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The German Nutrient Database: Effect of different versions on the calculated energy and nutrient intake of the German population
Journal of Food Composition and Analysis 42 (2015) 26–29
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Journal of Food Composition and Analysis journal homepage: www.elsevier.com/locate/jfca
Original Research Article
The German Nutrient Database: Effect of different versions on the calculated energy and nutrient intake of the German population Bernd M. Hartmann *, T. Heuer, I. Hoffmann Max Rubner-Institut, Federal Research Institute of Nutrition and Food, Haid-und-Neu-Str. 9, 76131 Karlsruhe, Germany
A R T I C L E I N F O
A B S T R A C T
Article history: Received 20 December 2013 Received in revised form 25 August 2014 Accepted 12 January 2015 Available online 16 February 2015
The effects of altered data on the nutrient content of food items in a food composition database can be described by calculating and comparing the energy and nutrient intake of a population group with different database versions. To examine the effect of the differences between the German Nutrient Database (BLS) versions II.3, II.4, and 3.02 (generated in 1999, 2006, and 2014), the energy and nutrient intake of a representative sample of the German population (German National Nutrition Survey II (NVS II)) were compared. This comparison reveals that the median intake for most of the studied nutrients differed significantly between the three BLS versions for both sexes, in approximately one fourth of the comparisons more than 10%. The differences are largest for calcium (men: 21.5%; women: 22.5%), magnesium (men: 19.3%; women: 22.1%), and iodine (women: 20.2%) in the comparison of BLS version 3.02 and II.3. In particular changes of nutrient data of food items with high consumption, like milk, tea, and water, have strong effects on the calculated nutrient intake. Since the present study reveals a strong impact of the applied versions of a food composition database on the nutrient intake of food consumption studies, the knowledge of the version differences is of significant importance. ß 2015 Elsevier Inc. All rights reserved.
Keywords: Food composition database Food consumption Nutrient data Nutrient intake Nutrition survey German Nutrient Database Food analysis Food composition
1. Introduction Food composition databases are subject to continuous changes due to successive adjustments of nutrient data to current laboratory analyses and the inclusion of new food items. The effects of altered data on the nutrient content of food items can either be described by the absolute changes introduced or by calculating the energy and nutrient intake of a population group with different database versions. The objective of this article was to compare three different versions of the German Nutrient Database (Bundeslebensmittelschlu¨ssel (BLS)) regarding calculated energy and nutrient intake in a representative sample of the German population. The study was undertaken within the scope of the German National Nutrition Survey II (NVS II). The BLS was developed as a standard instrument for assessing the energy and nutrient intake of epidemiological studies and nutritional surveys in Germany (Dehne et al., 1999). Since 2004 the Max Rubner-Institut (MRI), Federal Research Institute of Nutrition and Food, in Karlsruhe is responsible for its further development and maintenance (Hartmann et al., 2008).
* Corresponding author. Tel.: +49-721-6625269; fax: +49-721-6625552. E-mail address: [email protected] (B.M. Hartmann). http://dx.doi.org/10.1016/j.jfca.2015.01.001 0889-1575/ß 2015 Elsevier Inc. All rights reserved.
The current BLS version 3.02 comprises 14,814 foods available in Germany including unprocessed and processed foods, all described by 131 nutrients. The nutrient values of approximately 1200 predominantly unprocessed foods are based on analysis conducted by the MRI and by national partner institutions as well as public and commercial laboratories. Further data of cooperation partners, like the food composition database Souci–Fachmann–Kraut (SFK) (Kirchhoff, 2002), as well as data published in the scientific literature were included. Nutrient values of processed foods are mostly calculated based on analyzed nutrient values derived from unprocessed foods under consideration of the preparation method. For such calculations, weight yield and nutrient retention factors are used to consider changes during food preparation. The NVS II is a nationwide food consumption study conducted between November 2005 and January 2007 to collect representative data of almost 20,000 German speaking participants (14–80 years) concerning food consumption, nutrient intake, social demographics, health and lifestyle aspects, as well as anthropometric measurements. It was commissioned by the Federal Ministry of Food, Agriculture and Consumer Protection (Heuer et al., 2015; Brombach et al., 2006). At study centers computer assisted personal interviews were conducted to obtain sociodemographic information and data on nutritional behavior. Also a
B.M. Hartmann et al. / Journal of Food Composition and Analysis 42 (2015) 26–29
computer assisted diet history interview was carried out assessing food consumption of the previous four weeks. Additionally, two 24-h recalls and a weighing record were conducted (Heuer et al., 2015; Krems et al., 2006). For the data of all three dietary assessment methods the BLS served as data basis for the calculation of the nutrient intake. To study the effect of different versions of the BLS on the calculated energy and nutrient intake of participants of the NVS II, the BLS versions II.3, II.4 and 3.02 were used (Table 1). From BLS version II.3 to version II.4 the database was extended by over 4000 food items with a focus on processed foods due to the requirements of the NVS II. Additionally, the nutrient retention factors were updated according to European standards (Va´squezCaicedo et al., 2008) and nearly the complete dataset of the SFK database was integrated. For the BLS version 3.02 approximately 250 further food items were incorporated in comparison to version II.4. Updated nutrient analyses were also included. 2. Methods The comparison of the energy and nutrient intake of the three versions of BLS were based on the same food consumption data assessed by diet history interviews of the NVS II. The frequency and quantity of the consumed foods and beverages over the last four weeks of 15,371 German speaking persons (7093 men and 8278 women) between 14 and 80 years of age were conducted using the dietary assessment program DISHES (Dietary Interview Software for Health Examination Studies) (Mensink et al., 1998, 2001) especially modified and adapted to the requirements of the NVS II (Krems et al., 2006). The foods available in the DISHES program were already matched with BLS codes. New or altered foods of different BLS versions were matched using the best possible option in regard to the nutrient content. The methods of the NVS II survey and the data preparation (e.g. data controls for plausibility) are described in detail elsewhere (MRI, 2008). The median of the daily energy and nutrient intake, the relative difference of the median, and the 95% confidence interval of median were calculated with SAS version 9.1 (SAS Institute Inc., Cary, NC, USA). Because of the predominantly skewed distribution of nutrient intake data the median was used. For relative differences and significance, pairwise comparisons between the BLS versions II.4 versus II.3, 3.02 versus II.4, and 3.02 versus II.3 were conducted. Differences are considered to be significant if the 95% confidence intervals do not overlap. Out of the 131 nutrients of the BLS the comparison is conducted for 29 nutrients published in their final report of the NVS II (MRI, 2008). 3. Results For most of the nutrients the intakes calculated with the three BLS versions differ significantly for men and women (percentage of nutrients for which the calculated intakes differ between the compared BLS versions: II.4–II.3: 78%; 3.02–II.4: 64%; 3.02–II.3: 78%) (Table 2). For men and women the incidence of significant differences between the different BLS versions are mostly in concordance except for retinol (version II.4 versus II.3), protein, niacin equivalents, and iodine (3.02 versus II.4), protein, tocopherol equivalents, and vitamin C (3.02 versus II.3) where the intake
Table 1 BLS versions used for data comparison.
Year of publication Number of data sets
BLS II.3
BLS II.4
BLS 3.02
1999 10,653
2006 14,563
2014 14,814
27
differences are significant for men only, whereas for fat, vitamin D, vitamin B2, and vitamin B12 (3.02 versus II.3) the intake differences are only significant for women. The nutrients for which intakes differ significantly and continuously throughout all version comparisons are protein, retinol, tocopherol equivalents, niacin equivalents, vitamin C, and iodine for men. Vitamin B2 for women differed significantly as well as intakes of fiber, beta-carotene, alpha-tocopherol, sodium, calcium, magnesium, iron, and zinc for both sexes. No significant intake differences throughout all version comparisons are found for fat intake for men and alcohol intake for both sexes. Throughout all version comparisons significant intake differences of minerals are more consistent than of macronutrients and vitamins (Table 2). Regarding each version comparison BLS version II.4 versus II.3 reveals significant differences in the calculated intake of protein, fiber, vitamins (except for retinol (women) and vitamin D), and all minerals. In the comparison of BLS version 3.02 with II.4 the intakes of energy, protein (men), carbohydrates, fiber, and cholesterol differ significantly as well as the mineral intakes except for potassium and iodine (women). In the comparison of version 3.02 versus II.4 the intakes of fewer vitamins differ significantly than of II.4 versus II.3. The comparison of BLS version 3.02 with II.3 shows significant differences in energy, protein (men), carbohydrates, fat (women), and fiber as well as all mineral intakes. Here most of the vitamins also differ significantly except for vitamin D, vitamin B2, and vitamin B12 for men, tocopherol equivalents and vitamin C for women, and vitamin B6 for both sexes. In approximately one fourth of all version comparisons, the significant differences between the medians of nutrient intake differ more than 10%. The differences are largest in the comparison of version 3.02 and II.3 for calcium (men: 21.5%; women: 22.5%), magnesium (men: 19.3%; women: 22.1%), and iodine (women: 20.2%). Further differences above 10% include beta-carotene (men: +18.5%; women: +19.2%), retinol (men: +18.6%; women: +14.0%), iron (men: 16.3%; women: 18.0%), and alpha-tocopherol (men: +12.6%; women: +13.1%) in the comparison of BLS version 3.02 and II.3. Concerning differences of the medians of the nutrient intake between all version comparisons, no systematic changes can be detected: There are increasing values from BLS version II.3 to II.4 to 3.02 (e.g. retinol and beta-carotene) and decreasing values (e.g. for calcium, magnesium, and iron); there are lower values from version II.3 to II.4 and higher ones from II.4 to 3.02 (e.g. fiber, vitamin C, and zinc) and also higher values from version II.3 to II.4 and lower ones from II.4 to 3.02 (e.g. vitamin B2 and vitamin B6). Comparing BLS versions 3.02 versus II.4 reveals that the nutrient intake of beta-carotene and retinol was higher in version 3.02 while the retinol equivalents showed lower values. The iodine intake from version II.3 to II.4 is lower for both sexes (men: 17.4%; women: 18.9%), while the iodine intake from version II.4 to 3.02 is only higher for men (9.5%). 4. Discussion Adjustments of nutrient data in food composition databases may be described by listing the alterations. However, it is preferable to explore the analysis of the energy and nutrient intake of food consumption data with different versions of a food composition database (Hulshof et al., 1996; Matsuda-Inoguchi et al., 2001; Ahuja et al., 2006). The comparison of energy and nutrient intake of the NVS II participants assessed by diet history method and evaluated with the versions II.3, II.4 and 3.02 of the BLS shows that discrepancies of most nutrient intakes differed significantly and ranged up to 23%. This is in concordance with publications which compared the
B.M. Hartmann et al. / Journal of Food Composition and Analysis 42 (2015) 26–29
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Table 2 Comparison of daily energy and nutrient intake of men and women in the NVS II study, based on the BLS versions II.3, II.4 and 3.02. Median
Nutrient
Energy (kcal) Protein (g) Carbohydrate (g) Fat (g) Alcohol (g) Fiber, total dietary (g) Cholesterol (mg) Retinol equivalents (mg) Retinol (mg) Beta-carotene (mg) Vitamin D (mg) Tocopherol equivalents (mg) Alpha-tocopherol (mg) Vitamin B1 (mg) Vitamin B2 (mg) Niacin equivalents (mg) Niacin (mg) Vitamin B6 (mg) Vitamin B12 (mg) Vitamin C (mg) Folate equivalents (mg) Folate (mg) Sodium (mg) Potassium (mg) Calcium (mg) Magnesium (mg) Iron (mg) Zinc (mg) Iodine (mg)
M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F
Difference (%)
BLS II.3
BLS II.4
BLS 3.02
2427 1831 88.3 65.7 271 219 92.3 67.7 9.00 2.00 26.6 24.6 345 249 1.58 1.42 0.59 0.43 4.05 4.22 2.83 2.21 12.56 11.06 10.60 9.44 1.46 1.11 1.71 1.41 34.74 25.50 18.30 13.15 1.97 1.57 5.60 3.71 136 143 269 239 269 239 3316 2481 3764 3285 1269 1167 518 444 16.0 13.3 12.9 10.2 120.2 113.0
2413 1833 85.3 64.3 270 220 92.5 68.4 9.04 2.05 24.8 23.1 352 254 1.75 1.54 0.64 0.44 4.26 4.41 2.88 2.19 13.72 11.97 11.07 10.06 1.55 1.18 1.85 1.52 36.29 26.67 19.82 14.29 2.25 1.78 5.80 3.96 130 134 283 252 280 249 3216 2379 3612 3140 1052 964 432 361 14.4 11.8 11.6 9.1 99.3 91.6
2490 1891 86.7 65.1 284 231 94.0 69.7 9.02 2.08 26.0 23.7 342 245 1.73 1.52 0.70 0.49 4.80 5.03 2.74 2.06 12.22 10.98 11.94 10.68 1.57 1.19 1.75 1.44 37.22 26.93 20.12 14.27 1.98 1.55 5.67 3.96 145 146 280 253 277 249 3529 2557 3676 3192 996 905 418 346 13.4 10.9 12.3 9.5 108.7 90.2
Significance*
95% Confidence interval
BLS II.4-II.3
BLS 3.02-II.4
BLS 3.02-II.3
0.6 0.1 3.4 2.1 0.4 0.5 0.2 1.0 0.4 2.5 6.8 6.1 2.0 2.0 10.8 8.5 8.5 2.3 5.2 4.5 1.8 0.9 9.2 8.2 4.4 6.6 6.2 6.3 8.2 7.8 4.5 4.6 8.3 8.7 14.2 13.4 3.6 6.7 4.4 6.3 5.2 5.4 4.1 4.2 3.0 4.1 4.0 4.4 17.1 17.4 16.6 18.7 10.0 11.3 10.1 10.8 17.4 18.9
3.2 3.2 1.6 1.2 5.2 5.0 1.6 1.9 0.2 1.5 4.8 2.6 2.8 3.5 1.1 1.3 9.4 11.4 12.7 14.1 4.9 5.9 10.9 8.3 7.9 6.2 1.3 0.8 5.4 5.3 2.6 1.0 1.5 0.1 12.0 12.9 2.2 0.0 11.5 9.0 1.1 0.4 1.1 0.0 9.7 7.5 1.8 1.7 5.3 6.1 3.2 4.2 6.9 7.6 6.0 4.4 9.5 1.5
2.6 3.3 1.8 0.9 4.8 5.5 1.8 3.0 0.2 4.0 2.3 3.7 0.9 1.6 9.5 7.0 18.6 14.0 18.5 19.2 3.2 6.8 2.7 0.7 12.6 13.1 7.5 7.2 2.3 2.1 7.1 5.6 9.9 8.5 0.5 1.3 1.3 6.7 6.6 2.1 4.1 5.9 3.0 4.2 6.4 3.1 2.3 2.8 21.5 22.5 19.3 22.1 16.3 18.0 4.7 6.9 9.6 20.2
BLS II.3
BLS II.4
BLS 3.02
BLS II.4-II.3
BLS 3.02-II.4
BLS 3.02-II.3
2404–2448 1816–1847 87.5–89.0 65.2–66.3 267–273 218–221 91.3–93.3 67.0–68.5 8.66–9.39 1.87–2.10 26.4–26.9 24.3–24.9 342–350 246–252 1.57–1.60 1.40–1.43 0.58–0.60 0.42–0.44 3.98–4.12 4.16–4.29 2.79–2.90 2.16–2.26 12.44–12.68 10.96–11.19 10.51–10.71 9.33–9.53 1.45–1.48 1.10–1.12 1.70–1.73 1.40–1.42 34.41–35.04 25.26–25.70 18.11–18.51 13.05–13.27 1.95–1.99 1.56–1.58 5.54–5.66 3.67–3.76 134–138 141–146 266–272 237–242 266–271 237–242 3284–3345 2463–2501 3731–3795 3257–3313 1255–1282 1156–1179 513–523 441–447 15.8–16.1 13.2–13.5 12.8–13.0 10.1–10.3 119.3–121.4 111.8–114.0
2396–2433 1817–1849 84.4–85.9 63.7–64.9 267–273 219–222 91.4–93.6 67.7–69.2 8.70–9.49 1.93–2.17 24.6–25.1 22.8–23.4 347–356 251–256 1.74–1.78 1.52–1.57 0.63–0.65 0.44–0.45 4.18–4.36 4.34–4.46 2.82–2.94 2.15–2.23 13.58–13.93 11.84–12.11 10.90–11.19 9.94–10.17 1.53–1.57 1.17–1.19 1.83–1.87 1.51–1.54 36.03–36.58 26.44–26.87 19.60–20.07 14.17–14.42 2.22–2.27 1.76–1.80 5.73–5.88 3.92–4.01 128–132 132–136 280–287 250–255 278–283 247–252 3192–3246 2359–2396 3580–3643 3114–3164 1041–1064 957–974 430–436 358–364 14.2–14.5 11.7–11.9 11.5–11.7 9.0–9.2 98.4–100.3 90.6–92.6
2465–2511 1877–1908 86.0–87.4 64.5–65.6 280–287 229–233 92.9–95.2 69.0–70.5 8.68–9.46 1.96–2.19 25.8–26.3 23.5–24.0 338–346 243–248 1.70–1.75 1.50–1.54 0.69–0.72 0.48–0.50 4.71–4.88 4.95–5.11 2.69–2.80 2.02–2.10 12.09–12.37 10.85–11.13 11.80–12.11 10.57–10.83 1.55–1.59 1.18–1.20 1.73–1.77 1.43–1.46 36.92–37.65 26.71–27.12 19.91–20.33 14.15–14.43 1.96–2.00 1.53–1.56 5.60–5.73 3.90–4.01 142–146 144–148 278–283 250–255 274–279 246–252 3492–3561 2534–2580 3642–3706 3164–3219 985–1010 897–913 414–421 344–349 13.3–13.5 10.8–11.0 12.2–12.4 9.4–9.6 107.5–109.7 89.3–91.2
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M: male; F: female. * Significant: Differences are considered significant if the 95% confidence intervals of median do not overlap. Retinol equivalents: retinol + 1/6 beta-carotene, tocopherol equivalents: mainly based on alpha-tocopherol without considering further vitamin E vitamers, folate equivalents: to calculate folate equivalents for enriched foods the factor 1.7 is used.
calculated energy and nutrient intake of the respective national dietary surveys with two predecessor versions of BLS II.3 and showed that BLS updates led to nutrient intake deviations up to 20% (Cholmakow-Bodechtel et al., 1997; Linseisen and Wolfram, 1997; Hoffmann et al., 1999). Lu¨hrmann et al. (2002) compared the BLS versions II.2 with II.3 presenting deviations below 10% except for vitamin D, which revealed lower intake levels for men (36%) and for women (19%) applying version II.3.
The alterations in nutrient content of different foods of a database version can have opposed effects as can be seen in the case of iodine. The differences of iodine intake between the studied BLS versions can be traced back to alterations of the iodine data of milk and tea. The iodine data of milk of 7.5 mg/100 g (version II.3), 2.7 mg/100 g (version II.4) and 11.7 mg/100 g (version 3.02) fluctuate mainly due to different literature sources, in which the indirect iodine supplementation via udder disinfections, cleaning
B.M. Hartmann et al. / Journal of Food Composition and Analysis 42 (2015) 26–29
agents, and iodized mineral mixtures as feed additive were considered to a different degree (Renner and Renz-Schauen, 1992; Souci et al., 1998; Hampel et al., 2009). The higher iodine content of milk in version 3.02 is partly compensated by the reduced iodine data of black, fruit, and herbal tea from version II.4 to 3.02 (Heuer et al., 2009). The diverging trend of iodine intake from version II.4 to 3.02 between men and women seems to be due to the higher tea consumption of women. For beta-carotene, retinol, and alpha-tocopherol the higher intake data with version 3.02 compared to version II.3 may mostly be traced back to changed ingredients of BLS recipes often consumed in Germany as well as changes in the beta-carotene content of carrots. The effect of lower calculated retinol equivalent values in comparison to higher nutrient intake data of beta-carotene and retinol between the BLS versions 3.02 and II.4 is caused by a modification of retinol equivalents calculation in BLS version 3.02. Modifications in the nutrient content of mineral water and tap water due to different data sources were mainly responsible for the intake differences of calcium, magnesium, and iron. Technical reasons can also be the cause for nutrient data differences. The difference between alpha-tocopherol intake from version II.4 to 3.02 and the intake of tocopherol equivalents calculated thereof goes back to a software error; as a result the tocopherol equivalents value of margarine was not considered in version 3.02. Nutrient alterations of different database versions may have numerous causes as described. Whenever a single food is identified as the source of intake deviations these are food items with a high consumption in the NVS II study, like milk, tea, and water. If an entire evaluation of nutrient intake with different database versions cannot be performed, a comparison of nutrient data of foods with high consumption may give useful hints to assess effects of different database versions on the energy and nutrient intake in a food consumption study. Ahuja et al. (2006) also show that nutrient alterations of food items with high consumption have a significant impact on nutrient intake.
5. Conclusion The comparison of the nutrient intake of the NVS II participants evaluated with three versions of the BLS shows a strong impact of the used version. In particular alterations of nutrient values of food items with high consumption, like milk, tea, and water have a high impact on the calculated intake. Consequently, for the comparison of the nutrient intake in food consumption studies based on different versions of a food composition database, the knowledge of version differences is of high importance.
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Journal of Food Composition and Analysis journal homepage: www.elsevier.com/locate/jfca
Original Research Article
The German Nutrient Database: Effect of different versions on the calculated energy and nutrient intake of the German population Bernd M. Hartmann *, T. Heuer, I. Hoffmann Max Rubner-Institut, Federal Research Institute of Nutrition and Food, Haid-und-Neu-Str. 9, 76131 Karlsruhe, Germany
A R T I C L E I N F O
A B S T R A C T
Article history: Received 20 December 2013 Received in revised form 25 August 2014 Accepted 12 January 2015 Available online 16 February 2015
The effects of altered data on the nutrient content of food items in a food composition database can be described by calculating and comparing the energy and nutrient intake of a population group with different database versions. To examine the effect of the differences between the German Nutrient Database (BLS) versions II.3, II.4, and 3.02 (generated in 1999, 2006, and 2014), the energy and nutrient intake of a representative sample of the German population (German National Nutrition Survey II (NVS II)) were compared. This comparison reveals that the median intake for most of the studied nutrients differed significantly between the three BLS versions for both sexes, in approximately one fourth of the comparisons more than 10%. The differences are largest for calcium (men: 21.5%; women: 22.5%), magnesium (men: 19.3%; women: 22.1%), and iodine (women: 20.2%) in the comparison of BLS version 3.02 and II.3. In particular changes of nutrient data of food items with high consumption, like milk, tea, and water, have strong effects on the calculated nutrient intake. Since the present study reveals a strong impact of the applied versions of a food composition database on the nutrient intake of food consumption studies, the knowledge of the version differences is of significant importance. ß 2015 Elsevier Inc. All rights reserved.
Keywords: Food composition database Food consumption Nutrient data Nutrient intake Nutrition survey German Nutrient Database Food analysis Food composition
1. Introduction Food composition databases are subject to continuous changes due to successive adjustments of nutrient data to current laboratory analyses and the inclusion of new food items. The effects of altered data on the nutrient content of food items can either be described by the absolute changes introduced or by calculating the energy and nutrient intake of a population group with different database versions. The objective of this article was to compare three different versions of the German Nutrient Database (Bundeslebensmittelschlu¨ssel (BLS)) regarding calculated energy and nutrient intake in a representative sample of the German population. The study was undertaken within the scope of the German National Nutrition Survey II (NVS II). The BLS was developed as a standard instrument for assessing the energy and nutrient intake of epidemiological studies and nutritional surveys in Germany (Dehne et al., 1999). Since 2004 the Max Rubner-Institut (MRI), Federal Research Institute of Nutrition and Food, in Karlsruhe is responsible for its further development and maintenance (Hartmann et al., 2008).
* Corresponding author. Tel.: +49-721-6625269; fax: +49-721-6625552. E-mail address: [email protected] (B.M. Hartmann). http://dx.doi.org/10.1016/j.jfca.2015.01.001 0889-1575/ß 2015 Elsevier Inc. All rights reserved.
The current BLS version 3.02 comprises 14,814 foods available in Germany including unprocessed and processed foods, all described by 131 nutrients. The nutrient values of approximately 1200 predominantly unprocessed foods are based on analysis conducted by the MRI and by national partner institutions as well as public and commercial laboratories. Further data of cooperation partners, like the food composition database Souci–Fachmann–Kraut (SFK) (Kirchhoff, 2002), as well as data published in the scientific literature were included. Nutrient values of processed foods are mostly calculated based on analyzed nutrient values derived from unprocessed foods under consideration of the preparation method. For such calculations, weight yield and nutrient retention factors are used to consider changes during food preparation. The NVS II is a nationwide food consumption study conducted between November 2005 and January 2007 to collect representative data of almost 20,000 German speaking participants (14–80 years) concerning food consumption, nutrient intake, social demographics, health and lifestyle aspects, as well as anthropometric measurements. It was commissioned by the Federal Ministry of Food, Agriculture and Consumer Protection (Heuer et al., 2015; Brombach et al., 2006). At study centers computer assisted personal interviews were conducted to obtain sociodemographic information and data on nutritional behavior. Also a
B.M. Hartmann et al. / Journal of Food Composition and Analysis 42 (2015) 26–29
computer assisted diet history interview was carried out assessing food consumption of the previous four weeks. Additionally, two 24-h recalls and a weighing record were conducted (Heuer et al., 2015; Krems et al., 2006). For the data of all three dietary assessment methods the BLS served as data basis for the calculation of the nutrient intake. To study the effect of different versions of the BLS on the calculated energy and nutrient intake of participants of the NVS II, the BLS versions II.3, II.4 and 3.02 were used (Table 1). From BLS version II.3 to version II.4 the database was extended by over 4000 food items with a focus on processed foods due to the requirements of the NVS II. Additionally, the nutrient retention factors were updated according to European standards (Va´squezCaicedo et al., 2008) and nearly the complete dataset of the SFK database was integrated. For the BLS version 3.02 approximately 250 further food items were incorporated in comparison to version II.4. Updated nutrient analyses were also included. 2. Methods The comparison of the energy and nutrient intake of the three versions of BLS were based on the same food consumption data assessed by diet history interviews of the NVS II. The frequency and quantity of the consumed foods and beverages over the last four weeks of 15,371 German speaking persons (7093 men and 8278 women) between 14 and 80 years of age were conducted using the dietary assessment program DISHES (Dietary Interview Software for Health Examination Studies) (Mensink et al., 1998, 2001) especially modified and adapted to the requirements of the NVS II (Krems et al., 2006). The foods available in the DISHES program were already matched with BLS codes. New or altered foods of different BLS versions were matched using the best possible option in regard to the nutrient content. The methods of the NVS II survey and the data preparation (e.g. data controls for plausibility) are described in detail elsewhere (MRI, 2008). The median of the daily energy and nutrient intake, the relative difference of the median, and the 95% confidence interval of median were calculated with SAS version 9.1 (SAS Institute Inc., Cary, NC, USA). Because of the predominantly skewed distribution of nutrient intake data the median was used. For relative differences and significance, pairwise comparisons between the BLS versions II.4 versus II.3, 3.02 versus II.4, and 3.02 versus II.3 were conducted. Differences are considered to be significant if the 95% confidence intervals do not overlap. Out of the 131 nutrients of the BLS the comparison is conducted for 29 nutrients published in their final report of the NVS II (MRI, 2008). 3. Results For most of the nutrients the intakes calculated with the three BLS versions differ significantly for men and women (percentage of nutrients for which the calculated intakes differ between the compared BLS versions: II.4–II.3: 78%; 3.02–II.4: 64%; 3.02–II.3: 78%) (Table 2). For men and women the incidence of significant differences between the different BLS versions are mostly in concordance except for retinol (version II.4 versus II.3), protein, niacin equivalents, and iodine (3.02 versus II.4), protein, tocopherol equivalents, and vitamin C (3.02 versus II.3) where the intake
Table 1 BLS versions used for data comparison.
Year of publication Number of data sets
BLS II.3
BLS II.4
BLS 3.02
1999 10,653
2006 14,563
2014 14,814
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differences are significant for men only, whereas for fat, vitamin D, vitamin B2, and vitamin B12 (3.02 versus II.3) the intake differences are only significant for women. The nutrients for which intakes differ significantly and continuously throughout all version comparisons are protein, retinol, tocopherol equivalents, niacin equivalents, vitamin C, and iodine for men. Vitamin B2 for women differed significantly as well as intakes of fiber, beta-carotene, alpha-tocopherol, sodium, calcium, magnesium, iron, and zinc for both sexes. No significant intake differences throughout all version comparisons are found for fat intake for men and alcohol intake for both sexes. Throughout all version comparisons significant intake differences of minerals are more consistent than of macronutrients and vitamins (Table 2). Regarding each version comparison BLS version II.4 versus II.3 reveals significant differences in the calculated intake of protein, fiber, vitamins (except for retinol (women) and vitamin D), and all minerals. In the comparison of BLS version 3.02 with II.4 the intakes of energy, protein (men), carbohydrates, fiber, and cholesterol differ significantly as well as the mineral intakes except for potassium and iodine (women). In the comparison of version 3.02 versus II.4 the intakes of fewer vitamins differ significantly than of II.4 versus II.3. The comparison of BLS version 3.02 with II.3 shows significant differences in energy, protein (men), carbohydrates, fat (women), and fiber as well as all mineral intakes. Here most of the vitamins also differ significantly except for vitamin D, vitamin B2, and vitamin B12 for men, tocopherol equivalents and vitamin C for women, and vitamin B6 for both sexes. In approximately one fourth of all version comparisons, the significant differences between the medians of nutrient intake differ more than 10%. The differences are largest in the comparison of version 3.02 and II.3 for calcium (men: 21.5%; women: 22.5%), magnesium (men: 19.3%; women: 22.1%), and iodine (women: 20.2%). Further differences above 10% include beta-carotene (men: +18.5%; women: +19.2%), retinol (men: +18.6%; women: +14.0%), iron (men: 16.3%; women: 18.0%), and alpha-tocopherol (men: +12.6%; women: +13.1%) in the comparison of BLS version 3.02 and II.3. Concerning differences of the medians of the nutrient intake between all version comparisons, no systematic changes can be detected: There are increasing values from BLS version II.3 to II.4 to 3.02 (e.g. retinol and beta-carotene) and decreasing values (e.g. for calcium, magnesium, and iron); there are lower values from version II.3 to II.4 and higher ones from II.4 to 3.02 (e.g. fiber, vitamin C, and zinc) and also higher values from version II.3 to II.4 and lower ones from II.4 to 3.02 (e.g. vitamin B2 and vitamin B6). Comparing BLS versions 3.02 versus II.4 reveals that the nutrient intake of beta-carotene and retinol was higher in version 3.02 while the retinol equivalents showed lower values. The iodine intake from version II.3 to II.4 is lower for both sexes (men: 17.4%; women: 18.9%), while the iodine intake from version II.4 to 3.02 is only higher for men (9.5%). 4. Discussion Adjustments of nutrient data in food composition databases may be described by listing the alterations. However, it is preferable to explore the analysis of the energy and nutrient intake of food consumption data with different versions of a food composition database (Hulshof et al., 1996; Matsuda-Inoguchi et al., 2001; Ahuja et al., 2006). The comparison of energy and nutrient intake of the NVS II participants assessed by diet history method and evaluated with the versions II.3, II.4 and 3.02 of the BLS shows that discrepancies of most nutrient intakes differed significantly and ranged up to 23%. This is in concordance with publications which compared the
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Table 2 Comparison of daily energy and nutrient intake of men and women in the NVS II study, based on the BLS versions II.3, II.4 and 3.02. Median
Nutrient
Energy (kcal) Protein (g) Carbohydrate (g) Fat (g) Alcohol (g) Fiber, total dietary (g) Cholesterol (mg) Retinol equivalents (mg) Retinol (mg) Beta-carotene (mg) Vitamin D (mg) Tocopherol equivalents (mg) Alpha-tocopherol (mg) Vitamin B1 (mg) Vitamin B2 (mg) Niacin equivalents (mg) Niacin (mg) Vitamin B6 (mg) Vitamin B12 (mg) Vitamin C (mg) Folate equivalents (mg) Folate (mg) Sodium (mg) Potassium (mg) Calcium (mg) Magnesium (mg) Iron (mg) Zinc (mg) Iodine (mg)
M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F
Difference (%)
BLS II.3
BLS II.4
BLS 3.02
2427 1831 88.3 65.7 271 219 92.3 67.7 9.00 2.00 26.6 24.6 345 249 1.58 1.42 0.59 0.43 4.05 4.22 2.83 2.21 12.56 11.06 10.60 9.44 1.46 1.11 1.71 1.41 34.74 25.50 18.30 13.15 1.97 1.57 5.60 3.71 136 143 269 239 269 239 3316 2481 3764 3285 1269 1167 518 444 16.0 13.3 12.9 10.2 120.2 113.0
2413 1833 85.3 64.3 270 220 92.5 68.4 9.04 2.05 24.8 23.1 352 254 1.75 1.54 0.64 0.44 4.26 4.41 2.88 2.19 13.72 11.97 11.07 10.06 1.55 1.18 1.85 1.52 36.29 26.67 19.82 14.29 2.25 1.78 5.80 3.96 130 134 283 252 280 249 3216 2379 3612 3140 1052 964 432 361 14.4 11.8 11.6 9.1 99.3 91.6
2490 1891 86.7 65.1 284 231 94.0 69.7 9.02 2.08 26.0 23.7 342 245 1.73 1.52 0.70 0.49 4.80 5.03 2.74 2.06 12.22 10.98 11.94 10.68 1.57 1.19 1.75 1.44 37.22 26.93 20.12 14.27 1.98 1.55 5.67 3.96 145 146 280 253 277 249 3529 2557 3676 3192 996 905 418 346 13.4 10.9 12.3 9.5 108.7 90.2
Significance*
95% Confidence interval
BLS II.4-II.3
BLS 3.02-II.4
BLS 3.02-II.3
0.6 0.1 3.4 2.1 0.4 0.5 0.2 1.0 0.4 2.5 6.8 6.1 2.0 2.0 10.8 8.5 8.5 2.3 5.2 4.5 1.8 0.9 9.2 8.2 4.4 6.6 6.2 6.3 8.2 7.8 4.5 4.6 8.3 8.7 14.2 13.4 3.6 6.7 4.4 6.3 5.2 5.4 4.1 4.2 3.0 4.1 4.0 4.4 17.1 17.4 16.6 18.7 10.0 11.3 10.1 10.8 17.4 18.9
3.2 3.2 1.6 1.2 5.2 5.0 1.6 1.9 0.2 1.5 4.8 2.6 2.8 3.5 1.1 1.3 9.4 11.4 12.7 14.1 4.9 5.9 10.9 8.3 7.9 6.2 1.3 0.8 5.4 5.3 2.6 1.0 1.5 0.1 12.0 12.9 2.2 0.0 11.5 9.0 1.1 0.4 1.1 0.0 9.7 7.5 1.8 1.7 5.3 6.1 3.2 4.2 6.9 7.6 6.0 4.4 9.5 1.5
2.6 3.3 1.8 0.9 4.8 5.5 1.8 3.0 0.2 4.0 2.3 3.7 0.9 1.6 9.5 7.0 18.6 14.0 18.5 19.2 3.2 6.8 2.7 0.7 12.6 13.1 7.5 7.2 2.3 2.1 7.1 5.6 9.9 8.5 0.5 1.3 1.3 6.7 6.6 2.1 4.1 5.9 3.0 4.2 6.4 3.1 2.3 2.8 21.5 22.5 19.3 22.1 16.3 18.0 4.7 6.9 9.6 20.2
BLS II.3
BLS II.4
BLS 3.02
BLS II.4-II.3
BLS 3.02-II.4
BLS 3.02-II.3
2404–2448 1816–1847 87.5–89.0 65.2–66.3 267–273 218–221 91.3–93.3 67.0–68.5 8.66–9.39 1.87–2.10 26.4–26.9 24.3–24.9 342–350 246–252 1.57–1.60 1.40–1.43 0.58–0.60 0.42–0.44 3.98–4.12 4.16–4.29 2.79–2.90 2.16–2.26 12.44–12.68 10.96–11.19 10.51–10.71 9.33–9.53 1.45–1.48 1.10–1.12 1.70–1.73 1.40–1.42 34.41–35.04 25.26–25.70 18.11–18.51 13.05–13.27 1.95–1.99 1.56–1.58 5.54–5.66 3.67–3.76 134–138 141–146 266–272 237–242 266–271 237–242 3284–3345 2463–2501 3731–3795 3257–3313 1255–1282 1156–1179 513–523 441–447 15.8–16.1 13.2–13.5 12.8–13.0 10.1–10.3 119.3–121.4 111.8–114.0
2396–2433 1817–1849 84.4–85.9 63.7–64.9 267–273 219–222 91.4–93.6 67.7–69.2 8.70–9.49 1.93–2.17 24.6–25.1 22.8–23.4 347–356 251–256 1.74–1.78 1.52–1.57 0.63–0.65 0.44–0.45 4.18–4.36 4.34–4.46 2.82–2.94 2.15–2.23 13.58–13.93 11.84–12.11 10.90–11.19 9.94–10.17 1.53–1.57 1.17–1.19 1.83–1.87 1.51–1.54 36.03–36.58 26.44–26.87 19.60–20.07 14.17–14.42 2.22–2.27 1.76–1.80 5.73–5.88 3.92–4.01 128–132 132–136 280–287 250–255 278–283 247–252 3192–3246 2359–2396 3580–3643 3114–3164 1041–1064 957–974 430–436 358–364 14.2–14.5 11.7–11.9 11.5–11.7 9.0–9.2 98.4–100.3 90.6–92.6
2465–2511 1877–1908 86.0–87.4 64.5–65.6 280–287 229–233 92.9–95.2 69.0–70.5 8.68–9.46 1.96–2.19 25.8–26.3 23.5–24.0 338–346 243–248 1.70–1.75 1.50–1.54 0.69–0.72 0.48–0.50 4.71–4.88 4.95–5.11 2.69–2.80 2.02–2.10 12.09–12.37 10.85–11.13 11.80–12.11 10.57–10.83 1.55–1.59 1.18–1.20 1.73–1.77 1.43–1.46 36.92–37.65 26.71–27.12 19.91–20.33 14.15–14.43 1.96–2.00 1.53–1.56 5.60–5.73 3.90–4.01 142–146 144–148 278–283 250–255 274–279 246–252 3492–3561 2534–2580 3642–3706 3164–3219 985–1010 897–913 414–421 344–349 13.3–13.5 10.8–11.0 12.2–12.4 9.4–9.6 107.5–109.7 89.3–91.2
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M: male; F: female. * Significant: Differences are considered significant if the 95% confidence intervals of median do not overlap. Retinol equivalents: retinol + 1/6 beta-carotene, tocopherol equivalents: mainly based on alpha-tocopherol without considering further vitamin E vitamers, folate equivalents: to calculate folate equivalents for enriched foods the factor 1.7 is used.
calculated energy and nutrient intake of the respective national dietary surveys with two predecessor versions of BLS II.3 and showed that BLS updates led to nutrient intake deviations up to 20% (Cholmakow-Bodechtel et al., 1997; Linseisen and Wolfram, 1997; Hoffmann et al., 1999). Lu¨hrmann et al. (2002) compared the BLS versions II.2 with II.3 presenting deviations below 10% except for vitamin D, which revealed lower intake levels for men (36%) and for women (19%) applying version II.3.
The alterations in nutrient content of different foods of a database version can have opposed effects as can be seen in the case of iodine. The differences of iodine intake between the studied BLS versions can be traced back to alterations of the iodine data of milk and tea. The iodine data of milk of 7.5 mg/100 g (version II.3), 2.7 mg/100 g (version II.4) and 11.7 mg/100 g (version 3.02) fluctuate mainly due to different literature sources, in which the indirect iodine supplementation via udder disinfections, cleaning
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agents, and iodized mineral mixtures as feed additive were considered to a different degree (Renner and Renz-Schauen, 1992; Souci et al., 1998; Hampel et al., 2009). The higher iodine content of milk in version 3.02 is partly compensated by the reduced iodine data of black, fruit, and herbal tea from version II.4 to 3.02 (Heuer et al., 2009). The diverging trend of iodine intake from version II.4 to 3.02 between men and women seems to be due to the higher tea consumption of women. For beta-carotene, retinol, and alpha-tocopherol the higher intake data with version 3.02 compared to version II.3 may mostly be traced back to changed ingredients of BLS recipes often consumed in Germany as well as changes in the beta-carotene content of carrots. The effect of lower calculated retinol equivalent values in comparison to higher nutrient intake data of beta-carotene and retinol between the BLS versions 3.02 and II.4 is caused by a modification of retinol equivalents calculation in BLS version 3.02. Modifications in the nutrient content of mineral water and tap water due to different data sources were mainly responsible for the intake differences of calcium, magnesium, and iron. Technical reasons can also be the cause for nutrient data differences. The difference between alpha-tocopherol intake from version II.4 to 3.02 and the intake of tocopherol equivalents calculated thereof goes back to a software error; as a result the tocopherol equivalents value of margarine was not considered in version 3.02. Nutrient alterations of different database versions may have numerous causes as described. Whenever a single food is identified as the source of intake deviations these are food items with a high consumption in the NVS II study, like milk, tea, and water. If an entire evaluation of nutrient intake with different database versions cannot be performed, a comparison of nutrient data of foods with high consumption may give useful hints to assess effects of different database versions on the energy and nutrient intake in a food consumption study. Ahuja et al. (2006) also show that nutrient alterations of food items with high consumption have a significant impact on nutrient intake.
5. Conclusion The comparison of the nutrient intake of the NVS II participants evaluated with three versions of the BLS shows a strong impact of the used version. In particular alterations of nutrient values of food items with high consumption, like milk, tea, and water have a high impact on the calculated intake. Consequently, for the comparison of the nutrient intake in food consumption studies based on different versions of a food composition database, the knowledge of version differences is of high importance.
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