Dietary Questionnaire for Epidemiological Studies (DQES v2)

User Information Guide

2009

Cancer Epidemiology Centre Nutritional Assessment Office

Cancer Council Victoria 1 Rathdowne Street

Carlton Vic 3053

ffq@cancervic.org.au Phone: 03 9635-5603

Fax: 03 9635-5330 http://www.cancervic.org.au/dqes

Updated: January 2009

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TABLE OF CONTENTS

1 INTRODUCTION.........................................................................................................................3

2 QUESTIONNAIRE EVALUATION..............................................................................................5

3 SOURCES OF NUTRITIONAL DATA........................................................................................5

4 ADMINISTRATION OF THE QUESTIONNAIRE........................................................................6

5 ALCOHOL CALCULATIONS IN THE FFQ................................................................................8

6 SCANNING ERRORS.................................................................................................................8

7 BARCODE LABELS...................................................................................................................9

8 OUTPUT FROM SCANNED QUESTIONNAIRES .....................................................................10

9 REFERENCING THE FOOD FREQUENCY QUESTIONNAIRE ...............................................18

10 PROCEDURE FOR PROCESSING QUESTIONNAIRES..........................................................18

11 CONTACT US.............................................................................................................................19

12 REFERENCES............................................................................................................................19

13 ORDER/MOU FORM (APPENDIX A).........................................................................................20

14 HOW TO FILL IN A QUESTIONNAIRE (APPENDIX B)............................................................22

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1 Introduction Food frequency questionnaires have developed as a means of assessing usual diet in large-scale epidemiological studies (1), and are not intended to replace careful diet histories or recalls in one-to-one nutritional counselling (2). In most epidemiological applications the aim of the FFQ is to rank people according to intake, although for translation into public health recommendations it is necessary to measure absolute intakes. In FFQ’s it is necessary to compromise between including enough foods to reflect intake accurately and not including so many that participants do not complete the questionnaire (1). Because FFQ’s usually ask about intake over the previous 12 months, and may not be sensitive to small changes in intake, they may not be appropriate for measuring short-term dietary change in response to interventions. In a study of 397 women, FFQ’s and four 24-hour recalls were used to measure dietary change from baseline to 1 year post-intervention. Both instruments were able to detect dietary change in the desired direction, over this period (3), but the FFQ was modified specifically “to ensure that the food items and dietary practices associated with the prescribed intervention were adequately represented in the instrument”, and the reference period was only the last 3 months. If, for example the intervention is about reducing fat intake by trimming fat from meat and skin from chicken, these behaviours need to be included on the FFQ. The original FFQ, developed by Willet for the Nurse’s Health Study, included only 61 items and accounted for between 60 and 80% of intakes for most nutrients, compared with those estimated by four 1-week diet records. For an enlarged FFQ with 116-items, over 90% of most nutrients were accounted for. Other data provided by Willett showed that the mean energy intakes for 27 men and women for the 116-item FFQ and 1-year diet records were reasonably similar. However, for each person the agreement is likely to be much less (1). The Observing Protein and Energy Nutrition (OPEN) study used urinary nitrogen and doubly labelled water as biomarkers to assess a FFQ, this showed that both protein and energy intakes were considerably under-estimated by the FFQ, although the percentage of energy from protein was not under-reported (4). A sub-study of EPIC showed reasonable correlations of protein (n=134) and energy (n=28) intakes with biomarkers, however, all but one person under-reported energy intake (5). Correlations with a ‘gold standard’ method are typically used as the main measure of validity for FFQ’s, reflecting the main purpose of ranking, rather than absolute nutrient intake measurement. There are a number of different methods of assessing dietary intake, and the appropriate method depends on the intended end use of the information. If a FFQ is suitable for your needs, it is ideal to develop and validate a dietary tool for your specific study and population, but this is usually not practical (6). If you are using a pre-existing questionnaire, such as the Cancer Council Victoria Dietary Questionnaire (CCVDQ), it is important to consider its suitability for your particular study. The CCVDQ is a modification of a FFQ that was developed in the late 1980’s to measure diet in the Melbourne Collaborative Cohort Study (MCCS). The MCCS participants are men and women aged 40-69 at recruitment between 1990 to 94, who were born in Australia, Greece and Italy, and the food list on the original FFQ was based on weighed food records in 810 demographically similar volunteers. The only validation of the CCVDQ was conducted in a group of women aged 16-48 years (mean 33 yrs), and showed correlation coefficients for nutrient intakes comparable with those reported for other FFQ’s (7). The CCVDQ is not recommended for children, or younger people in general, as it does not include soft drinks/electrolyte drinks for example, which contributed only around 4-5% of energy, but 16-21% of sugar in males and females aged 12-18 years in the 1995 National Nutrition Survey (8). We believe that the CCV DQ is a suitable tool for assessing intakes of foods and nutrients among adults in epidemiological studies, subject to the limitations common to all FFQ’s. For

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other uses, where more detail about diet is required, or where a very different population is being studied, we cannot be confident about the suitability of this instrument.

1. Willett W: Nutritional Epidemiology. In Monographs in Epidemiology and Biostatistics, Second ed. Kelsey JL, Marmot MG, Stolley PD, Vessey MP, Eds. New York, Oxford University Press, 1998, p. 514 2. Gibson RS: Principles of nutritional assessment. New York, Oxford University Press, 1990 3. Thomson CA, Giuliano A, Rock CL, Ritenbaugh CK, Flatt SW, Faerber S, Newman V, Caan B, Graver E, Hartz V, Whitacre R, Parker F, Pierce JP, Marshall JR: Measuring dietary change in a diet intervention trial: comparing food frequency questionnaire and dietary recalls. Am J Epidemiol 157:754-762, 2003 4. Subar AF, Kipnis V, Troiano RP, Midthune D, Schoeller DA, Bingham S, Sharbaugh CO, Trabulsi J, Runswick S, Ballard-Barbash R, Sunshine J, Schatzkin A: Using Intake Biomarkers to Evaluate the Extent of Dietary Misreporting in a Large Sample of Adults: The OPEN Study. Am. J. Epidemiol. 158:1-13, 2003 5. Kroke A, Klipstein-Grobusch K, Voss S, Möseneder J, Thielecke F, Noack R, Boeing H: Validation of a self-administered food-frequency questionnaire administered in the European Prospective Investigation into cancer and Nutrition (EPIC) Study: comparison of energy, protein, and macronutient intakes estimated with the doubly labeled water, urinary nitrogen, and repeated 24-h dietary recall methods. Am J Clin Nutr 70:439-447, 1999 6. Cade J, Thompson R, Burley V, Warm D: Development, validation and utilisation of food-frequency questionnaires - a review. Public Health Nutr 5:567-587, 2002 7. Hodge A, Patterson AJ, Brown WJ, Ireland P, Giles G: The Anti Cancer Council of Victoria FFQ: relative validity of nutrient intakes compared with weighed food records in young to middle-aged women in a study of iron supplementation. Aust NZ J Public Health 24:576-583, 2000 8. McLennan W, Podger A: National Nutrition Survey Nutrient Intakes and Physical Measurements Australia. Canberra, Australian Bureau of Statistics, 1998 The dietary questionnaire was developed specifically for use in Australian adults. It is the dietary instrument used in the Australian arm of the Breast Cancer CFR, the Melbourne Collaborative Cohort Study, the Australian Prostate Cancer Family Study, the Australian Longitudinal Study of Women’s Health and over 20 other smaller epidemiological studies in Australia. The original questionnaire was developed for the Melbourne Collaborative Cohort Study, including foods identified from weighed food records among men and women born in Australia, Greece and Italy. The current questionnaire was developed from the original, and now comprises a food list of 74 items with 10 frequency response options ranging from ‘Never’ to ‘3 or more times per day’. It also contains 3 photographs of scaled portions for four foods (used to calculate a portion size calibrator), questions on the overall frequency of consumption of fruits and vegetables (used to calibrate the overestimation of these foods in the food list), and questions on consumption of foods such as bread that do not fit easily into the frequency format. The 74 food items are grouped into four categories: 1) cereal foods; sweets and snacks; 2) dairy products, meats and fish; 3) fruit and 4) vegetables. A separate set of questions covers intake of alcoholic beverages. The food composition data used to calculate nutrients are from NUTTAB95 [1], supplemented by other data where necessary [2] [3] [4] [5] The output includes the following: water, kilojoules, fat (total),protein, carbohydrate (total), sugars, starch and dextrins, dietary fibre, cholesterol, sodium, potassium, calcium, phosphorus magnesium, iron, zinc, retinol equivalent, retinol, thiamine, beta-carotene equivalent, riboflavin, niacin niacin equivalent, vitamin c, alcohol, saturated fatty acids (total), monounsaturated fatty acids(total), polyunsaturated acids (total). We have recently extended the calculations to include individual fatty acids, carotenoids, glycemic index and glycemic load.

The dietary questionnaire is the property of the Cancer Council Victoria.

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2 Questionnaire Evaluation The performance of the current questionnaire is described in the paper below, and the subsequent erratum: Hodge A, Giles GG, Patterson A, Brown W, Ireland P. The Anti-Cancer Council of Victoria FFQ. Relative validity of nutrient intakes compared with diet diaries in young of middle-aged women in a study of iron supplementation. ANZ J of Public Health 2000;24:576-83. An erratum to this was published in ANZJPH 2003;27 (4) 468.

The following papers have also evaluated the questionnaire. Ambrosini GL, van Roosbroeck SA, Mackerras D, Fritschi L, de Klerk NH, Musk AW.The reliability of ten-year dietary recall: implications for cancer research. J Nutr. 2003 Aug;133(8):2663-8.

Xinying Xie P, Noakes M, Keogh J. Can a food frequency questionnaire be used to capture dietary intake data in a 4 week clinical intervention trial? Asia Pacific Journal of Clinical Nutrition 2004;1(4):318-23. Woods RK, Stoney RM, Ireland PD, Bailey MJ, Raven JM, Thien FC, Walters EH, Abramson MJ. A valid food frequency questionnaire for measuring dietary fish intake. Asia Pac J Clin Nutr. 2002;11(1):56-61. 3 Sources of Nutritional Data 3.1 Nutrients computed using Australian NUTTAB 95 database [1] Water Kilojoules Calories Protein Carbohydrate (total) Sugars Starch & Dextrins Dietary Fibre Cholesterol Sodium Potassium Calcium Phosphorus Magnesium Iron Zinc Retinol Equivalent Retinol Thiamin Beta-Carotene Equivalent Riboflavin Niacin Niacin Equivalent Vitamin C Alcohol Saturated Fatty Acids (total) Monounsaturated fatty

Acids (total) Fat (total) Polyunsaturated Acids (total)

3.2 Additional outputs Vitamin E, Folate British data [2] Carotenoids US data [3] Fatty acids Australian data [5] Glycaemic Index, Glycemic load

International tables [4]

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4 Administration of the Questionnaire The dietary questionnaire is designed to be self-administered, but can also be interviewer-administered. If self-administered it is the responsibility of the study coordinator to ensure questionnaires are completed correctly and that no pages are left blank, prior to returning to the Cancer Epidemiology Centre for scanning and analysis. It is important to instruct the respondents thoroughly on the need to fill in bubbles completely, not leave questions blank, and except in questions 3, 5, 7, 10 to only give one answer. As completed questionnaires are collected, they should be checked for completeness and errors so that mistakes can be corrected on the spot. If questionnaires are to be interviewer-administered, it is important that all interviewers have been appropriately trained to administer the questionnaire in a standard manner. As the completed forms are optically scanned, it is very important that each question is answered correctly. Answers should be recorded by completely filling the appropriate bubble as indicated on page 1 of the questionnaire. If ticks, crosses or lines are used, the scanner will not detect the response. Either pen or pencil can be used but pencil is preferable as mistakes can be more easily erased. All mistakes must be completely erased, not crossed out. Every question should be answered, including the date section on the front page. The program used to compute nutrients from the dietary questionnaire produces a report of all errors and inconsistencies in the responses. In some cases, default values will be assumed and the output will still be calculated, when the assumptions required for calculations are too great, no output will be produced. This will be detailed in the error report. It is up to the investigator to decide what to do about the missing or inconsistent data. You may choose to exclude the individual or recontact them to edit data. 4.1 Questions 1 and 2 The information obtained about fruit in question 15 is necessary to determine the relative contribution of different types of fruit to the person's total fruit intake. It is often found that food frequency questionnaires do not provide an accurate estimate of a person's total fruit intake, so question 1 has been added to scale the responses in question 15. Generally people find question 1 relatively easy to answer because their total intake of fruit is reasonably constant over the year, even if the types of fruit they consume varies with the seasons. As with fruit, the information obtained about vegetables in question 15 is essential for determining the relative contribution of different vegetables to a person’s total vegetable intake. Question 2 asks about how many different vegetables the person usually eats per day. We chose not to ask about the number of "serves" of vegetables because there is confusion about what constitutes a "serve" of vegetables. Moreover, we obtain information about vegetable serving sizes separately in questions 11 and 12. The response to question 2 is used scale the responses about frequency of vegetable consumption in question 15. Because the program that computes nutrient values from the scanned data uses responses to questions 1 and 2 to adjust the answers about fruit and vegetable intake in question 15, if either of these questions is left blank the program will not compute nutrients for that person. Also if the responses to questions 1 or 2 are completely inconsistent with the responses in question 15, nutrients will not be computed. It is not expected that answers will match exactly, but if for example it were indicated in question 1 that the respondent did not eat fruit, and in question 15 they reported eating fruit, this would be rejected. Similarly, if some fruit were reported in question 1 and none in question 15, this would lead to rejection. The same logic applies to vegetables in questions 2 and 15.

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4.2 Number of responses expected for questions 1-10 Only one response is required for most of these questions. However, for questions 3, 5, 7 and 10 more than one answer is acceptable. If more than a single type of milk, bread, spread or cheese is selected, it will be assumed that each is consumed in equal quantities for the computation of nutrient intakes. Inconsistencies between questions determining types of foods and amounts consumed will result in the data for that person being rejected. For questions 1, 2, 4, 6, 8 and 9, only one response is allowed, if more than one response is given the lowest response will be recorded and used for the nutritional analysis. 4.3 Portion Size Questions (Questions 11-14) Responses to the portion size questions are used to calculate a single portion size factor (PSF) indicating whether on average a person eats median size serves (PSF=1), more than the median (PSF > 1), or less than the median (PSF < 1). The PSF is used to scale the standard portion size for different foods up or down. Instructions are given at the top of the page for these four questions. Exactly one response should be recorded on each line. If more than one response per line is given, the smallest portion size will be assumed. If some of the questions are left blank, for example the steak in a vegetarian respondent, the portion size factor will be calculated as the average of all portion size responses provided. If all four portion size questions are left unanswered, a standard portion size will be used and this will be reflected as a serious error in the Error Report. 4.4 Question 15 The 74 food items are grouped into four categories: Cereal foods; sweets and snacks Dairy products, meats and fish Fruit Vegetables

Take care that only one response is recorded per line. It is easy to put two marks on one line and miss the next one. Certain foods such as sandwiches and salads are not listed because their composition varies. People should think about the separate ingredients that make up these foods and answer the questionnaire accordingly. For example, if a person ate a salad that included tomato once a week and a tomato sandwich once a week, the appropriate answer for tomato would be "2 times per week". For all the foods listed, the bubble indicating how often they were eaten on average should be filled . People should think back over the past year about foods eaten away from home or when on holidays as well as foods eaten and prepared at home. For seasonal foods, record frequency as if foods are in season. If a particular food item is never eaten, the bubble in the column headed “NEVER” should be filled to indicate this. 4.5 Alcohol Questions 4.5.1 Question 16

Asks about average alcohol consumption over the past twelve months. Each alcohol type is asked about separately. Only one response is permitted per line.

If ALL responses to this question are “NEVER”, no further questions need be answered.

4.5.2 Question 17 This question asks about the total number of glasses of all alcohol types usually drunk per day. This may require totalling of all alcohol types usually drunk.

4.5.3 Question 18

This question asks for the maximum number of glasses of alcohol drunk in any 24 hours during the past year. Because the response to this question is not used in calculation of nutrients, missing this question will not stop nutrients being computed, but a warning will be given in the error report.

5 Alcohol Calculations in the Dietary Questionnaire Because the dietary questionnaire asks about beverage-specific frequency of consumption but only about overall quantity of consumption, we have to make some assumptions in the calculation of nutrients. To estimate beverage-specific (and total) weekly consumption, we calculate a weighted average from two extreme methods of assigning quantity to consumption of individual beverages. The first method assumes that people who consume more than one type of beverage always do so on the same days (subject to the constraints of the beverage-specific frequencies), while the second method assumes that people separate their beverages wherever possible. In both methods, on days when people drink more than one beverage, we apportion the total glasses consumed equally among all types consumed on that day. From the 3-day diary of the 1995 National Health Survey, we determined that people who drank more than one beverage were about two times as likely to drink them on separate days as on the same day. Therefore, the data from the second method are given two times the weight of the first method when we construct the weighted average. Due to the assumptions required in the calculation of nutrients from alcoholic beverages, the results are less reliable than are those for nutrients from food. Therefore, nutrients from alcoholic beverages are reported separately and it is up to the investigator to decide whether to include these nutrients in the totals. If you want to include alcohol, all nutrients in the alcohol file should be added to the nutrients in the main file. 6 Scanning Errors It has been our experience that a large proportion of completed questionnaires returned for scanning contain errors that prevent further processing to compute nutrients. As a result, we have developed a set of editing rules that are applied when missing or multiple responses are detected in questions 15 to 16. These default rules are provided below, if you would like alternative rules applied to your data, please contact us to discuss your requirements. 6.1 Edit rules When a question has not been answered (missing), it is assumed none of that food or drink item was consumed in the past 12 months.

Cauliflower

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When two responses have been given when only one was expected (multiple response) the lowest response is taken (based on the assumption that people tend to over estimate food intake rather than underestimate).

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Cauliflower When two responses have been given to one question and the following question has been left unanswered, it is assumed that the greater response on the first line actually belongs to the second line.

Cauliflower

Broccoli When one question is left unanswered and the following question has two responses the greater response on the lower line is taken for the missing question

Cauliflower

Broccoli

7 Barcode Labels A barcode is affixed to the questionnaire prior to scanning. See Appendix B for instructions. The barcode labels consist of the Barcode Name and Sequential Number. The Barcode Name is an abbreviation of the study name, unchanging, maximum of ten digits and used as the reference name in all correspondence. The Sequential Number is changing, maximum of ten digits and can contain a capital letter if required i.e. H854. For example:

HTH 2020

Barcode Name

Sequential Number.

If barcode labels are not required, please note on order form.

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8 Output from Scanned Questionnaires You will receive 5 files consisting of: 1. raw data, 2. nutrients computed from food without alcoholic beverages (including carotenoid &

fatty acids, glycaemic index & glycaemic load), 3. nutrients from alcoholic beverages, 4. food intakes, and 5. error messages The raw data file includes Scan no., ID no, and date, then goes through the answers to all questions as scanned. For questions on page 1 except those regarding type of bread, milk, spread and cheese, responses are coded as sequential numbers starting at 1. For example, if the second response for Q1, ‘less than 1 piece of fruit per day’ was selected, it would be coded as 2. For the questions about different types foods, where it is possible to choose more than one type, there are separate variables for each type, which are coded ‘0’ if not used and ‘1’ if used. Q11-14 regarding serving sizes are coded from 1 ‘never ate’ to 8 ‘more than C’. For items in Q15, possible responses are from 1-10, corresponding to the frequency options from ‘Never’ to ‘3 or more times per day’. To analyse food intake in terms of frequency it is necessary to convert these responses to daily equivalent frequencies using the values in the table below.

Recorded response Frequency Daily equivalent frequency 1 never 0 2 less than once per month 0.02 3 1-3 times per month 0.07 4 once per week 0.14 5 twice per week 0.28 6 3-4 times per week 0.5 7 5-6 times per week 0.78 8 once per day 1 9 twice per day 2

10 3 or more times per day 3 Similarly for the questions on alcoholic beverages, the response values correspond to the response options on the QUESTIONNAIRE. The second file usually has ‘_nutanalysis’ in the file name, and is the calculated daily intake of nutrients from foods in the QUESTIONNAIRE. If the file you receive includes Portion Standard Factor, Fruit Calib and Vegetable Calib, ignore these, they are calculated on the way to the final nutrient intakes and are not used for anything else. The third file, typically including ‘_nutanalysis_alc’ in the file name, has identical variables to the standard nutrients from food, although some variables will have all zero intakes. As discussed in section 5, these two nutrient intake files can be added to give total nutrient intakes. The dietary analysis program has recently been updated to compute intakes of carotenoids, fatty acids, glycemic load and dietary glycemic index, and individual food intakes. Variable descriptions are given below: The nutrients from ‘Energy’ through to ‘Zinc’ are the standard output, and values are based on Australian nutrient composition data from NUTTAB95 [1], excepting folate and vitamin E, which are not available in NUTTAB, and have been derived from British tables [2]. Outputs from both food and alcoholic beverages include these standard nutrients. Within this is a

variable ‘BetaCarotene’, which is ß-carotene equivalents (mcg/d) from NUTTAB. ß-carotene equivalents is the sum of the ß-carotene and half the amounts of α-carotene and α- and ß-cryptoxanthins present. Alpha-Carotene through to Lycopene are individual carotenoid intakes (mcg/d) calculated from the USDA data base [3]. The value labeled ‘Beta-Carotene’ is total ß-carotene, and is not directly related to the ‘BetaCarotene’ from NUTTAB. Because these two variables come from completely separate databases from different times and countries, and may include different foods, there is no expectation of close agreement. Variables FD40 to FD226N3N6, are intakes of individual fatty acids, based on a data set we obtained from Neil Mann at RMIT, and now used in FoodWorks. Some of these will have very low or zero intakes, all the variable columns from the original database have been retained, even if intakes are zero.

Code Unit Fatty acid NameFD40 g/day C4:0 Butyric acid from diet (g/d) FD60 g/day C6:0 Caproic acid from diet (g/d) FD80 g/day C8:0 Caprylic acid from diet g/d) FD100 g/day C10:0 Capric acid from diet (g/d) FD120 g/day C12:0 Lauric acid from diet (g/d) FD140 g/day C14:0 Myristic acid from diet (g/d) FD150 g/day C15:0 Pentadecanoic acid from diet (g/d) FD160 g/day C16:0 Palmitic acid from diet (g/d) FD170 g/day C17:0 Margaric acid from diet (g/d) FD180 g/day C18:0 Stearic acid from diet (g/d) FD200 g/day C20:0 Arachidic acid from diet (g/d) FD220 g/day C22:0 Behenic acid from diet (g/d) FD240 g/day C24:0 Lignoceric acid from diet (g/d) FD141 g/day C14:1 Myristoleic acid from diet (g/d) FD151 g/day C15:1 Pentadecenoic acid from diet (g/d) FD161 g/day C16:1 Palmitoleic acid from diet (g/d) FD161T g/day C16:1 trans Trans Palmitoleic acid from diet (g/d) FD171 g/day C17:1 Heptadecenoic acid from diet (g/d) FD181 g/day C18:1 Oleic acid from diet (g/d) FD181T g/day c18:1 trans Elaidic/trans Vaccenic acid from diet (g/d) FD201 g/day C20:1 Eicosenic acid from diet (g/d) FD221 g/day C22:1 Cetoleic/Erucic acid from diet (g/d) FD182N6 g/day C18:2 n-6 Linoleic acid from diet (g/d) FD182N6T g/day C18:2 n-6 trans Trans Linoleic acid from diet (g/d) FD183N3 g/day C18:3 n-3 Alpha-linolenic acid from diet (g/d) FD202N6 g/day C20:2 n-6 Eicosadienoic acid from diet (g/d) FD203N6 g/day C20:3 n-6 Dihomo-gamma-linolenic acid from diet (g/d) FD204N6 g/day C20:4 n-6 Arachidonic acid from diet (g/d) FD205N3 g/day C20:5 n-3 Eicosapentaenoic acid (EPA) from diet (g/d) FD205N6 g/day C20:5 n-6 Fatty acid F205N6 from dietFD224N6 g/day C22:4 n-6 Adrenic acid from diet (g/d) FD225N3 g/day C22:5 n-3 Clupanodonic acid from diet (g/d) FD226N3 g/day C22:6 n-3 Decosahexaenoic acid from diet (DHA) from diet (g/d)

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Individual food intakes are in grams per day. Glycemic index and glycemic load are based on values from an international table [4]. The method of their calculation is explained in the publication including the tables, and also in a paper we published in Diabetes Care [6]. The relevant section from our paper is copied below. ‘Glycemic index is a method of ranking foods on the basis of the blood glucose response to a given amount of carbohydrate from that food. GI values of individual food items were obtained from the 2002 International table of GI and GL values [4]. Where there was more than one value, GI values were averaged, with preference being given to Australian figures. Dietary GL was computed by summing the product of carbohydrate intake from each food by the GI for that food. GL was divided by total carbohydrate intake to obtain dietary GI, i.e an average of individual food GI values, weighted according to their contribution to carbohydrate intake [4]. Alcoholic beverages were not included in the overall GI. None of these new values have been tested or validated so we welcome any feedback and the values should be used with caution. The fifth output file is the error log. It lists each error and whether that QUESTIONNAIRE was processed or not. It is quite possible to have fewer subjects in the calculated nutrients than the raw data due to exclusions. Examples of each file type are shown overleaf.

8.1 Example of Raw Data

Scan.no Id Date Fruit.p.d Veg.p.d Milk.none Milk.full Milk.red Milk.skim Milk.soy Milk.p.d Bread.none Bread.highf B10

read.white73100000 0249 6-Mar-01 3 3 0 0 1 0 0 3 0 1 0

Bread. heese.hard0

Chees orridge7 3 7

Muesli Rice Pasta Dry biscuits Sweet biscuits Cakes Pies/pastries Pizza Hamburger Chocolate Flav.milk Nuts Peanut butter Chips1

Jam/h ey Vegemite Cheese Icecream Yoghurt Beef Veal Chicken Lamb Pork Bacon Ham Beef/salami Sausages3 1 3 3 3 3 3 3 2

Fish.grill Fish.fried Fish.tinned Fruit.tin Fruit juice Oranges Apples Pears Bananas Melons Pineapple Strawberry Apricots Peaches2 4 3 3 1 4 4 4 4 1 1 3 3 3

Mango Avocado Pot.roast/fried Pot.not fat Tom sauce/paste Tom.tinned Peppers Green salad Cucumber Celery Beetroot Carrots Cabbage Cauliflower2 1 3 6 4 4 1 4 4 4 4 4 4 4

Broccoli Spinach Peas Green bean Sprouts Bakes beans Soy bean Other bean Pumpkin Onion Garlic.fresh Mushroom Zucchini Beer.low4 4 4 4 4 4 1 4 4 4 1 5 5 1

Beer.full Red wine White wine Port/sherry Spirits Glass.p.d Max.glass.p.d1 1 3 3 3 1 1

whol Bread.rye Bread.multi Bread.p.d Spread.none Marg Poly.marg Mono.marg Marg blends Butter Sugar.p.d Eggs.p.w Cheese.none C0 0 0 6 0 0 1 0 0 0 1 2 0

e.firm Cheese.soft Ricotta Cream cheese Lowf.cheese Pot.eat Veg.eat Steak.eat Casserole.eat Allbran Other brans Weetbix Cornflakes P1 0 0 0 0 6 4 4 4 3 1

3 3 3 1 4 1 4 1 1 4 1 3 3

on4 1 5 3 1

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8.2 Example of Nutrients f

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rom food list (including carotenoid & fatty acids, glycaemic index & glycaemic load), full list Scan Scan Portion Energy All Fat SatFat PolyFat MonoFat Protein CarbohydratSugars Starch Fibre AlcoholID Date Standard kJ/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day

Factor1948 7/03/2005 0.725 6699.821 61.1701 30.63372 7.717802 17.76102 63.03661 203.0659 101.7313 100.3643 19.41932 0

BetaCaroCalcium Cholesterol Folate Iron MagnesiumNiacin Niacin EquivPhosphorusPotassium Retinol Retinol Equ Riboflavin Sodiumug/day mg/day mg/day ug/day mg/day mg/day mg/day mg/day mg/day mg/day ug/day ug/day mg/day mg/day

2148.3 1061.274 214.5715 243.2412 10.54445 262.4491 14.83017 28.15072 1273.983 2433.896 451.9157 809.9382 2.077933 1948.391

Thiamin VitaminC VitaminE Zinc Alpha-CaroBeta-CaroteBeta-CryptoLutein+ZeaxLycopene FD40 FD60 FD80 FD100 FD120mg/day mg/day mg/day mg/day ug/day ug/day ug/day ug/day ug/day g/day g/day g/day g/day g/day

1.3519 84.1606 4.772141 8.098256 724.1287 2825.672 163.2716 710.828 1333.864 0.8125666 0.442995 0.521081 0.8767341 2.298161

FD140 FD150 FD160 FD170 FD180 FD200 FD220 FD240 FD141 FD151 FD161 FD161T FD171 FD181g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day

4.3079 0.3415976 16.05117 0.305939 9.46227 0.286424 0.121433 7.23E-02 0.3307192 4.09E-03 0.891477 0 3.89E-02 21.2029

FD181T FD201 FD221 FD182N6 FD182N6T FD183N3 FD202N6 FD203N6 FD204N6 FD205N3 FD205N6 FD224N6 FD225N3 FD226N3 Glycemic Glycemic g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day Load Index

0.679 0.1650253 4.26E-02 6.578168 0.0749 0.949695 1.96E-02 1.07E-02 2.56E-02 2.39E-02 0 2.85E-03 9.64E-03 0.061914 110.3033 54.31897

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8.3 Example of Nutrients from alcoholic beverages, full list

Scan Scan Portion Energy All Fat SatFat PolyFat MonoFat Protein Carbohydrate Sugars Starch Fibre AlcoholID Date Standard kJ/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day

Factor249 6/03/2001 0.9375 56.22954 0 0 0 0 2.31E-02 0.4521611 0.4521611 0 0 1.668858

BetaCarotene Calcium Cholesterol Folate Iron Magnesium Niacin Niacin Equiv Phosphorus Potassium Retinol Retinol Equiv Riboflavin Sodiumug/day mg/day mg/day ug/day mg/day mg/day mg/day mg/day mg/day mg/day ug/day ug/day mg/day mg/day

0 0.7247917 0 0 0.0214375 0.8438889 8.17E-03 8.17E-03 2.079097 6.138611 0 0 0 2.555486

Thiamin VitaminC VitaminE Zincmg/day mg/day mg/day mg/day

0 0.245 0 0

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8.4 Example of food intakes, full list Sc Scan Portion Full cream milk Reduced fat milk Skim milk Soya milk High fibre white bread White bread Wholemeal bread Rye bread Multi-grain bread Margarine Polyunsaturated margarine

ID Date Standard g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/dayFactor

1948 7/03/2005 0.725 0 0 375 0 0 0 120 0 0 0 0

Monounsaturated margarine Butter and margarine blends Butter Hard cheese Firm cheese Soft cheese Ricotta or cottage cheese Cream cheese Low fat cheese Sugar Eggs All Bran Branflakes Weet Bixg/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day

0 28 0 0 28.7 0 0 0 0 0 12.9 0 0 20.2

Cornflakes Porridge Muesli Rice Pasta Crackers Sweet Biscuits Cakes Meat pies Pizza Hamburger Chocolate Flavoured Milk Drink Nutsg/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day

23.6 0 0 0 18.7 0 0 53.5 0 0 0 22 0 0

Peanut butter Crisps Jam Vegemite Ice-cream Yoghurt Beef Veal Chicken Lamb Pork Bacon Ham Salamig/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day

0 0 10 0 51.7 0 13.4 0 9.3 11.4 0 0 0 0

Sausages Fish Fried fish Tinned fish Tinned fruit Fruit juice Oranges Apples Pears Bananas Melon Pineapple Strawberries Apricotsg/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day

0 0 0 3.7 0 100.7 0 70 0 73.6 0 0 0 0

Peaches Mango Avocado Chips Potatoes Tomato sauce Tomatoes Capsicum Lettuce Cucumber Celery Beetroot Carrots Cabbageg/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day

38.9 0 0 0 31.9 0.4 0 0 10.3 9.5 1.6 8.8 10.8 2.7

Cauliflower Broccoli Spinach Peas Green beans Bean sprouts Baked beans Tofu Other beans Pumpkin Onion Garlic Mushrooms Zucchinig/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day g/day

2 0 5.1 5.4 11.4 0 3.5 0 0 17.4 4.2 0 0.7 1.2

Light beer Heavy beer Red wine White wine Fortified wines Spiritsg/day g/day g/day g/day g/day g/day

3.7 0 128.3 2.3 0 0

an

8.5 Example of an error report

Scan File is : tccv 22-05-06.csvProcessing was commenced at 4/07/2006 9:26:45 AM No. ID Warning/Rejection reasons879000003 2335 Trivial warning - portion size factor(Q11-14) is based on only 3 foods.879000005 2338 Trivial warning - portion size factor(Q11-14) is based on only 3 foods.879000021 2360 Trivial warning - Milk type selected in (Q3) but 'none' used in (Q4).879000025 2356 Serious warning - (Q1) 'I don''t eat fruit' and fruit intake reported in (Q15).879000104 2507 Trivial warning - (Q2) reports eating 1 or more vegetable per day and no vegetables selected in (Q15).879000114 2410 Trivial warning - Milk type selected in (Q3) but 'none' used in (Q4).879000116 2422 Serious warning - (Q1) 'I don''t eat fruit' and fruit intake reported in (Q15).879000124 2378 Serious warning - (Q1) 'I don''t eat fruit' and fruit intake reported in (Q15).879000130 2420 Trivial warning - portion size factor(Q11-14) is based on only 3 foods.879000134 2479 Serious warning - (Q1) 'I don''t eat fruit' and fruit intake reported in (Q15).879000137 2482 Intermediate warning - cheese type (Q10) is missing or 'I don''t eat cheese' but (Q15) indicates cheese consum879000158 2510 Intermediate warning - portion size factor(Q11-14) is based on only 2 foods.879000162 2514 Trivial warning - portion size factor(Q11-14) is based on only 3 foods.8790001687900016

4 2516 Intermediate warning - cheese type (Q10) is missing or 'I don''t eat cheese' but (Q15) indicates cheese consum6 2413 Trivial warning - portion size factor(Q11-14) is based on only 3 foods.

879000177 2466 Trivial warning - portion size factor(Q11-14) is based on on018

ly 3 foods.87900 5 2521 Trivial warning - portion size factor(Q11-14) is based on on

019ly 3 foods.

87900 0 2527 Trivial warning - portion size factor(Q11-14) is based on on019

ly 3 foods.87900 5 2532 Intermediate warning - cheese type (Q10) is missing or 'I don''t eat cheese' but (Q15) indicates cheese consum879000203 2539 Trivial warning - cheese consumption indicated in (Q10) bu

020t frequency 'never' in (Q15).

87900 7 2543 Trivial warning - portion size factor(Q11-14) is based on on021

ly 3 foods.87900 0 2545 Trivial warning - (Q2) reports eating 1 or more vegetable pe

021r day and no vegetables selected in (Q15).

87900 2 2547 Trivial warning - portion size factor(Q11-14) is based on on021

ly 3 foods.87900 3 2548 Trivial warning - cheese consumption indicated in (Q10) bu

022t frequency 'never' in (Q15).

87900 9 586 Serious warning - (Q1) 'I don''t eat fruit' and fruit intake repo022

rted in (Q15).87900 9 586 Intermediate warning - Milk type (Q3) is missing or 'none' b

0231 665 Trivial warning - portion size factor(Q11-14) is based on on023

ut (Q4) indicates milk consumed.87900 ly 3 foods.87900 2 678 Trivial warning - portion size factor(Q11-14) is based on on

sing was completed at 4/07/2006 9:35:04 AMer of records processed : 235er of records rejected : 0

ly 3 foods.ProcesNumbNumb

Page 18 of 22

R uestionnaire

esearchers referencing the dietary questionnaire should use the following citation: iles GG, Ireland PD. Dietary Questionnaire for Epidemiological Studies (Version 2), Melbourne: The

Cancer Council Victoria, 1996. The following is the reference, which validates the dietary questionnaire: Hodge A, Patterson AJ, Brown WJ, Ireland P, Giles G. The Anti Cancer Council of Victoria FFQ: relative validity of nutrient intakes compared with weighed food records in young to middle-aged women in a study of iron supplementation. Aust N Z J Public Health. 2000 Dec;24(6):576-83. An erratum to this was published in ANZJPH 2003;27 (4) 468. 10 Procedure for Processing Questionnaires 10.1 Fees

• Price per unit includes questionnaires, barcodes, scanning, analysis, postage and GST. • Minimum of 100 units per order.

Quantity Cost per unit

9 eferencing the Dietary Q RG

100-499 $14.85 500-999 $12.65 1000+ $11.00

10.2 Purchasing Order/MOU form (Appendix A) is required, before questionnaires can be dispatched. Please submit a signed copy via email, fax or post to the Nutritional Assessment Office, details above. Questionnaires, barcode labels and Dispatch & Receipt Agreement from are dispatched within a week of receiving an authorised Order/MOU form. Barcodes ordered independent of the questionnaires will be subjected to a minimum additional cost of $55.00. Invoices are mailed following the questionnaires unless credit card option is selected. 10.3 Scanning and Analysis Questionnaire’s are scanned and analysed in order lot.. It is imperative that questionnaires are completed correctly as re-scanning will be subjected to a minimum additional cost of $55.00. Questionnaires and the Dispatch & Receipt Agreement form should be sent to the Nutritional Assessment Office, details above. Two week is required to process <200 and four weeks for 200+. 10.4 Output- Nutrient Analysis You will receive five output files. These files will be emailed to you and consist of

• raw data, • nutrients computed from food without alcoholic beverages (including carotenoid & fatty acids,

glycaemic index & glycaemic load), • nutrients from alcoholic beverages, • food intakes, and • error messages

Questionnaires are returned to you by mail.

Page 19 of 22

Phone: +61 3 9635 5603 Fax: +61 3 9635 5330

11 Contact Us Nutritional Assessment Office 1 Rathdowne Street Cancer Epidemiology Centre The Cancer Council Victoria

Carlton South Victoria 3053

E-mail: ffq@cancervic.org.au

Table for Use in Australia. 1995, Australian

. Holland B, Welch AA, Unwin ID, Buss DH, Paul AA, and Southgate DAT. McCance and Widdowson's The ty of Chemistry.

-NCC. USDA-NCC Carotenoid Database for U.S.Foods. 1998. Retrieved.

4. load 76: 5-56.

. RMIT. RMIT Fatty Acid database of Australian foods. Xyris software, Brisbane. Retrieved from h yris.com.au

12 References 1. Lewis J, Milligan G, and Hunt A. NUTTAB95 Nutrient Data

Government Publishing Service: Canberra.

2Composition of Foods. 5th ed. 1993, Cambridge: Royal Socie

3. USDA

Foster-Powell K, Holt HA, and Brand-Miller JC. International tables of glycemic index and glycemicvalues: 2002. Am J Clin Nutr. 2002;

5ttp://www.x .

6. Hodge AM, English DR, O'Dea K, and Giles GG. Glycemic index and dietary fiber and the risk of type 2 d betes Care. 2004; 27:(11

iabetes. Dia ): 2701-6.

Page 20 of 22

) 13 Order/MOU Form (Appendix A

Page 21 of 22

Page 22 of 22

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BA

RC

14 How to fill in a Questionnaire (Appendix B) Every question MUST be completed. Please check each question is completed. Any question that is not completed will default to the first answer. Use a soft pencil only, preferably 2B. Ensure the oval is completely covered.

Place barcode correctly in orange box. It is preferred that numbers start from the bottom of the page going up, as shown in example below.

OD

E D

IRE

CTI

ON