Effect of the choice of food composition table on nutrient estimates: a comparison between the British and American (Chilean) tables

Abstract

Objective:To determine the level of agreement between the American (Chilean) and British food composition tables in estimating intakes of macronutrients and antioxidants. Design, setting and subjects: Information based on a food-frequency questionnaire with emphasis on antioxidants was collected from 95 Chileans aged 24-28 years. Nutritional composition was analysed using the British table of food composition and the American table of food composition modified by Chilean food items. Mean differences and limits of agreement (LOAs) of estimated intake were assessed. Results: Mean differences between the two tables of food composition ranged from 5.3% to 8.9% higher estimates when using the American (Chilean) table for macronutrients. For micronutrients, a bias towards a higher mean was observed for vitamin E, iron and magnesium when the American (Chilean) table was used, but the opposite was observed for vitamin A and selenium. The intra-class correlation coefficient (ICC) ranged from 0.86 (95% confidence interval (CI) 0.81 -0.91) to 0.998 (95% CI 0.995 -1.00), indicating high to excellent agreement. LOAs for macronutrients and vitamins A and C were satisfactory, as they were sufficiently narrow. There was more uncertainty for other micronutrients. Conclusion: The American table gives relative overestimates of macronutrients in comparison to the British table, but the relative biases for micronutrients are inconsistent. Estimates of agreement between the two food composition tables provide reassurance that results are interchangeable for the majority of nutrients.

The EPIC nutrient database project (ENDB): a first attempt to standardize nutrient databases across the 10 European countries participating in the EPIC study

“…Nutrient databases (NDBs), required to calculate nutrient intakes from food consumption data, are important potential sources of random and systematic dietary measurement errors (Bingham, 1987;Cameron and van Staveren, 1988;Southgate, 1992, 2003;Nieman et al, 1992;Guilland et al, 1993;Lee et al, 1995;Garcia et al, 2003;Hakala et al, 2003;Kim et al, 2003;Vaask et al, 2004). These errors, which will be detailed in this paper, can affect individual and population means as well as the distribution of nutrient intakes, and subsequently distort diet-disease associations.…”

Analysis of eating behaviors and eating habits, body mass index and waist-to-hip ratio in association with spirometry results of young adults

“…a diet rich in fresh vegetables and fruits, improves respiratory function in the general population (Kelly et al 2003, Butland et al 1999, 2000, Shaheen et al 2010. Epidemiological studies looking into the effect of balanced nutrition have shown that subjects on a diet rich in fruits, vegetables, fish and whole grains had much better respiratory parameters (Butland et al 2000, Shaheen et al 2010, Garcia et al 2004. However, most studies/reports focus on the effect of individual nutrients, their groups or nutritional patterns, and this may offer a limited chance for the interpretation of diet's effect on lung health (Garcia et al 2004).…”

Agreement of dietary fiber and calorie intake values according to the choice of nutrient composition and household measure tables

“…In addition to the analytical methodologies, the tables differ from one another in the list of foods and in the nutrients in the same food due to crop, variety, environmental factors, and food production and preparation among others [5,[7][8][9]. Due to these factors, the use of international tables in national studies on food consumption assessment must be done with caution [31].…”

“…A previous study has showed that different values were found between the American [5]. The incorrect description of foods and source of nutritional data, the use of unsuitable analytical methods with inadequate sampling, and variations due to genetic factors, regional disparities, food preparation and processing, and seasonal variation are factors that can influence the nutrient amounts listed in food composition tables [4][5][6][7][8]. It is important to check whether the data on food composition tables are constantly updated, considering the changes in food composition over time, improved analytical methods for particular nutrients, or the inclusion of information for new dietary components [3].…”

“…Researchers should pay attention to the main biases related to nutrient composition tables. A previous study has showed that different values were found between the American [5]. The incorrect description of foods and source of nutritional data, the use of unsuitable analytical methods with inadequate sampling, and variations due to genetic factors, regional disparities, food preparation and processing, and seasonal variation are factors that can influence the nutrient amounts listed in food composition tables [4][5][6][7][8].…”