Methodology for assigning appropriate glycaemic index values to an Australian food composition database

We aimed to produce an updated Australian glycaemic index (GI) database based on a systematic method. GI values were assigned to the 3871 unique foods in an Australian food composition database. Following the method, 1124 (29%) foods had less than 2.5 g of available carbohydrates per 100 g and were assigned a GI of 0, and 416 (11%) foods had a direct match in one of the three data tables used. The GI value of a ‘closely related’ food was assigned to 1793 (46%) foods; 135 foods (3%) had their GI values calculated using the weighted average GI method; 391 (10%) foods were assigned the median GI of their corresponding food subgroup, and 12 (<1%) foods were assigned a GI of 0 because they were not significant sources of carbohydrates in a typical diet. For the 3634 foods which received a GI value in the 2009 assignment, 1954 (53.8%) had an updated GI value, and the mean ± SD difference between the 2009 and current assigned values was +3.0 ± 16.0 units (paired sample t-test p < 0.001). Acknowledging some limitations, this database will enhance the utility of the GI concept in research and clinical settings in Australia (199 words).     

Methodology for adding glycemic index values to 24-hour recalls

Objective

To describe a standardized method to assign glycemic index (GI) values to food items, obtained from 3 × 24-h recalls among Aboriginal and Torres Strait Islander and non-Indigenous Australian children, which can be adapted for use with simple food composition databases.

Methods

Four published GI databases were used as the source of GI values. Changes were made to a previously published methodology for GI value assignment to accommodate the needs of the Many Rivers Diabetes Prevention Project.

Results

There were 1132 food items in the recall database. Two hundred nineteen (19.3%) food items were directly linked to the FoodWorks GI database and 545 (48.1%) items were assigned the GI value of a “closely related” food item in the four GI databases used. Among the top carbohydrate contributors, 113 (35.3%) items have a direct linkage with the FoodWorks GI database. The mean ± SEM dietary GI and glycemic load (GL) of the study population resulting from this methodology are 57.5 ± 0.3 and 143.4 ± 2.6, respectively.

Conclusion

This simple method provides opportunities for countries without food composition database that are comprehensive for GI/GL but which contain accurate information on carbohydrates in foods to assign high-quality GI values to food items in epidemiological studies based on 24-h recalls.     

Using database values to determine food density

Estimating food weight from data on food volume requires that density of the food be known. When both volume and weight are published on food tables the density can be calculated, however for many foods volume data are not available on the food table. Using a camera image of food to document dietary intake by automatically matching the food to a database entry requires that food volume be calculated and food weight estimated. This paper discusses some considerations when using USDA food tables to calculate composition of foods documented by camera image, as well as thoughts on measuring food volume and the potential for developing default values for density using available food volume data.     

混合膳食中不同膳食成分对血糖生成指数的影响

为了探讨脂肪、蛋白质和膳食纤维对食物血糖生成指数（ＧＩ）的影响,本研究应用葡萄糖氧化酶法和放射免疫法测定了９种混合膳食的血糖生成指数及人体的血糖、胰岛素应答。实验结果显示９种混合膳食的血糖生成指数分别为：米饭８３．２±３．１,米饭＋ 猪肉７２．０±１４．０,米饭＋ 猪肉＋ 芹菜５７．１±１１．２,米饭＋ 蒜苗５７．９±７．８,米饭＋ 蒜苗＋ 鸡蛋６２．８±１６．７,馒头８０．１±２２．５,馒头＋ 黄油６８．０±１６．３,馒头＋ 酱牛肉４９．４±２２．８,饼＋ 鸡蛋炒木耳４８．４±１１．７。蛋白质（β１ ＝ － ０．６９６,Ｐ＜ ０．０１）和膳食纤维（β２＝ － ７．３６４,Ｐ＜ ０．０１）与血糖生成指数有显著的相关性,可抑制餐后血糖的增加。脂肪与ＧＩ的相关性不显著,但有使ＧＩ值降低的趋势。结果还显示：膳食中适量的蛋白质可使血糖水平降低;适量的脂肪,可降低血糖的水平,但不促进胰岛素的分泌;膳食纤维与碳水化合物一起摄入可减少胰岛素分泌,降低血糖。结论：蛋白质和膳食纤维可降低血糖反应,对食物血糖生成指数产生显著的影响     

血糖负荷百分等级评价的方法

目的 建立血糖负荷的参照食物组,探讨应用血糖负荷参照食物组对食物血糖负荷进行百分等级评价的方法.方法 使用2011年中国居民营养与健康状况调查(CHNS)数据库,选取11～64岁人群膳食调查的食物摄入量,对碳水化合物的贡献率由高到低累积达到95％为目标,建立碳水化合物食物组;计算组内食物血糖负荷值并排序,建成血糖负荷参...     

食物血糖指数及其预测模型研究进展

近年来研究表明,食物血糖指数能有效指导糖尿病人膳食规划,从而控制血糖.本文概述了食物血糖指数概念的发展、数据测定、预测模型建立以及临床应用进展.     

Glycemic index and glycemic load are not associated with brain lesions in the elderly

Objective  The goal of this study was to determine if brain lesion volume was correlated with dietary glycemic index and glycemic load in elderly individuals. Design and Setting  This cross-sectional study was performed at an academic medical center as part of a clinical study of late-life depression. Participants  Subjects (n=137) were age 60 or over, and were participating as non-depressed comparison subjects. Measurements  Food intake was assessed using the Block 1998 food frequency questionnaire. Glycemic index and glycemic load measures were derived from reported food intake. Brain lesion volumes were calculated from magnetic resonance imaging (MRI). Results  No significant associations were found between glycemic index or glycemic load, and brain lesion volume. Conclusion  Dietary glycemic measures may be unrelated to brain lesions or may be related to brain lesions only in individuals with impaired glycemic control or other vascular risk factors. Further studies are needed to confirm this finding and to determine if glycemic control moderates this association. (work was completed as part of the Master of Science in Clinical Research program)     

Raisins are a low to moderate glycemic index food with a correspondingly low insulin index

The objective of this study was to determine the glycemic index (GI) and insulin index (II) of raisins and evaluate if these values are similar in different populations. The study subjects consisted of 10 healthy sedentary individuals (S; age, 25.7 ± 1.3 years; body mass index [BMI] = 23.3 ± 1.7 kg/m²), 11 aerobically trained adults (A; age, 23.1 ± 1.0 years; BMI = 24.1 ± 0.3 kg/m²), and 10 prediabetic adults (P; age, 50.0 ± 2.6 years; BMI = 32.6 ± 1.9 kg/m²). Subjects consumed 50 g of available carbohydrate from raisins and from a glucose solution (reference food) on 2 separate occasions. Serum glucose and insulin concentrations were measured from capillary fingerstick blood samples at baseline and at 15, 30, 45, 60, 90, and 120 minutes (and 150 and 180 minutes for P group) postprandially. The GI of raisins was low (GI, ≤55) in the S (49.4 ± 7.4) and P (49.6 ± 4.8) groups and was moderate (GI, 55-69) in the A group (62.3 ± 10.5), but there were no differences among the subject groups (P = .437). The II of raisins was 47.3 ± 9.4, 51.9 ± 6.5, and 54.4 ± 8.9 for the S, A, and P groups, respectively. On average, the A group secreted 2- to 2.5-fold less insulin per gram of carbohydrate compared with the S and P groups (P < .05). Thus, raisins are a low to moderate GI food, with a correspondingly low II. The lower insulin response in the A group compared with the other groups suggests enhanced insulin sensitivity.     

低血糖生成负荷饮食对糖尿病病人的疗效观察

目的:探讨低血糖生成负荷(LGL)饮食对2型糖尿病病人的影响. 方法:将90例2型糖尿病人随机分为试验组和对照组,每组各45例.试验组病人采用临床治疗配合正规糖尿病饮食以及少量多餐的低血糖负荷饮食;对照组采用临床治疗配合正规糖尿病饮食治疗.分别观察两组病人的体重指数(BMI)、空腹血糖(FPG)、餐后2h血糖(2 hPG)、糖化血红蛋白(HbAlc)、住院时间和住院费用等指标. 结果:试验组病人治疗后HbAlc明显改善,低血糖发生人数少于对照组,住院时间缩短,住院费用也低于对照组. 结论:LGL饮食干预能改善2型糖尿病病人HbAlc,减少低血糖发生率.     

Development of a food composition database to study complementary feeding: An Italian experience

Food Composition Databases (FCDBs) are important tools for epidemiological research, public health nutrition and education, clinical practice and nutrition declaration on food labels. The aim of this paper is to describe the methodology used to compile a FCDB for the analysis on the dietary intake of an Italian cohort of infants, and to assess its strengths and weaknesses. Dietary data were collected using a 3-DD records compiled at 6, 9 and 12 months of age of the infants. We developed a FCDB that contains data from the Italian and the USDA food composition databases and other sources. Our FCDB includes 563 food derived from the analysis of 623 3-DD records. Non-commercial products are more consumed than commercial products (25.5% vs. 9.1% at 6 months, 58.4% vs. 18.1% at 9 months and 77.8% vs. 11.3% at 12 months) but the latter are the main source of missing data (>70% in each database, with the exception of the energy components), which is one of the major weaknesses of this tool. An integrated system of data collection (NUTRIRETE.lab) that brings together food composition data from public and private laboratories will allow us to build a more complete and representative food composition database.     

Update of the Moroccan food composition tables: Towards a more reliable tool for nutrition research

The last food composition table (FCT) for Morocco was published in 1984 and has not been updated since. Our study aimed at bringing this FCT up to date, taking into account the current Moroccan population’s diet. To collate nutrient information, we used the indirect method based on existing data published in the scientific literature. The primary data sources for compiling this table were local FCTs. International food composition data were used as an alternative source when Moroccan data were not available. This updated FCT includes information on 38 nutrient components, for 587 food items commonly consumed in Morocco. These foods represent an addition of 79 % of foods in the FCT. About 7 % of nutritional values were derived from Moroccan data sources and about 93 % from international sources, namely Tunisia, West Africa, France, UK, and USA. We were unable to find approximately 20 % of nutrient estimates. This updated FCT provides information on foods and dishes commonly consumed in Morocco and it can be used as a tool to foster nutritional research and to design public health strategies in Morocco. This work is a first step towards updating a standardized Moroccan FCT, which will need to be complemented with high-quality composition data.     

Development of an on-line Irish food composition database for nutrients

Food composition databases underpin national dietary surveys, support epidemiological and experimental research in human nutrition and are essential in the development of food regulations and dietary guidelines. To date, nutrition researchers in Ireland have not had access to national food composition data and have relied heavily on borrowed data—mainly from the United Kingdom. The aim of this project was to compile an on-line Irish food composition database, which is compatible with international standards. Data on foods specific to the Irish population, including commonly consumed manufactured products, composite dishes and nutritional supplements, were collected between 1997 and 2006 during national dietary intake surveys. In conjunction with EuroFIR (European Food Information Resource Network of Excellence), these foods have been compiled using standardised methodology. The database comprises 938 foods, with values for 41 components. Values for packaged products were sourced from manufacturers and values for composite dishes were calculated from ingredients. Homemade meat, fish and vegetable dishes, manufactured cereal products and nutritional supplements are the key foods in the database. The Irish food composition database is available on-line (http://www.ucc.ie/en/ifcdb) and is incorporated in the EuroFIR eSearch facility (http://www.eurofir.eu) alongside other European national and specialised food composition databases.     

Mineral content of Pakistani foods: An update of food composition database of Pakistan through indirect method

Analysis of nutrients to develop new or update food composition database is costly and time consuming. An alternate approach is to add the data on nutrients from existing literature using guidelines set by International Network of Food Data Systems (INFOODS). The currently available database for food composition in Pakistan is fairly old (2001) and thus, needs to be updated. In the present study mineral content of various foods from Pakistan was collected from existing literature and scrutinized against a set of criteria for inclusion in updated food composition database of Pakistan. Data for 37 food items with eight minerals (calcium, iron, zinc, phosphorus, magnesium, potassium, sodium and copper) fits under the criteria therefore is included in updated database for foods of Pakistan. Additionally, chromium, cobalt, cadmium, lead, nickel and manganese were also updated for 16 food items. Further, selected mineral content (iron, zinc, phosphorus and calcium) was compared with food composition Table of Pakistan (published in 2001). Comparison results showed that mineral content for most of the foods vary among two databases. The present study demonstrates feasibility of updating food composition databases thorough scientific reports on food products of a particular country.     

Adding lignan values to a food composition database

The dietary lignans secoisolariciresinol (SEC) and matairesinol (MAT) are phytoestrogens structurally similar to the hormone estrogen and may exert estrogenic effects in the body. Quantification of dietary intake of phytoestrogens is of particular interest for the study of hormone-related diseases. The purpose of this project was to expand the Cancer Research Center of Hawaii Food Composition Table (FCT) to include values for SEC and MAT. Published analytical data for these two dietary lignans were compiled and evaluated for inclusion in the database. Eleven literature sources were identified with applicable analytical values. Using these sources, foods in the FCT were assigned values as a direct match, imputation, calculated value or assumed zero. A total of 1332 (89%) of the individual foods in the FCT were assigned values for SEC and MAT. Sixty-eight foods were direct matches, 553 were imputed, 394 were calculated, and 317 were assumed zero; 173 foods were indicated as having unknown lignan content. Levels of SEC and MAT ranged from 0–885.4 to 0–578.8 μg/100 g wet weight, respectively. The addition of SEC and MAT values to the FCT will allow researchers studying diet and disease to quantify intake of these dietary lignans.     

Computer-generated vegan menus: The importance of food composition database choice

Precise data on food chemical composition is crucial for any quantitative nutrition research and indispensable for evaluation and planning of computer-based menus. Moreover, exact food chemical composition is of the utmost importance in composing specific diets that may be low in certain essential nutrients. Therefore, this research evaluated a weekly vegan menu using three different food composition databases (FCDB): the Croatian, the official Danish Food Composition Database and the United States Department of Agriculture (USDA) – National Nutrient Database for Standard Reference. Significant differences (p < 0.05) were determined in evaluated and optimised offers for the same menu when using different FCDBs. Furthermore, in these menus quantities of some nutrients have not reached official daily recommendations needed for prevention of non-communicable diseases. In this research, new vegan menus that can provide adequate quantity of essential nutrients, regardless of FCDB utilized, were created with linear optimisation (LO). This resulted in high quality daily menu offers. However, depending on the FCDB that was used, optimal menus differed in daily meal combinations, and the effectiveness of the optimisation in the minimisation of differences caused by differences of data in FCDBs was tested. Linear optimisation has been proved to be an effective tool in planning of specific diets, such as vegan diets. Nonetheless, the quality of computer-planned menus depends heavily on the quality of FCDB used.