food labeling and in food-composition databases linked to nutrition management systems to represent the glycemic impact of foods alongside nutrient intakes. GGE can also indicate carbohydrate quality when used to compare foods in equal carbohydrate food groupings.     

The glycemic load estimated from the glycemic index does not differ greatly from that measured using a standard curve in healthy volunteers

Glycemic load (GL) is calculated indirectly as glycemic index (GI) times the weight of available carbohydrate. Alternatively, GL may be measured directly using a standard glucose curve. The purpose of this study was to test the agreement between GL values obtained using direct and indirect methods of measurement in 20 healthy volunteers. A standard curve in which glucose dose was plotted against blood glucose incremental area under the curve (iAUC) was generated using beverages containing 0, 12.5, 25, 50, and 75 g glucose. The GI and available carbohydrate content of 5 foods were measured. The foods (white bread, fruit bread, granola bar, instant potato, and chickpeas) were consumed in 3 portion sizes, yielding 15 food/portion size combinations. GL was determined directly by relating the iAUC of a test food to the glucose standard curve. For 12 of 15 food/portion size combinations, GL determined using GI x available carbohydrate did not differ from GL measured from the standard curve (P > 0.05). For 3 of the test products (100 g white bread, and 100- and 150-g granola bars), GI x available carbohydrate was higher than the direct measure. Benefits of the direct measure are that the method does not require testing for available carbohydrate and it allows portion sizes to be tested. For practical purposes, GI x available carbohydrate provided a good estimate of GL, at least under circumstances in which available carbohydrate was measured, and GI and GL were tested in the same group of people.     

孕早期膳食血糖负荷与妊娠期糖尿病关系的前瞻性研究

目的 探讨孕早期膳食血糖负荷（GL）与妊娠期糖尿病（GDM）的关系。方法 采用前瞻性研究,选取成都市某三甲妇幼医疗机构产前门诊1 462名孕8～14周单胎健康孕妇为研究对象。采用3天24小时膳食回顾法收集孕早期摄入的食物种类及数量。参照《中国食物成分表：标准版》及国际血糖生成指数和血糖负荷值表（2008）确定食物血糖生成指数（GI）值,根据食物GI值及其平均每日摄入量中碳水化合物含量计算膳食GL及主食GL。于孕24～28周行口服葡萄糖耐量试验,根据《妊娠合并糖尿病诊治指南（2014）》诊断GDM。按照四分位数分别将膳食GL及主食GL由低到高分为4组（Q1～Q4）,采用log-binomial回归模型分析膳食GL及主食GL与GDM的关系。结果 研究对象孕早期每日膳食GL和主食GL分别为145.70（113.23～180.85）和121.05（89.08～155.70）,米类和薯类GL分别为73.14（43.89～107.50）和3.43（0.00～9.84）。调整年龄、孕前BMI等混杂因素后,log-binomial回归分析显示,膳食GL在Q3、Q4组孕妇GDM发生风险均较Q1组增加（RR=1.47,95% CI：1.20～1.80;RR=1.31,95% CI：1.04～1.64）;主食GL在Q3、Q4组孕妇GDM发生风险均较Q1组增加（RR=1.28,95% CI：1.04～1.58;RR=1.27,95% CI：1.02～1.60）;米类GL在Q3、Q4组孕妇GDM发生风险均较Q1组增加（RR=1.30,95% CI：1.06～1.59;RR=1.28,95% CI：1.03～1.59）;薯类GL在Q4组孕妇GDM发生风险较Q1组增加（RR=1.30,95% CI：1.09～1.54）。未发现面类GL和杂粮GL对GDM发生风险有影响。结论 孕早期膳食GL与GDM发生有关,膳食GL较高尤其是米类及薯类GL较高可能增加GDM的发生风险。     

基于血糖负荷概念的食物交换份在糖尿病营养治疗中的应用

目的:建立以控制血糖负荷和总能量为特征,体现食物血糖应答差异的新型食物交换系统,探索其在糖尿病人饮食管理中的应用价值。方法:根据食物血糖指数(glycemicindex,GI)与碳水化物含量计算血糖负荷(glycemicload,GL),比较GI与GL的相关性以及对食物血糖效应的影响。融合GL和食物交换份方法的特点,提出基于GL的新型食物交换份。结果:粮谷类、豆类及制品的GI与GL%有较好的一致性,相关系数分别为0.64、0.55。而蔬菜、水果类食物的GI与GL%无明显相关性。基于GL的食物交换份既保留了传统交换方法简单易行的特点,又充分考虑了碳水化物在质和量方面的差异,有助于在控制总能量的同时,定量预测或调整混合膳食的血糖应答效应。结论:基于GL的食物交换份有较高的应用前景,值得实践和推广。     

Higher glycemic load diet is associated with poorer nutrient intake in women with gestational diabetes mellitus

Changes in the quality and quantity of carbohydrate foods may compromise nutrient intake in women with gestational diabetes mellitus (GDM). We hypothesized that glycemic index, glycemic load (GL), carbohydrate intake, grains, and cereal product consumption would be associated with nutrient adequacy. Eighty-two women with GDM (61% of Asian background, 34% whites) completed a 3-day food record following their routine group nutrition education session. Nutrient intakes were compared to Nutrient Reference Values (NRV) for Australia and New Zealand. Nutrient intake across energy-adjusted tertiles of glycemic index, GL, carbohydrate intake, and intake of grains and cereal products were assessed. The majority of women (66%-99%) did not meet the NRV for fiber, folate, vitamin D, iodine, and iron, and exceeded NRV for saturated fat and sodium. Higher dietary GL was associated with lower intakes of total, monounsaturated, and polyunsaturated fat; vitamin E; and potassium (all P < .001). Higher grain intake was not significantly associated with intake of any micronutrients. In Australian women with GDM, high dietary GL predicts greater risk of poor nutrition.