Nutritional Assessment, Sixth Edition PDF

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Nu tri tionCa lc Plus RobERt d.LEE david C.NiEmaN  Confirming pages CHAPTER 5 C omputerized D ietary A nalysis S ystems O utline S tudent L earning O utcomes Introduction: Using Computers in Nutritional After reading this chapter, students will be able to: Assessment 1. Understand the role of computers in nutritional Factors to Consider in Selecting a Computerized assessment. Dietary Analysis System 2. List criteria for selecting a quality computerized Dietary Analysis on the Internet dietary analysis system. Summary 3. Use an Internet-based dietary analysis program. References Assessment Activity 5.1: Analysis of Your 24-Hour Recall on the Internet Assessment Activity 5.2: Internet Sources for Sound Nutrition Information I ntroduction: U sing C omputers to calculate your final 24-hour intake. Next you would have to compare intake to a dietary standard, such as in N utritional A ssessment the RDA/DRI, and express this as a percentage. And Prior to the development of computers and diet analysis you can imagine how much more difficult this process software, the manual nutritional analysis of diets was would be if you were analyzing a 7-day food record in difficult and time consuming. Consider, for example, which nutrient intake would have to be expressed as a the steps you would take to manually calculate intake daily average. of energy, protein, carbohydrate, total fat, calcium, iron, Clearly, computers are perfectly suited to this task vitamin C, and other nutrients from a 24-hour recall of nutrient analysis, which is nothing more than number using nutrient data from a published table. Your first crunching, saving time, labor, and expense while reduc- step would be to find the appropriate food in the table ing error (Figure 5.1).1–5 Hundreds of software programs and then compare the amount you actually ate with the have been developed since the mid-1980s for all sorts portion size listed for the food. If these differed, you of nutrition-related tasks, including analysis of food would have to mathematically adjust all of the nutri- records and food frequency questionnaires, menu plan- ent values before listing them on a spreadsheet table. ning and forecasting, analysis of recipes, food service After doing this for each food in your 24-hour recall, and food management tasks, nutrition education, patient you would have to add all of the values for each nutrient interviews and counseling, and research. 146 lee21332_ch05_146-165.indd 146 20/09/12 6:27 PM  Confirming pages Chapter 5 Computerized Dietary Analysis Systems 147 Nutrient Database The most important consideration to make when select- ing a computerized diet analysis system is its nutrient database.1,2,7 The database must be accurate, well docu- mented, and large enough to meet all intended tasks. Software vendors begin development of their databases with data from the U.S. Department of Agriculture (USDA). The USDA began publishing food composition values in 1896 and has continually revised and expanded its food composition tables ever since.10 The USDA has also contributed to the development of food composi- tion tables for other countries for many years and has participated in the International Network of Food Data Figure 5.1 Systems (INFOODS), organized first in 1984. INFOODS Computers are well suited to the task of nutrient analysis. is a comprehensive effort, under the United Nations Source: Comstock Images/Getty Images. University Food and Nutrition Program and cosponsored by the Food and Agriculture Organization (FAO) of the United Nations, to improve data on the nutrient composi- The purpose of this chapter is to delineate important tion of foods from all parts of the world. See http://www. characteristics of computerized dietary analysis systems fao.org/infoods/ for more information on INFOODS. A to aid you in selecting an appropriate software package link to this and other websites related to computers in for the analysis of food records, food frequency ques- nutritional assessment are available on the Nutritional tionnaires, and recipes. Dietary analysis systems are now Assessment website at www.mhhe.com/lee-nieman6. available on the Internet, and the strengths and weak- nesses of these systems will be described. USDA Nutrient Data Laboratory Descriptions of computer applications in nutrition and dietetics first appeared in the literature in the late 1950s. The Nutrient Data Laboratory (NDL) of the USDA is one Computer hardware cost is no longer the prohibitive factor of seven units in the Beltsville Human Nutrition Research it once used to be, and most hospitals, clinics, businesses, Center (BHNRC) of the Agricultural Research Service and educational facilities provide personal computer work (ARS). NDL has an interdisciplinary staff comprised of stations for their employees. Computerized dietary intake nutritionists, food technologists, and computer special- analysis is an important skill for dietitians and nutrition- ists. The mission of the NDL is to develop authoritative ists to master. food composition databases and state-of-the-art methods to acquire, evaluate, compile, and disseminate composi- tion data on foods available in the United States. As part F actors to C onsider in of its mission, the NDL operates the National Nutrient Databank, a computerized information system for storing S electing a C omputerized and summarizing data on the composition of foods. See D ietary A nalysis S ystem Box 5.1 for a glossary of terms and acronyms used by Hundreds of dietary analysis software packages are the NDL. available, ranging from simplified programs designed The USDA NDL develops and maintains a number for elementary school students to comprehensive pro- of databases, including the USDA Nutrient Database for grams designed for researchers. In selecting a dietary Standard Reference (SR). SR nutrient data serve as the analysis program, the first step is to establish the major core for most commercial and many foreign databases needs for obtaining the software, with specific tasks and are the numerical foundation of essentially all public defined. Once this has been accomplished, choose a and private work in the field of human nutrition. dietary analysis system that is suitable to these needs and tasks. For example, a research professor in a uni- USDA Nutrient Databases versity nutrition department will probably need a com- The Nutrient Databank System (NDBS) is a repository pletely different type of computerized dietary analysis for information on up to 146 nutrients and food compo- system than a public health nutritionist working with nents found in more than 7900 foods. Until 1992, most of pregnant women at nutritional risk in a county health this information was published in the form of Agriculture department. Handbook 8 (AH-8). However, AH-8 is no longer available In comparing software programs, dietitians and in printed form. To facilitate dissemination, the informa- other health professionals should consider aspects of the tion contained in AH-8 is provided in the SR at the website database, program operation, and system output.6–9 of the USDA NDL (http://www.ars.usda.gov/nutrientdata). lee21332_ch05_146-165.indd 147 20/09/12 6:27 PM  Confirming pages 148 Nutritional Assessment Box 5.1 Acronyms and Documentation Terms The following is a list of definitions of acronyms and terms and pasta (20), beverages (14), used in this chapter and in documentation for the USDA vegetables (11). National Nutrient Database for Standard Reference. Food Group Code Two-digit numeric code Analytical Data from laboratory analysis of identifying individual Food one or more food samples Groups. Food Groups are further classified by subcodes, AOAC Association of Official Analytical to produce a four-digit numeric Chemists, independent scientific code. For example, fresh pork organization that published a is 1010, while cured pork reference of methods used in is 1020. Food group codes analyzing the composition of foods. are independent of NDB AMS Agricultural Marketing Service, numbers. USDA Formulation The estimated proportion by ARS Agricultural Research Service, weight of ingredients in a USDA multi-ingredient commercial Atwater System System developed by W. O. Atwater food item when other to calculate the energy contributed characteristics of the food by protein, fat, and carbohydrates item are known or can be set. to foods. Characteristics that may be known or can be set include: BHNRC Beltsville Human Nutrition order of predominance of Research Center ingredients, retention codes, Calculated Nutrient values computed or target moisture level of estimated by mathematical individual ingredients and adjustment. Normalizing nutrients final product, and lower and to an average moisture or fat upper bounds on the proportion value, use of retention factors, and of any individual ingredient. substitution of similar ingredients As a minimum, to derive a in a formulation or recipe are formulation, some nutrient values examples of calculated values. must be known and flagged for CFR Code of Federal Regulations matching. CNPP Center for Nutrition Policy and FSIS Food Safety and Inspection Service, Promotion, USDA. Has information USDA on the Dietary Guidelines, and Handbook 8 (AH-8) USDA Agriculture Handbook MyPyramid.gov. No. 8, Composition of Foods Derivation code A 4-character, alphabetic code HG-72 Home and Garden Bulletin No. 72, used to document Standard Nutritive Value of Foods Reference nutrient data source and quality. Household measure Standard weight (sometimes with dimensions) or portion of Discontinued item Food product no longer sold or individual food. Sometimes called available commercially; item serving size. removed from Standard Reference Database. Imputed Nutrient values developed when analytical values are FDA Food and Drug Administration, unavailable. Nutrient values U.S. Department of Health and from another form of the same Human Services food, or another species of the same FNIC Food and Nutrition Information genus are examples of imputed Center. One of NAL’s information values. centers. INFOODS International Network of Food Data Food Group NDL categorizes foods into similar Systems groups and assigns a Food Group Code, such as cereal grains Item Individual food or food product lee21332_ch05_146-165.indd 148 20/09/12 6:27 PM  Confirming pages Chapter 5 Computerized Dietary Analysis Systems 149 Box 5.1 Continued Key Foods Identification of foods most highly expressed in household volume consumed and also best sources measure units such as cups and of nutrients deemed important tablespoons or may be expressed to national dietary health. Key as gram weights. The term “recipe” Foods are identified as those foods is generally applied to a food contributing up to 75% of any one item prepared from component nutrient. Key Foods are used by ingredients in a household or NDL to set priorities for our nutrient institutional setting. The term may analysis contracts. also apply to a commercial multi- Label Data printed on a food label, as ingredient food item for which supplied by its manufacturer. The the amounts of ingredients are values are primarily company set, rather than estimated (e.g., by analytical or imputed; however, the Standards of Identity). values have been rounded and/or Refuse Portion of food removed before adjusted to provide uniform serving consumption (meat bones, fruit size weights. pits, etc.). NAL National Agricultural Library, RM Reference Material used for USDA located in Beltsville, evaluating the reliability of Maryland analytical methods NCI National Cancer Institute, NIH Source code One-character numeric code to NHANES National Health and Nutrition document source of nutrient data. Examination Survey. SRM Standard Reference Material from Conducted by the National NIST used for evaluating the Center for Health Statistics, U.S. reliability of analytical methods Department of Health and Human Standard Reference USDA National Nutrient Database Services (SR) for Standard Reference NHLBI National Heart, Lung and Blood Tagname INFOODS Tag Names identify Institute, NIH individual nutrients for NNDB USDA National Nutrient Databank international interchange of nutrient data. NDB No. Identification number for food item in USDA Nutrient Database UPC Universal Product Code is a unique product identification NIH National Institutes of Health number found on most product NIST National Institute of Standards and labels, represented by bar and Technology, U.S. Department of number codes. Commerce USDA U.S. Department of Agriculture NLEA National Labeling and Education USDA Commodity Foods donated, or available for Act of 1990. Refers to food- donation, by the Department labeling regulations promulgated by under authorizing legislation, for the FDA. use in any state in child nutrition NTIS National Technical Information programs, nonprofit summer camps Service, U.S. Department of for children, charitable institutions, Commerce nutrition programs for the elderly, PDS Primary Data Set for USDA the Commodity Supplemental Nationwide Food Surveys. No Nutrition Program for Women, longer a separate database, but Infants, and Children (WIC), part of SR. the Food Distribution Programs Recipe The known weight or measure on Indian Reservations, and the of ingredients in a multi- assistance of needy people. ingredient food item. Amounts of USDHHS U.S. Department of Health and ingredients may be Human Services Source: USDA Nutrient Data Laboratory, Agricultural Research Service. http://www.ars.usda.gov. lee21332_ch05_146-165.indd 149 20/09/12 6:27 PM  Confirming pages 150 Nutritional Assessment The SR includes the sections and supplements of AH-8 the database may be based on the results of laboratory and has added new food group sections including “meals, analyses or calculated by using appropriate algorithms, entrees, and sidedishes,” “snacks,” “ethnic foods,” and factors, or recipes, as indicated by the source code in the “restaurant foods.” Nutrient Data file. As information is updated, new versions of the SR When nutrient data for prepared or cooked products database are released. Release 24 (SR24) was published are unavailable or incomplete, nutrient values are cal- in September 2011 and contained data on 7900 food items culated from comparable raw items or by recipe. When and up to 146 nutrients and food components. Table 5.1 values are calculated in a recipe or from the raw item, lists the 25 food groups included in SR24. appropriate nutrient retention and food yield factors are Data for SR24 were compiled from published and applied. To obtain the content of nutrient per 100 g of unpublished sources. Published sources included the cooked food, the nutrient content per 100 g of raw food scientific literature. Unpublished data were from the is multiplied by the nutrient retention factor and, where food industry, other government agencies, and research appropriate, adjustments are made for fat and moisture conducted under contracts initiated by the Agricultural gains and losses. Nutrient retention factors are based on Research Service (ARS). These analyses are currently data from USDA research contracts, research reported in conducted under the National Food and Nutrient Analysis the literature, and USDA publications. Program (NFNAP), in cooperation with the National Every food item may not contain a complete nutrient Cancer Institute and 16 other offices and institutes of the profile. Thus, blanks in the SR24 database are regarded National Institutes of Health. Data from the food industry as “missing data” or an indication of lack of reliable data. represent the nutrient content of a specific food or food Table 5.2 summarizes the number of foods in the SR24 product at the time the data are sent to NDL. Values in database containing selected nutrients. Nutrient values per 100 grams and in edible portions of common measures (e.g., cup, tablespoon, or teaspoon) are contained in SR24. Other data are listed to further Table 5.1 USDA Nutrient Database for describe the mean value including the standard error, Standard Reference, Release 24 number of data points upon which the mean is based, Food Group the derivation code, and the source code. The derivation code documents the nutrient data source and quality. An 01 Dairy and Egg Products “A,” for example, means “analytical data.” The source 02 Spices and Herbs code field indicates how the data value was determined 03 Baby Foods (for example, analytical, calculated, or assumed zero). 04 Fats and Oils Several support files that accompany SR24 provide 05 Poultry Products more specific information on the source code, descrip- 06 Soups, Sauces, and Gravies tive information about the food items, and descriptions of 07 Sausages and Luncheon Meats inedible material (for example, seeds, bone, skin). 08 Breakfast Cereals Table 5.3 gives an example of the data that are avail- 09 Fruits and Fruit Juices able for each food in SR24. Analytical values represent 10 Pork Products the total amount of the nutrient present in the edible por- 11 Vegetables and Vegetable Products tion of the food, including any nutrients added in process- 12 Nut and Seed Products ing. The values do not necessarily represent the nutrient 13 Beef Products amounts available to the body. 14 Beverages The USDA Food and Nutrient Database for Dietary 15 Finfish and Shellfish Products Studies (FNDDS) is a database of over 7000 foods, nutri- 16 Legumes and Legume Products ent values, and weights for typical food portions (formerly 17 Lamb, Veal, and Game Products called Survey Nutrient Database). The FNDDS is used to 18 Baked Products process data from the survey What We Eat in America, 19 Sweets the dietary intake component of the National Health and 20 Cereal Grains and Pasta Nutrition Examination Survey (NHANES). The FNDDS 21 Fast Foods is available for use in other dietary research studies and 22 Meals, Entrees, and Sidedishes can be downloaded free from the website of USDA’s 25 Snacks Food Surveys Research Group (FSRG), who develops 35 Ethnic Foods and maintains the FNDDS. The FNDDS is designed for 36 Restaurant Foods the coding and analysis of food consumption data. Many of the foods in FNDDS are mixtures that are not available Source: U.S. Department of Agriculture, Agricultural Research Service. 2011. in the SR. The SR is the source of the nutrient values for USDA Nutrient Database for Standard Reference, Release 24. http://www.ars. usda.gov/nutrientdata. foods in FNDDS, including mixed foods whose nutrient lee21332_ch05_146-165.indd 150 20/09/12 6:27 PM  Confirming pages Chapter 5 Computerized Dietary Analysis Systems 151 Table 5.2 Number of Foods in the Database (n 5 7906) Containing a Value for the Specified Nutrient Nutr. No. Nutrient Number of foods Nutr. No. Nutrient Number of foods 255 Water* † 7901 573 Vitamin E, added* 4070 208 Energy* † 7906 341 b-tocopherol 1421 203 Protein* † 7906 342 g-tocopherol 1416 204 Total lipid (fat)* † 7906 343 d-tocopherol 1401 205 Carbohydrate, by 7906 328 Vitamin D 4635 difference* † (D2 1 D3), mg * † 207 Ash† 7899 325 Vitamin D2 (ergocalciferol) 43 291 Total dietary fiber* † 7217 326 Vitamin D3 1325 269 Total sugars* † 5765 (cholecalciferol) 210 Sucrose 1250 324 Vitamin D, IU† 4636 211 Glucose 1252 428 Menaquinone-4 465 212 Fructose 1251 429 Dihydrophylloquinone 1284 213 Lactose 1232 606 Total saturated fatty acids* † 7574 214 Maltose 1220 607 4:0 4982 287 Galactose 1098 608 6:0 5027 209 Starch 837 609 8:0* 5286 301 Calcium* † 7771 610 10:0* 5752 303 Iron* † 7784 611 12:0 6021 304 Magnesium* † 7728 696 13:0 246 305 Phosphorus* † 7325 612 14:0 6397 306 Potassium* † 7486 652 15:0 1666 307 Sodium* † 7823 613 16:0* 6615 309 Zinc* † 7258 653 17:0 1881 312 Copper* 7050 614 18:0* 6603 315 Manganese† 6215 615 20:0 1980 317 Selenium* † 6488 624 22:0 1625 313 Fluoride 561 654 24:0 1353 401 Vitamin C, total ascorbic 7468 645 Total monounsaturated 7209 acid* † fatty acids* † 404 Thiamin* † 7231 625 14:1 1885 405 Riboflavin* † 7253 697 15:1 1395 406 Niacin* † 7226 626 16:1 undifferentiated* 6361 410 Pantothenic acid† 6263 673 16:1 cis 573 415 Vitamin B6* † 7062 662 16:1 trans 450 417 Folate, total* † 6839 687 17:1 1599 431 Folic acid* † 6489 617 18:1 undifferentiated* 6630 432 Food folate* † 6677 674 18:1 cis 1038 435 Folate (DFE)* † 6483 653 18:1 trans 1052 421 Choline, total* † 4157 859 18:1-1 trans trans 132 454 Betaine 1808 628 20:1* 5743 418 Vitamin B12* † 6974 630 22:1 undifferentiated* 5201 578 Vitamin B12, added* 4236 676 22:1 cis 476 320 Vitamin A (RAE)* † 6632 664 22:1 trans 369 319 Retinol* † 6409 671 24:1 cis 681 321 b-carotene* † 4757 646 Total polyunsaturated fatty 7216 322 a-carotene* † 4672 acids* † 334 b-cryptoxanthin* † 4663 618 18:2 undifferentiated* 6647 318 Vitamin A (IU)† 7476 675 18:2 n-6 cis, cis 996 337 Lycopene* † 4632 656 18:2 i (other isomers) 66 338 Lutein 1 zeaxanthin* † 4611 659 18:2 trans, trans 217 323 a-tocopherol 4908 665 18:2 trans, not further 508 (vitamin E)* † defined continued lee21332_ch05_146-165.indd 151 20/09/12 6:27 PM  Confirming pages 152 Nutritional Assessment Table 5.2 Number of Foods in the Database (n 5 7906) Containing a Value for the Specified Nutrient—continued Nutr. No. Nutrient Number of foods Nutr. No. Nutrient Number of foods 619 18:3 undifferentiated* 6545 638 Stigmasterol 128 670 18:2 conjugated linoleic 665 639 Campesterol 127 acid (CLAs) 641 b-sitosterol 128 851 18:3 n-3 cis, cis, cis (ALA) 117 501 Tryptophan 4817 685 18:3 n-6 cis, cis, cis 1002 502 Threonine 4863 856 18:3 i (other isomers) 101 503 Isoleucine 4867 627 18:4* 5002 504 Leucine 4866 672 20:2 n-6 cis, cis 1663 505 Lysine 4880 689 20:3 undifferentiated 1484 506 Methionine 4877 852 20:3 n-3 369 507 Cystine 4805 853 30-3 n-6 451 508 Phenylalanine 4863 620 20:4 undifferentiated* 5756 509 Tyrosine 4832 855 20:4 n-6 9 510 Valine 4867 629 20:5 n-3* (EPA) 5170 511 Arginine 4852 857 21:5 104 512 Histidine 4860 858 22:4 516 513 Alanine 4806 631 22:5 n-3* (DPA) 5120 514 Aspartic acid 4809 621 22:6 n-3* (DHA) 5165 515 Glutamic acid 4809 605 Fatty acids, total trans 2149 516 Glycine 4806 693 Fatty acids, total 1020 517 Proline 4794 trans-monoenoic 518 Serine 4807 695 Fatty acids, total 769 521 Hydroxyproline 1114 trans-polyenoic 221 Alcohol* 4831 601 Cholesterol*† 7575 262 Caffeine* 4597 636 Phytosterols 516 263 Theobromine* 4573 *Indicates the 65 nutrients included in the USDA Food and Nutrient Database for Dietary Studies (FNDDS). † Nutrients included in the Abbreviated file (p. 34). Source: U.S. Department of Agriculture, Agricultural Research Service, USDA Nutrient Data Laboratory, 2011. USDA National Nutrient Database for Standard Reference, Release 24. USDA Nutrient Data Laboratory website: http://www.ars.usda.gov/nutrientdata values are calculated using SR items as ingredients. The Criteria for Developing High-Quality Databases FNDDS portion weights are for the types of portion size Developers of commercial computerized dietary analysis that survey respondents report. For that reason, FNDDS systems are faced with several challenges in formulating includes additional weights for common food portion high-quality databases.6–9 Box 5.2 summarizes a check- sizes that are not available in the SR. There are no miss- list of criteria in choosing a good nutrient database. ing values in the FNDDS, and each food has values The first challenge is to decide on how many foods for energy and 63 nutrients and food components. The and nutrients to include in the software program. Even FNDDS is updated every 2 years in conjunction with data though the USDA SR provides values on more than 140 released from What We Eat in America, NHANES. nutrients and food components for more than 7900 foods, Other data sets developed by NDL include retention relatively few recipes and name brand foods are included. tables and tables of special interest on nutrients such as And, as emphasized in Table 5.2, a number of foods also choline, added sugars, flavonoids, fluoride, isoflavones, have missing values for some nutrients, such as manga- oxalic acid content of selected vegetables, oxygen radical nese, selenium, vitamin E, and newly introduced nutri- absorbance capacity (ORAC), and proanthocyanidins. ents such as individual sugars and tocopherols. (See http://www.ars.usda.gov/ba/bhnrc/ndl) The USDA Although the USDA releases substantial amounts of sponsors a yearly conference, the “National Nutrient new or updated information each year, the typical super- Databank Conference,” to facilitate cooperation among market contains 15,000 to 60,000 brand name food prod- the USDA, university researchers, food companies, and ucts. The best software vendors attempt to provide their others interested in nutrient data. customers with database updates at least once a year, lee21332_ch05_146-165.indd 152 20/09/12 6:27 PM  Confirming pages Chapter 5 Computerized Dietary Analysis Systems 153 Table 5.3 An Example of the Nutrient Data Available for Each Food in SR24 NDB No. 09003 Apples, raw, with skin (1) Malus domestica Includes USDA commodity food A343 Refuse: 10% Core and stem Amount in Edible Portion of Amount in 100 Grams of Edible Portion Common Measures of Food Number of Data Deriv Source Confidence Nutrients and Units Mean Std. Error Points Code Code Code Measure 1 Measure 2 Measure 3 Proximates: Water g 85.56 0.241 38 A 1 106.95 93.26 190.80 Energy kcal 52 0 NC 4 65 57 116 Energy kj 218 0 NC 4 272 237 486 Protein (N 3 6.25) g 0.26 0.019 29 A 1 0.33 0.29 0.59 Total lipid (fat) g 0.17 0.011 35 A 1 0.22 0.19 0.39 Ash g 0.19 0.018 29 A 1 0.24 0.21 0.43 Carbohydrate, by g 13.81 0 NC 4 17.26 15.05 30.80 difference Fiber, total dietary g 2.4 0.276 29 A 1 2.9 2.6 5.2 Sugars, total g 10.39 0.112 25 A 1 12.99 11.32 23.17 Sucrose g 2.07 0.049 25 A 1 2.58 2.25 4.61 Glucose (dextrose) g 2.43 0.031 25 A 1 3.03 2.65 5.41 Fructose g 5.90 0.059 25 A 1 7.37 6.43 13.15 Lactose g 0.00 0.000 25 A 1 0.00 0.00 0.00 Maltose g 0.00 0.000 25 A 1 0.00 0.00 0.00 Galactose g 0.00 0.000 25 A 1 0.00 0.00 0.00 Starch g 0.05 0.000 10 A 1 0.07 0.06 0.12 Minerals: Calcium, Ca mg 6 0.340 26 A 1 7 6 13 Iron, Fe mg 0.12 0.009 16 A 1 0.15 0.13 0.28 Magnesium, Mg mg 5 0.073 26 A 1 6 6 12 Phosphorus, P mg 11 0.337 23 A 1 14 12 25 Potassium, K mg 107 2.211 26 A 1 134 117 239 Sodium, Na mg 1 0.071 6 A 1 2 1 3 Zinc, Zn mg 0.04 0.004 26 A 1 0.05 0.04 0.08 Copper, Cu mg 0.027 0.001 13 A 1 0.034 0.030 0.060 Manganese, Mn mg 0.035 0.002 26 A 1 0.044 0.038 0.079 Selenium, Se mcg 0.0 0.000 7 A 1 0.0 0.0 0.0 Vitamins: Vitamin C, total mg 4.6 0.470 3 A 1 5.7 5.0 10.2 ascorbic acid Thiamin mg 0.017 0.002 23 A 1 0.022 0.019 0.039 Riboflavin mg 0.026 0.004 20 A 1 0.032 0.028 0.058 Niacin mg 0.091 0.006 13 A 1 0.114 0.099 0.203 Pantothenic acid mg 0.061 0.012 23 A 1 0.076 0.066 0.135 Vitamin B6 mg 0.041 0.001 23 A 1 0.051 0.045 0.092 Folate, total mcg 3 0.611 23 1 4 3 6 Folic acid mcg 0 0 Z 7 0 0 0 Folate, food mcg 3 0.611 23 1 4 3 6 continued lee21332_ch05_146-165.indd 153 20/09/12 6:27 PM  Confirming pages 154 Nutritional Assessment Table 5.3 An Example of the Nutrient Data Available for Each Food in SR24—continued NDB No. 09003 Apples, raw, with skin (1) Malus domestica Includes USDA commodity food A343 Refuse: 10% Core and stem Amount in Edible Portion of Amount in 100 Grams of Edible Portion Common Measures of Food Number of Data Deriv Source Confidence Nutrients and Units Mean Std. Error Points Code Code Code Measure 1 Measure 2 Measure 3 Folate, DFE mcg_DFE 3 0 NC 4 4 3 6 Choline, total mg 3.4 0 AS 1 4.3 3.8 7.7 Betaine mg 0.1 1 A 1 0.1 0.1 0.2 Vitamin B12 mcg 0.00 0 Z 7 0.00 0.00 0.00 Vitamin B12, added mcg 0.00 0 Z 7 0.00 0.00 0.00 Vitamin A, RAE mcg_RAE 3 0.155 14 A 1 3 3 6 Retinol mcg 0 0 Z 7 0 0 0 Carotene, beta mcg 27 1.662 14 A 1 34 30 61 Carotene, alpha mcg 0 0.000 14 A 1 0 0 0 Cryptoxanthin, mcg 11 0.926 14 A 1 13 12 24 beta Vitamin A, IU IU 54 3.108 14 A 1 68 59 121 Lycopene mcg 0 0.000 14 A 1 0 0 0 Lutein 1 zeaxanthin mcg 29 1.132 14 A 1 37 32 66 Vitamin E mg 0.18 10 A 1 0.23 0.20 0.41 (alpha-tocopherol) Vitamin E, added mg 0.00 0 Z 7 0.00 0.00 0.00 Tocopherol, beta mg 0.00 10 A 1 0.00 0.00 0.00 Tocopherol, gamma mg 0.00 10 A 1 0.00 0.00 0.00 Tocopherol, delta mg 0.00 10 A 1 0.00 0.00 0.00 Vitamin D IU Vitamin K mcg 2.2 0.079 20 A 1 2.8 2.4 4.9 (phylloquinone) Lipids: Fatty acids, total g 0.028 0 NC 4 0.036 0.031 0.063 saturated 4:0 g 0.000 0 1 0.000 0.000 0.000 6:0 g 0.000 0 1 0.000 0.000 0.000 8:0 g 0.000 0 1 0.000 0.000 0.000 10:0 g 0.000 0 1 0.000 0.000 0.000 12:0 g 0.000 1 1 0.001 0.001 0.001 13:0 g 14:0 g 0.001 1 1 0.001 0.001 0.002 15:0 g 16:0 g 0.024 4 1 0.029 0.026 0.052 17:0 g 18:0 g 0.003 4 1 0.004 0.004 0.008 20:0 g 22:0 g 24:0 g continued lee21332_ch05_146-165.indd 154 20/09/12 6:27 PM  Confirming pages Chapter 5 Computerized Dietary Analysis Systems 155 Table 5.3 An Example of the Nutrient Data Available for Each Food in SR24—continued NDB No. 09003 Apples, raw, with skin (1) Malus domestica Includes USDA commodity food A343 Refuse: 10% Core and stem Amount in Edible Portion of Amount in 100 Grams of Edible Portion Common Measures of Food Number of Data Deriv Source Confidence Nutrients and Units Mean Std. Error Points Code Code Code Measure 1 Measure 2 Measure 3 Fatty acids, total g 0.007 0 NC 4 0.009 0.008 0.016 monounsaturated 14:1 g 15:1 g 16:1 undifferentiated g 0.000 1 1 0.001 0.001 0.001 17:1 g 18:1 undifferentiated g 0.007 4 1 0.009 0.007 0.015 20:1 g 0.000 0 1 0.000 0.000 0.000 22:1 undifferentiated g 0.000 0 1 0.000 0.000 0.000 24:1 c g Fatty acids, total g 0.051 0 NC 4 0.064 0.056 0.115 polyunsaturated 18:2 undifferentiated g 0.043 4 1 0.053 0.046 0.095 18:3 undifferentiated g 0.009 4 1 0.011 0.010 0.020 18:4 g 0.000 0 1 0.000 0.000 0.000 20:2 n-6 c,c g 20:3 undifferentiated g 20:4 undifferentiated g 0.000 0 1 0.000 0.000 0.000 20:5 n-3 g 0.000 0 1 0.000 0.000 0.000 22:5 n-3 g 0.000 0 1 0.000 0.000 0.000 22:6 n-3 g 0.000 0 1 0.000 0.000 0.000 Fatty acids, total trans g Cholesterol mg 0 0 Z 7 0 0 0 Phytosterols mg 12 0 1 15 13 27 Amino Acids: Tryptophan g 0.001 0 A 1 0.001 0.001 0.002 Threonine g 0.006 0 A 1 0.008 0.007 0.014 Isoleucine g 0.006 0 A 1 0.007 0.006 0.013 Leucine g 0.013 0 A 1 0.016 0.014 0.029 Lysine g 0.012 0 A 1 0.015 0.013 0.027 Methionine g 0.001 0 A 1 0.001 0.001 0.002 Cystine g 0.001 0 A 1 0.001 0.001 0.002 Phenylalanine g 0.006 0 A 1 0.008 0.007 0.014 Tyrosine g 0.001 0 A 1 0.001 0.001 0.002 Valine g 0.012 0 A 1 0.015 0.013 0.026 Arginine g 0.006 0 A 1 0.007 0.006 0.012 Histidine g 0.005 0 A 1 0.006 0.005 0.011 Alanine g 0.011 0 A 1 0.014 0.012 0.025 Aspartic acid g 0.070 0 A 1 0.087 0.076 0.156 Glutamic acid g 0.025 0 A 1 0.031 0.027 0.055 continued lee21332_ch05_146-165.indd 155 20/09/12 6:27 PM  Confirming pages 156 Nutritional Assessment Table 5.3 An Example of the Nutrient Data Available for Each Food in SR24—continued NDB No. 09003 Apples, raw, with skin (1) Malus domestica Includes USDA commodity food A343 Refuse: 10% Core and stem Amount in Edible Portion of Amount in 100 Grams of Edible Portion Common Measures of Food Number of Data Deriv Source Confidence Nutrients and Units Mean Std. Error Points Code Code Code Measure 1 Measure 2 Measure 3 Glycine g 0.009 0 A 1 0.011 0.009 0.019 Proline g 0.006 0 A 1 0.008 0.007 0.014 Serine g 0.010 0 A 1 0.013 0.011 0.023 Hydroxyproline g Others: Alcohol, ethyl g 0.0 0 7 0.0 0.0 0.0 Caffeine mg 0 0 Z 7 0 0 0 Theobromine mg 0 0 Z 7 0 0 0 Blanks in the Mean column indicate lack of reliable data. The Number of Data Points column is the number of analyses upon which the mean is based. Number of Data Points of zero indicates the mean was either calculated (as for Energy) or estimated, usually from a recipe, another form of the same food, or similar food. Common Measures: Measure 1 5 125g: 1 cup, quartered or chopped Measure 2 5 109g: 1 cup slices Measure 3 5 223g: 1 large (3-1/4" dia) Footnotes: 1 Based on analytical data for red, delicious, golden delicious, gala, Granny Smith, and fuji varieties. 2 3 and 5 pound bags of apples typically contain small and extra small sizes. Calories Factors: Protein 3.36 Fat 8.37 Carbohydrate 3.6 Food Group: 09 Fruits and Fruit Juices Source: USDA National Nutrient Database for Standard Reference, Release 24 (2011). they use non-USDA sources to give information on brand vitamin K, biotin) are unknown for many foods. Thus, name and ethnic foods, and they fill in missing data. with an increasing number of food components, the soft- The total number of food items included in a data- ware package developer has to cope with an expanding base is important to ensure that substitution (choosing a bank of missing values. If missing data are entered as similar food when the specific food is not in the database) zero and not flagged (indicated by the software as miss- is kept at a minimum.11–13 For example, if a patient in ing), nutrient totals will appear lower than they actually a cardiac rehabilitation program provides a 3-day food are. During counseling sessions with patients or clients, record that includes several low-fat items not found in some confusion can develop because, for many of these the database, some less than ideal substitutions with other nutrients, low values represent a “database deficiency,” similar foods will have to be made. However, more is not not a deficiency in the diet of the patient. The best soft- necessarily better. As the database size increases, the dif- ware packages will give information on how many miss- ficulty in finding the right food and the processing time ing values are present for each nutrient or will warn the can increase. dietitian or user about the issue. Some software packages report having more than One way to judge the quality of a computerized 100 nutrients and food components in their databases, diet analysis system is to determine how the developer while others contain fewer than 30. Again, more is not met the challenge of missing data in the management of necessarily better, because values for certain trace min- its database.7–9 Some developers go to unusual lengths erals (e.g., chromium, selenium, molybdenum, manga- to ensure that missing values are substituted with either nese), amino acids, some fatty acids, and some vitamins non-USDA data or imputed values. Many food compa- (e.g., alpha-tocopherol, total tocopherol, vitamin D, nies provide information on the nutrient content of their lee21332_ch05_146-165.indd 156 20/09/12 6:27 PM  Confirming pages Chapter 5 Computerized Dietary Analysis Systems 157 Box 5.2 Basic Checklist for Computerized Dietary Analysis Systems 1. The Nutrient Database Can the portion size or volume and weight measure How many food items are in the database? Aim for be easily adapted to conform to those listed in your more than 15,000 to minimize food substitution food record? decisions during data entry. Can you view the nutrients for a food item during Does the database contain a significant number of data entry? Access to this information makes food brand name items, fast foods, baby foods, and ethnic substitution decisions easier. foods? If the database contains only the 7900 foods How easy is it to edit the food list during entry? found in the USDA SR, few brand name foods will You are bound to make mistakes during data entry, be available, and considerable food substitution and the best programs make it easy to correct decisions will have to be made. your errors. How many nutrients and nutrient factors does Can you easily average multiple days of dietary input the software program analyze for? It should at to derive a daily nutrient intake average? a minimum include the 12 basic components Does the software package allow you to compare (energy sources, water, cholesterol, lipids, dietary dietary intake with a wide variety of standards, such fiber, and caffeine), 12 vitamins, and 9 minerals as the RDA/DRI, Canadian RNI, and USDA Dietary available from the USDA SR and FNDDS. Ensure Guidelines for Ame