Foods that we eat and their relationship to health
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Food history questionnaires
A lot of nutrition research is done through the use of the food history questionnaire. This is different from food recalls in that it is shorter, easier to administer and does not require special interviewing skills.
Sometimes studies need to identify patterns of food consumption in a large population. This is done, for instance, as part of a general population health survey. These are done on a fairly regular basis, usually funded by governments, to be proactive in the formulation of heath related polices. This saves our tax money in the long run.
Food history questionnaires are related to food recalls in that they collect information on commonly eaten foods. These questionnaires tend to be simpler in that they do not seek to know each individual food that was eaten. They ask questions like “When you eat pasta how much do you eat and do you eat it once a week, or 3-5 times a month”. You get the idea. Typically a food history questionnaire will have fewer than 100 such questions.
Before a questionnaire like this can be formulated it is wise to know what kinds of foods the population usually eats. A smaller number of individuals are asked what they ate recently, using the recall format. Using the example above, from the results of these recalls, a pattern of “pasta” consumption can be determined. A composite “pasta” food can then be created and used as the nutrient profile for the “pasta” question in the food history questionnaire.
The downfall is that it is a fairly “blunt” instruments. With a bit of care in its construction some of the bluntness can be removed.
The following techniques can be used to make them better research instruments:
Make up your own;
Make them specific to your target population;
Make them as detailed as possible while keeping them still realistically long;
Base the questions on foods your population eats. Collect as many food recalls as you can and base the questions on the foods in those recalls;
Create composite foods from similar foods in the recalls and use those to calculate nutrient contributions for corresponding questions in the food history questionnaire;
Validate your questionnaire… does it over/under-estimate specific nutrients in comparison to your food recall data?
There is enough variability in food intake and nutrient concentrations of individual foods to try to minimize the effect of further variability introduced by blunt food history questionnaires.
Given the amount of variability in this data it is a wonder that any conclusion can be reached about the predicted effect of a nutrient intervention or of specific nutrient consumption.
By all means find and use good software that will make your task bearable. Variability can only be reduced by eliminating mistakes, using the best sources of data possible and collecting large amounts of data. A significant task indeed.
Questionnaire concepts
A subject’s nutrient profile, whether obtained from food recall information or from food history (questionnaire) information, is obtained by a simple arithmetic calculation. Each nutrient is the product of the food quantity consumed and the nutrient’s concentration in that food. The subject’s consumption is the sum of these products over the foods consumed in one day. Simple.
Problems: In a recall… using the right food code to represent the food consumed and estimating the quantity consumed as accurately as possible. For a recall there are thousands of food codes to choose from, one of those is likely to represent fairly accurately the actual food consumed. The quantity of that food consumed can also be fairly accurately recorded as reported. An example of a recall record would be “I ate a banana for breakfast”. The corresponding coding would have the food code for bananas and quantity being typically “one medium banana”. Hence, nutrient profile and quantity fairly accurately recorded and yield fairly good nutrient information.
In a questionnaire very few questions (usually less than 200, sometimes as few as 100) are used to represent historical intake. Every question is matched to a food with a nutrient profile representing the consumption for that question. A single food taken from a database used in recalls is not likely to be indicative of the group of foods represented by any one question in the questionnaire.
An example question could be “Do you consume soup?”. There are many soups with different nutrient profiles. Which one to use for the question as a nutrient profile? The soup code used should be a “composite” of all the possible soups. Which composite to use? One formed of the relative use all the soups consumed in the population in question. This information can be obtained from a food recall study of the population. This “composite” food could then be taken as the food representing the question’s nutrient profile… a good estimate on a population basis, probably not so good on an individual basis.
Composite food calculations from food recalls:
Determine the unique food codes from all the recalls. Typically should be 400-600 food codes
Divide those codes into food groups corresponding to questions you would want in the questionnaire
Run the nutrient calculations on the recalls looking at food details by food group, sorted in descending order of food quantity in grams
Create a recipe from each food group using the main foods in that group and their corresponding quantities as recipe ingredients
Run the nutrient analysis on the recipe file and export each recipe and its nutrients per 100G to a food file
Use this food file in your nutrient calculations of the relevant questions
Of course, this assumes you have the software to do all these calculations and conversions automatically. Doing the calculations manually or using a spreadsheet would be very onerous indeed.
The question of quantity to record is a bit more difficult. Usually such a question asks “How often do you consume this soup? Per day? Per week? Per month?”. No problem here, just a mathematical calculation. The problem is in the next part of the estimate, the portion size. If the portion size is indicated precisely as in .5 cup, 1 cup, 2 cups… again, no problem. The composite soup can have a weighted density based on the density of the soups making up the composite. Cup weights can then be precisely calculated. 250 ml x 1.06 G/ml would give us a cup weight of 265 G.
Technique A: How does one estimate portion sizes when the portion is not so precisely indicated? As in, .5 of a cup or less, .5 cup to 2 cups, 2 cups or more? One logical estimate would be to take the mid-point of the ranges. For minimal consumption to .5 cups, use .25 cup; for .5 to 2 cups, use 1.25 cups; for 2 cups or more use 4 cups (maximal consumption assumed to be 6 cups).
Technique B: Much more intensely computational… not using the composite weighted densities… An alternative to the above would be to use population based estimates. For each of the range of consumption, .5 cup or less, .5 cup to 2 cups and 2 cups and more, establish the distribution of consumption and calculate the median or average value. The median value would probably be best as it would negate the effects of outlier consumption.
In the population there is no consumption of the composite soup. The distributions have to be calculated for each and every soup making up the composite. One median per soup! For example for the lower range, less than .5 cup, how does one obtain a composite median from the individual soup medians? A weighted average of medians? Based on what weighting factor? The relative weight of the total weight of the soup consumed in the population (used to get the weighted density of the composite) or the relative weight of the total weight consumed in the range less than .5 cup? I would guess the latter to be the better estimate.
How does one establish the cut-off weight for .5 cup. The best value would be obtained by using the density for the soup whose median is being calculated. If the soup has a density of 1.06, one would look at all consumption of that soup of .5 cup or less or of 265G/2 = 132 G or less. The range .5 and above would start at 133G…
Should the basis of the distribution of consumption be each consumption of soup or the total soup consumption for the day? This question may not seem relevant here (each consumption would be the best information for the typical portion size) but what about other foods, such as milk in all its possible consumption portion sizes (see below)?
Assumptions: Technique B assumes that all consumptions recorded in the population recalls are based on portions that are cups. In soups this is probably reasonable. What about questions that ask questions about foods such as milk. “Do you consume milk?” If yes, how many times per day/week/month and how many glasses? Recalls will record all kinds of consumptions of milk. In cereal, in coffee or tea, in glasses or cups. Each one of these will be converted to Grams. The total of those consumptions, on a daily basis, or on a per consumption basis, may not reflect typical population median gram values for typical glass or cup portion sizes. Estimates of portion sizes for questionnaire data should be based on recall data collected using those same portion sizes.
Food frequency questionnaires
Sometimes studies need to identify patterns of food consumption in a large population. This is done, for instance, as part of a general population health survey. These are done on a fairly regular basis, usually funded by governments, to be proactive in the formulation of heath related polices. This saves our tax money in the long run.
Food history questionnaires are related to food recalls in that they collect information on commonly eaten foods. These questionnaires tend to be simpler in that they do not seek to know each individual food that was eaten. They ask questions like “When you eat pasta how much do you eat and do you eat it once a week, or 3-5 times a month”. You get the idea. Typically a food history questionnaire will have fewer than 100 such questions.
Before a questionnaire like this can be formulated it is wise to know what kinds of foods the population usually eats. A smaller number of individuals are asked what they ate recently, using the recall format. Using the example above, from the results of these recalls, a pattern of “pasta” consumption can be determined. A composite “pasta” food can then be created and used as the nutrient profile for the “pasta” question in the food history questionnaire.
SPSS or SAS or PSPP or … and CANDAT
SPSS, SAS (or other good statistical packages) is used to process Candat calculations into results for your scientific report.
At its most detailed Candat will produce data files consisting of:
Subject code
Date
Day of Week code (0-6, where 0 is Sunday)
Food Group code
Meal code
Food code
Food description
Nutrient variables (Weight of foods and all nutrients you selected at reporting)
The printed (text or PDF) file (hopefully you did not print to paper) can have all of the above information as well as basic statistics (for a quick perusal, not meant to be used instead of a statistical package).
Candat also produces computer readable files that can be directly read into statistical packages or spreadsheet software (such as Excel or Open or Libre Office Calc or ….) . . Your study will probably want to make use of daily average intake data, as representative as possible of your subject’s usual intake.
Where you have days of the week and weekend days you will probably want to make use week-weighted average daily intakes, where weekend days carry less weight than week days. These week-weighted averages are calculated in Candat but should be re-calculated in the statistical package so that you can make use of the proper variance calculations for weighted data.
Systematically then here are the procedures to follow for managing your data:
Generate the data in Candat you need in a compact way. If you are not interested in data by meals or by food group or at the food detail level, leave those out of the Candat calculation.
Read the Candat generated file into a statistical package
Identify missing data as -1 (the Candat value at the food level. In Candat summaries (means) missing values are considered a zero. This makes sense because food databases do not spend much time analyzing nutrients that are not likely to exist in the food but they do not report them as having a value of zero (usually).
Convert the Day of Week code to a weight to be used in week weighted calculations. In Candat we use 5 for codes 1 to 5 and 2 for codes 0 and 6.
Weight the cases using the converted Day of Week variable
Aggregate the cases. In most cases you will want to aggregate the data using Subject code and Date code as independent variables, an average weight code for the weighting variable (average will maintain the weight code for the day) and sum (which adds up all the contributions for that day) for the nutrient variables. At this point your data is ready for statistical processing.
Apply exploratory statistics to all your variables and make sure the data seems reasonable
Merge the data variables that identify your subject variables. This may be from a file produced externally from Candat or from the Candat Description file. In either case you must make sure to merge on the Subject codes.
Compare your subjects to your control groups (subject variables) using statistical procedures and save the results.
Report these results, write the other sections of the paper and you are done.
Week-weighted Averages in CANDAT
When expressing and comparing results of multi-day (3 day commonly) food recalls one tends to use the average daily intake as a measure of a subject’s intake. Of course, 7 day recalls will give more accurate estimates of this daily intake and the accuracy will increase if all the days of a week are used. The assumption here is that subjects will eat differently on different days with the greatest variability been between week days and weekend days.
Rather than simply computing an average daily intake one may get more accurate results by weighting the days of the week and the weekend days differently.
A weight of 5 for each week day and a weight of 2 for weekend days should allow us to calculate week-weighted averages for any number of recalls. Of course, for recalls without weekends this would just be a day of the week average and vice-versa.
The week-weighted average could be calculated as follows:
xw = (∑ wi × xi) ÷ ∑ w
where xw is the weighted average with xi as the daily intakes, and i is 1 – 5 (codes for days of the week) or 0,6 codes for weekend days corresponding to Sunday and Saturday respectively. w1-5 would then be 5 and w0,6 would be 2.
with a variance of
Var(xw) = Var(x) × ((∑ wi2) ÷ (wi)2)
where Var(x) would be the variance over all the days of the food intakes for the subject.
Course & Documentation
Please follow the outline in the column on the right to navigate through food research techniques and documentation on using Candat with those techniques.
Please enjoy the site and all its information.
Recipes & CANDAT
Recipes are another source of food information. Not all foods can be found in food databases, There is a limitless number of recipes and thus a limitless number of foods. You only need to look at the number of recipe books that are available to have an idea of the number of foods that are possible.
A good study needs to be able to identify commonly used recipes in the target populations and find suitable foods to code for those recipes. Where there are no suitable codes, the ingredients of the recipe need to be identified and a suitable food defined from these ingredients. CANDAT has tools to do this and to manage the consequent data
The following are the two menu selections needed manage the tasks in the recipe module.
This from the main CANDAT menu and
this from the choices then presented:
The standard startup choices below are presented after the selection of a task and
are explained in Appendix A (click on the screen to see the explanation). The prompts that follow activating “START the task” control the options for the task in question and are explained in the appropriate task chapter.
The list of tasks in the task menu area are listed in the order one would use them. More detailed information about each task can be found in that task’s chapter.
400 Recipe file maintenance – this is where recipes are defined, copied, modified, listed, etc.
410 Recipe file validation – once recipes have been created this task validates that the ingredients exist and that proper units have been specified for quantities
420 Recipe nutrient calculations – nutrients are calculated for each recipe and listed on a total and per ingredient basis. Ratings of recipes based on system Recommended Daily Intakes (RDI) are listed here as well
430 Recipe to food file conversion – to use recipe data as part of subject recalls or even as ingredients in other recipes, they must be made into foods using food files. The foods in these food files can then be used as input to subject data or recipe data and managed like regular food files
100 Food file maintenance – this task is part of the food files module. It is included here as a convenient link to food files once recipes have been converted to foods
440 Recipe reports by types – part of the definition of foods has optional fields which define attributes of the recipe. The reports in this task allow listing of recipes that satisfy those attributes.
Task 400 – Recipe Maintenance
This task begins by prompting for the file name. Files that exist already will be listed and the one desired selected. If the new… choice is selected a new file name needs to be entered. New file names must start with a letter, have no spaces within the name and have 8 characters (letters or numbers) or less.
Recipe files can contain the definition of many recipes. Each recipe is identified by a code of up to 7 digits. As recipe files may eventually be converted to foods it is a good idea to use the same convention for their codes as are used for food codes.
A food code is entered here. If the code exists already, the next prompt will be the options prompt where the recipe information can be modified. Otherwise a message will appear prompting for the creation of a recipe. Again, the options prompt will appear allowing the entry of recipe information.
The various parts of a recipe can be defined using the recipe options listed here. The ingredient editing options change the same ingredient data, there are two ways of editing these for convenience.
Attributes define a recipes profile. There can be two preparations for each recipe to be used as desired. Some will use preparion one for imperial units and preparation two for metric units. Some will use preparation one for a recipe with a small number of servings and preparation two for a much larger number of servings. Each preparation has its own profile and its own quantities for each ingredients. Other uses of preparations are up to the imagination and needs of the user. Of course, a single preparation can be used as well.
The fields defining a recipe are as follows:
Recipe name: A description for the recipe. Remember this will also be used as a description for the food if the recipe data is ever converted to a food.
Remarks: Any remark specific to this recipe. It serves as additional documentation to the recipe and is not used in conversion to a food and is an optional field.
Hints line 1::Any hint specific to this recipe. It serves as additional documentation to the recipe and is not used in conversion to a food. Also an optional field.
Target % H2O: This is used to compensate for cooking method. The recipe nutrient data will be adjusted to force this % moisture in the final recipe. It consists of a single number like 8.5 or 10 or 33.8, etc. It this field is not used for target moisture it can be used for additional hint data and is an optional field.
Where used:,Product Group:,Main Product: These are arbitraty and optional descriptions used to further define the profile of recipes. To use these fields as selectors in future report groupings a consistent set of descriptions must be developed and used.
Number of servings: A number, required to calculate nutrients per serving.
Serving size: Specified in grams.
Unit of measure: This is always 0, the unit code for grams.
Density: If known, is entered here as a number of grams per 100 ml. Is used in conversion to food. A food with a density can be used with volumetric units.
Dates: The date created is automatically entered here. The other dates are optional and can serve as record keeping to monitor the progress of the recipe through its phases. Dates are entered using the format yyyymmdd.
Recipe Type Code: These codes are arbitraty and optional and can be used as selectors in future report groupings. This requires a consistent set of descriptions to be developed and used
Preparation Time (mins): A number of minutes, again, used as selectors in future report groupings
Ingredients are inserted and modified using either of the two following panels. Fields describing each ingredient are:
Ingredient code: Ingredient codes come from food files and must exist there before they are used. Food codes for ingredients are found using the F6 information key with a keyword search term. Multiple keywords can be used. If seperated by spaces each keyword must be present, separated by commas, one or the other keyword can be present. The result of the search is a list of foods satisfying the search parameters. Choosing the desired food inserts its code in the ingredient code field.
Unit code: This code is specific to the ingredient and a list of possible codes are accessed using the F6 information key. Choosing the desired unit code inserts its code int he unit field.
Quantity: This is the quantity of the ingredient required for the recipe in “unit code” units.
The E/F and the % Yield fields are not presently used and are reserved. The concept behind the E/F field was as an “each” parameter as in each of the servings would have this quantity of the ingredient. The total quantity of the ingredient would thus depend on the recipe’s profile information.
The above panel consists of multiple lines of entry per ingredient. As you tab from field to field you will see the space highlighted for each.
The above panel consists of a single line of entry per ingredient. Again, As you tab from field to field you will see the space highlighted for each.
The preparation panel is used to describe the preparation of the recipe. It is mostly meant to be used in managing cookbooks and is not used in the conversion of recipes to food codes. It consists of arbitrary text and it too is an optional field.
Once all the data has been entered pressing the Esc key will save all the recipe data automatically and navigate back to the previous step or menu.
Recipe – Validation
One of the purposes of creating recipes is to be able to calculate their nutrient profile. If you were doing this manually you would look for the nutrient profile of each ingredient and sum each ingredient’s nutrient contribution. From this you would get an estimate of the recipe’s nutrient profile.
Validating a recipe is a step that ensures, in an automated system, that all ingredients are present in the food database. The nutrient calculation of the recipe can then proceed automatically. Validation will report either that the ingredient does not exist or that the units used to quantify the ingredient are not valid. In either case one must correct the mistake before instructing the program to calculate the recipe values.
Recipe – management
A database of recipes needs to be managed. Management means the following:
Being able to list the recipes (simple code and description only)
Being able to list the recipes with contents. This allows verification of information entered to ensure accuracy
Being able to copy recipes to other recipe databases to save re-entry
Being able to delete recipes no longer relevant
Being able to copy a recipe into another recipe. This allows creating variations on a recipe without having to re-enter all the duplicated information
This management is best done by computer programs. Recipe database files can then be easily stored, backed-up and shared with others.
Recipe – Input
There is more to recipe input than just entering the ingredients and their quantities. Below is a list of requirements to define recipes. (R) indicates a required item, (O) indicates an optional item but useful if you are going to be creating a large collection of recipes for many purposes.
(R) A recipe database. If a database does not exist, it must be easy to create one.
(R) Recipe code. The unique identification for the recipe. One can build in some information in this code, for instance, all 100 recipes could be salads, all 500 recipes could be deserts, etc.
(R) Recipe description. This is the name of the recipe.
(R) Ingredients. A list of ingredients with quantities. Each ingredient is a food code from the active food database. Quantities of each ingredient are specified in grams.
(R) Number of servings. How many servings does this recipe produce.
(R) Serving size. This can usually be derived from the sum of the ingredients weights and the number of servings. If the recipe loses moisture in cooking the serving size will not be correct and an actual serving size will need to be inserted.
(O) Preparation. A description of how to prepare the recipe. This is only needed if one is creating recipes for others to use. It is not required for the calculation of nutrients.
(O)Many other attributes could be collected for recipe documentation, such as remarks; a couple of hints lines; where the recipe is used; its main product, its product group, its type, its density, various dates such as date created, tested, analyzed, converted and preparation time.
This defines a single recipe which then becomes a single entry in the database.
First Nations Food, Nutrition and Environment Study
We are a multi-organization research team (University of Northern British Columbia, University of Ottawa, Université de Montréal, Assembly of First Nations and Health Canada) that has used CANDAT since 2008. So far, we have used CANDAT to enter over 5000 single and repeated recalls. The software is easy to learn and use. One of our students doing data entry mentioned that CANDAT was easier and more friendly to use than another program he had been using. We are able to incorporate traditional foods and recipes from our study easily into the database. The software developer is always open to suggestions from CANDAT users to facilitate data entry, such as viewing the food description when reviewing data entry and automatic repeat of past key word searches. Above all, the technical support provided by Godin London Incorporated (Gaetan) is always top-notch. He is prompt to answer questions and to solve problems. Recently, we requested a new feature which would enable users to view the food description when reviewing data entry and they were able to do this within a few days. Also, when validation of a dietary file with a more recent version of the Canadian Nutrient File was needed, they were able to write a program that allowed the file to be imported back into CANDAT (from SAS).
This was all done under the no-charge support provided with all CANDAT licences. I would highly recommend CANDAT to any nutrition researcher. Gaetan always strives to adapt CANDAT’s capabilities to suit its users.
Amy Ing, M.Sc. Data Analyst First Nations Food, Nutrition and Environment Study www.fnfnes.ca
University of Guelph
I have used Candat for many years for the analysis of 24 hour recall data, and for the development and subsequent analysis of food frequency questionnaires for two different studies. The range of analytic options provided by Candat, and the fact that it is based on the latest version of the Canadian Nutrient File, are key features.
Assistance with the development of FFQs and translation of responses into the format that can be analyzed with Candat is available on an as needed and timely basis. Response is usually within 24 hours. And, there is no problem asking for help.
I have used Candat for years because of GLI’s knowledge and continuous efforts to make the software ever more powerful.
Susan Evers PhD
Professor
Department of Family Relations and Applied Nutrition
University of Guelph
Guelph, Ontario, N1G 2W1
University of PEI
CANDAT is superior to other nutrient analysis programs because it is designed to accommodate the diverse needs of researchers. Being able to handle food recalls and records and food frequency questionnaires in the same program, to create user files of special food items not included in the CNF and to easily import files into statistical analysis packages makes it unique in Canada. Most of all, having a support person who has extensive experience with nutrition researchers makes CANDAT an easy choice for me.
I have been working with CANDAT since 1984, and have also tried a number of other nutrient analysis programs. I keep coming back to CANDAT for two reasons: the support with CANDAT is superb. I have emailed Gaetan and received a phone call within minutes. He “knows his stuff” and can pinpoint and resolve any problems or challenges quickly. The program he uses to take over the computer is amazing and very efficient.
Since he has worked with a number of academics in nutrition, he understands research and the special needs researchers have. My research group had a challenging task a few years ago which involved adapting an American Food Frequency questionnaire for Canadian use and adding data on dietary nitrates. This was a very complex and time consuming task, and Gaetan was an active participant in the research process. When we were under time pressures to complete the analysis, Gaetan committed time and was able to get us the data when we needed it. He goes beyond a technical role, and sometimes poses questions which I don’t think of, preventing problems before they happen.
Dr. Jennifer Taylor, Associate Professor & Chair
Department of Family & Nutritional Sciences
Dalton Hall 204
University of Prince Edward Island
550 University Ave, Charlottetown PEI C1A 4P3 (902)
566-0475 Fax (902) 628-4367
McGill University
We use CANDAT because it is the best software giving access to the Canadian Nutrient File (CNF) that we have been able to find. It allows us to structure our data to provide the results that we need. For example, we have made consistent use of the food grouping capability that provides us with nutrients from these food groups so we can write manuscripts pertaining not only to the nutrients but also the food sources in the Canadian population. Support from the software provider is exceptional and very responsive to user needs. For example, when Health Canada removed some units from the Canadian nutrient file that were essential to the data entry, Godin London Incorporated extracted these from an older version of the CNF and added these back to CANDAT. Godin London Incorporated has also responded to our needs by adding functions that save us time when doing corrections and data cleaning.
Louise Johnson-Down
Survey Coordinator Food habits of Canadians
McGill University 21,111 Lakeshore
Ste Anne de Bellevue QC
H9X 3V9
Tel:514-398-7808
Fax: 514-398-7739
Essential CANDAT information
This section explains the CANDAT software environment. You need to have a feeling for the following three areas:
Navigating CANDAT, how to get to and start the tasks;
How to respond to typical prompts within the task:
for selecting database files;
for selecting individual records within those files;
for printing;
The computer structure of folders and sub-folders that support CANDAT
CANDAT Environment (GRASP)
GRASP (General Reporting and Application Support Package) is an environment which contains standard mechanisms for communicating between the user and the computer. This allows for consistency within applications and is the background within which CANDAT is defined.
GRASP assumes a well defined user area on the disk (usually created at installation) and a structure of modules and tasks. Modules identify broad areas of functionality. There are modules for food files, nutrient tables, category (food group) definitions and RNI tables, subject files, recipe files, food frequency (history) questionnaires, and file maintenance utilities. Tasks define the functianlity of CANDAT and together, define the tasks required for food intake research.
Menu navigation
The basic functional unit of an application is the task. There is a two level menu structure that directs the user to the task required. The first level lists general areas of the application., the second lists the tasks. We will use CANDAT as an example application to show menus. The first and A second level menu of CANDAT are shown here:
To choose a particular item in a menu just cursor down to that item and press Enter or type the first character ot the item. In this case, the “4” was pressed which immediately brought up the Recipe menu. Pressing Enter on the first item in the Recipe menu, in this case 400 Recipe file maintenance, essentially Task400 in the CANDAT system, would activate that task and bring up the following menu, a menu common to all the tasks.
Task startup menu
Once a task has been chosen and it has been read in by the computer, the following menu is displayed:
At the end of a task, the same menu appears again. You can choose at this point to restart the task by choosing the first option again.
There are two ways to exit from CANDAT. One is temporary and leaves CANDAT in memory, ready to be reactivated. This is the EXIT to DOS choice. To return to CANDAT after choosing this alternative, simply type EXIT from within DOS and you will be returned to CANDAT. Do not try to start a new session of CANDAT if you exited this way. You will quickly use up all of your memory and may not be able to start another session if you do so. If you choose QUIT and return to the operating system, CANDAT is released from memory and terminates normally.
Data entry prompts
CANDAT prompts you for information in the form of a list of choices or tables. Lists are referred to as menus, not to be confused with menus used in restaurants. CANDAT will also prompt you for single field entries as in food codes, date of recalls, etc. An entry of a blank code or a 0 serves to cancel the prompt.
There are three kinds of menus presented in CANDAT.
The usual menu is a list of items. You are expected to make a single choice. That is done by moving the selection bar (cursor) to the choice and pressing the enter key. Another way of accomplishing the same thing is to enter the first letter or number of the choice. Pressing the Esc (escape) key chooses the last item in the list or exits menu selection without making a choice.
Another menu type gives you a series of Yes/No items which you toggle by pressing the Y or N keys. You can also make all the choices Y or all N by pressing the Alt key with your selection of Y or N.
The third menu selection consists of a single field at the bottom of the screen. This field usually expects a record key (in the case of a food database, this would be the food code, in the case of a recipe database, this would be the recipe code). The F6 key, found in the row of F keys at the top of your keyboard, serves as an information key. Pressing it will give you various options, from a simple list of codes that you can enter in the field to a search bar in which you can put keywords that are found in the description of the item. In either case you can choice the desired item from the list of items that appears and the proper code will be entered in the field automatically. Keyword searches are very simple. If you put in two keywords, seperated by a space, both must be present in the description in order for the search to be successful. If you wish one item or the other or both, seperate the keywords with a comma.
There are two kinds of table entry in CANDAT.
The usual table entry allows you to enter information within each cell of a table. Some cells will only allow numbers, others, both numbers and characters. Whichever is allowed will be obvious from the context. If you try to enter a character and it does not appear in the cell, the cell is probably expecting a number. Blank cells are considered filled with characters and you will not be allowed to move out of a number cell until you insert a number. A 0 is usually sufficient. If this entry resulted in an extra line being added to the table, it can usually be removed using Alt F4 (see below). Some of these tables grow automatically as you try to enter another row. Pressing the Enter key in the last cell of the last row of a table activates this feature. You cannot simply move to a row that does not exist by using cursor controls. Other rows can be inserted and deleted in these “growing” tables by using Alt F3 to add lines and Alt F4 to delete lines. To exit after having entered your information, press the Esc key. You can move from cell to cell by pressing Tab (or back Tab) and by using the cursor control keys. You can also use Ctrl Home and Ctrl End to go to the first and last cells respectively. In some contexts the function keys F1 and F6 will provide you with additional information which is just shown (in the case of F1) or serves as input based on your choice in the case of F6.
The other type of table entry allows editing of a full line at a time. This is a free form type of entry. and you need to be careful of the layout of the information as it is not controlled by the software. To exit after having entered this information you must press Ctrl E or Ctrl Q. Ctrl E will save your entries, Ctrl Q will quit without saving your entries. CANDAT has very few of these types of table entry.
Printing reports
Reports produced by CANDAT can be sent to a printer, a file or both and, in the case of subject calculated data (task 340), to documented files. CANDAT is configured to print to LPT1 (or text files if you wish). The printer definition within CANDAT which ensures printing to LPT1 is called PRNTLPT1. It can be set in Activate System Utilities menu, under Activity Options menu. Activity Options is available as a menu item in each Module or Task selection menu as well as in the Task startup menu. This is explained in more detail under those menus.
In order to use your Windows printers you need a software such as DOS2USP which captures the LPT1 port. It can be obtained here as a trial version and as a permanent version for a very low cost. The advantage of printing to Windows printers is that you can create PDF files from CANDAT output and be better able to manage the large volumes of data produced. A configuration of that program which works well with CANDAT is shown here:
Once installed and these settings defined (do not forget to click on Save Settings) you can forget about the DOS2USP program. It will always be on your computer, will start when you start Windows and will just be used with CANDAT or some other DOS program you may have on your computer. Set it up once and forget about it.
Paper definitions
CANDAT uses paper size to layout reports for printing. Please note that this paper size is independent from the one above. Paper size is a menu item under Activity Options (see above). Paper size is always defined in portrait mode, even if you wish to print in landscape mode (sideways). CANDAT determines the size of the report in relation to the size of the paper available. A few reports cannot print on paper 8.5 in. wide. These reports need to be printed on wider paper or need to be printed in landscape mode. When CANDAT detects this situation, it prompts you to change your paper definition so that it can continue. You must then switch to landscape (if you have landscape capabilities on your printer) or specify wider paper.
Printer definitions
The DOS2USB program allows you to define the print device (which can be a .PDF file), the font and the font size to use for the report. This printer definition works in conjunction with CANDAT to provide the printed (or visual) representation of the reports. CANDAT defines the width of the report and the length of the pages based on its paper definition (see above). DOS2USB makes this definition fit on a page or on the screen.
Most of the reports in CANDAT are presented in a table form. A fixed font (such as Courier New) is preferable as it uses characters that are all the same width. An “M” has the same width as an “I”. A “1″ has the same width as a “0″. This allows columns of data and numbers to line up properly and be easier to read. Font size is set here too. Please note that these sizes are in CPI (Characters per inch) and not in dots per inch as in windows. A larger CPI results in smaller characters and vice versa. A bit of experimenting with the paper setups of CANDAT and the printer setups of DOS2USB will have you producing beautiful reports very quickly.
Output to text files
Most of the reports in CANDAT which can print on paper can also print to files. You are prompted for the file name and the file is created in your user area (see Structure – Users, below). Use eight characters only for file names, no spaces and no special characters. CANDAT will append an extension of .TXT to these files so that they are readily identifiable. All such files will be created in the user folder identified at CANDAT installation.
You have a choice of printing with printer control codes or not. Printing without control codes makes the assumption you will be importing the information into a word processing or other type of program using “cut-and-paste”. Titles and headers are then also not printed. If you wish to print to file with titles and headers and no control codes, specify printer type “none” and print to files specifying control codes. The “none” printer type does not output printer control codes.
Output to save files
Reports that are the result of nutrient calculations can be output to files that you can either open with a word processor or import into a spreadsheet environment (like Excel) or adatabase environment (like SAS, SPSS or other statistical package) . You are prompted for a file name and different files are created using those names in your user SAVE area. Use eight characters only for file names, no spaces and no special characters. CANDAT will append various extensions to these files so that they are readily identifiable. All such files will be created in the user folder, sub-folder SAVE, identified at CANDAT installation.
Structure – Users
CANDAT is licensed on a per computer basis. CANDAT may be installed on only those computers and networks for which it is licensed. It is possible for multiple users to use CANDAT simultaneously when installed in a network. You are only allowed the number of simultaneous users negotiated in your purchase agreement.
Any one license (on one computer) can and is allowed to support any number of users. Users are created within CANDAT using a NEWUSER2 creation process. This process creates a folder for the user, specific to the disk (memory stick or other USB device) drive specified at creation. Note that CANDAT records the drive on which the user is created. Users must function on the drive specified at creation in order for CANDAT to be able to function properly. This is particularly important in a laboratory structure where users may connect their memory sticks to a USB port and create their own environment. CANDAT creates an icon with the particulars of the user drive. A user can manually change the drive in the properties of this icon to correspond to the drive of their memory stick, if used on another computer. For instance, a user could create an environment on their memory stick under the “F” drive in the laboratory environment and then need to use it on the “G” drive of another computer.
User folders store food files, category files, subject files, questionnaire files, save files, and recipe files. For a user to use another user’s files, those files must be copied to the relevant user folder. There is no user identification on the files themselves. This structure also allows the same (project) name to be used for each of the food, category, subject, etc. files. Please note that the user structure and files is never deleted by CANDAT or by re-installation of CANDAT. It is always prudent, however, to fully backup the user structure and its files.
Structure – Modules and Tasks
CANDAT has a unique structure for Users and for Food files. The actual work performed by CANDAT is organized in a structure of Modules and Tasks.
Modules identify broad areas of functionality. There are modules for food files, nutrient tables, category (food group) definitions and RNI tables, subject files, recipe files, food frequency (history) questionnaires, and file maintenance utilities.
Tasks are found within modules and provide the detailed interaction with the User. It is within tasks that subject data is entered, recipes and food files are created, nutrient data is calculated, reports are produced, etc. The titles of the modules are self explanatory as are the titles of the tasks. Follow the prompts within the tasks and you should be able to accomplish your work with ease.
Introduction
This section shows you how to install CANDAT and the first steps to actually using it. For more information please use the contact us link on this website.
Preface
These links give you some background on CANDAT and a bit of an idea as to how you should publish your findings.
Publications
Please refer to the links below for more information.
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Citations
Some publications that mention using CANDAT
(please note that articles in journals, books, masters and PhD theses are in this growing list)
Alder, Robert J., Gail McKeown-Eyssen, and Elizabeth Bright-See. “Randomized trial of the effect of calcium supplementation on fecal risk factors for colorectal cancer.” American journal of epidemiology 138.10 (1993): 804-814.
Allès, Benjamin, et al. “Nutrient patterns in older persons from France and Quebec: comparisons of dietary, lifestyle and socio-economic characteristics.” NUTRITION (2013): 181578.
Allès, Benjamin. “DOCTORAT DE L’UNIVERSITE BORDEAUX 2.”
Alles, Benjamin. Profils de comportement alimentaire et déclin cognitif chez les personnes âgées en Aquitaine et au Québec. Diss. Bordeaux 2, 2013.
Andraea Van Hulst, Marie-Hélène Roy-Gagnon, Lise Gauvin, Yan Kestens, Mélanie Henderson, Tracie A Barnett. “Identifying risk profiles for childhood obesity using recursive partitioning based on individual, familial, and neighborhood environment factors” International Journal of Behavioral Nutrition and Physical Activity 2015, 12:17 (15 February 2015)
Arguin, Hélene, et al. “Short-and long-term effects of continuous versus intermittent restrictive diet approaches on body composition and the metabolic profile in overweight and obese postmenopausal women: a pilot study.” Menopause 19.8 (2012): 870-876.
Atikessé, Laura, et al. “Innu food consumption patterns: traditional food and body mass index.” Canadian Journal of Dietetic Practice and Research 71.3 (2010): e41-e49.
Aubertin‐Leheudre, Mylène, et al. “Effect of sarcopenia on cardiovascular disease risk factors in obese postmenopausal women.” Obesity 14.12 (2006): 2277-2283.
Aubertin-Leheudre, Mylène, et al. “Isoflavones and clinical cardiovascular risk factors in obese postmenopausal women: a randomized double-blind placebo-controlled trial.” Journal of Women’s Health 17.8 (2008): 1363-1369.
BOFEGL FISH – 1998 – nlc-bnc.ca FISH, BENEFITS OF EATING GREAT LAKES. “AN ASSESSMENT OF THE NUTRITION-RELATED.” (1998).
Baraké, Roula, et al. “Vitamin D supplement consumption is required to achieve a minimal target 25-hydroxyvitamin D concentration of≥ 75 nmol/L in older people.” The Journal of nutrition 140.3 (2010): 551-556.
Barake, Roula Ismail. Correlates and Consequences of Vitamin D Status in Older People. Diss. McGill University, 2009.
Benson, Victoria S., et al. “Type 1 diabetes mellitus and components in drinking water and diet: a population-based, case-control study in Prince Edward Island, Canada.” Journal of the American College of Nutrition 29.6 (2010): 612-624.
Bobeuf, F., et al. “Combined effect of antioxidant supplementation and resistance training on oxidative stress markers, muscle and body composition in an elderly population.” The journal of nutrition, health & aging 15.10 (2011): 883-889.
Borduas, Julie. “Conciliation des bénéfices et risques de la consommation de nourriture traditionnelle atikamekw: l’utilisation des questionnaires alimentaires pour dégager le profil de l’exposition au méthylmercure.” (2008).
Bouchard, Danielle R. Obésité et capacité physique chez la personne âgée. Université de Sherbrooke, 2008.
Bright‐See, E., et al. “Dietary fiber and cancer: a supplement for intervention studies.” (1985): 211-220.
Bright-See, E., V. Jazmaji, and C. A. Benda. “Computerized food and nutrient calculation for research.” Journal of the Canadian Dietetic Association (1986).
Campbell, Cathy C., and Ellen Desjardins. “A model and research approach for studying the management of limited food resources by low income families.” Journal of Nutrition Education 21.4 (1989): 162-171.
Campbell, Martha Karen, et al. “Determinants of small for gestational age birth at term.” Paediatric and perinatal epidemiology 26.6 (2012): 525-533.
Caron, Marie-Noëlle. Étude transversale comparative des effets des apports nutritionnels en lipides et en antioxydants sur les marqueurs du stress oxydatif chez le sujet âgé atteint de diabète mellitus de type 2 versus chez le sujet âgé non-diabétique. Université de Sherbrooke, 2004.
Chan, Laurie, et al. ““Our waters, our fish, our people” Mercury contamination in fish resources of two Treaty# 3 communities.”
Chaput, J‐P., et al. “Physical activity vs. sedentary time: independent associations with adiposity in children.” Pediatric obesity 7.3 (2012): 251-258.
Chaput, Jean-Philippe, et al. “Combined associations between moderate to vigorous physical activity and sedentary behaviour with cardiometabolic risk factors in children.” Applied Physiology, Nutrition, and Metabolism 38.5 (2013): 477-483.
Chaput, Jean-Philippe, et al. “Is overweight/obesity associated with short sleep duration in older women?.” Aging clinical and experimental research 19.4 (2007): 290-294.
Chaput, Jean-Philippe, et al. “Short sleep duration is independently associated with overweight and obesity in Quebec children.” Canadian Journal of Public Health/Revue Canadienne de Sante’e Publique (2011): 369-374.
Chaput, Jean-Philippe. Relation entre l’apport en antioxidants alimentaires et la sarcopénie de type I chez des personnes âgées de 60 à 75 ans. Université de Sherbrooke, 2004.
Choquette, S. T. E. P. H. A. N. E., et al. “Predicting energy expenditure in elders with the metabolic cost of activities.” Medicine and science in sports and exercise 41.10 (2009): 1915-1920.
Cole, Donald C., et al. “Dietary intakes and plasma organochlorine contaminant levels among Great Lakes fish eaters.” Archives of Environmental Health: An International Journal 57.5 (2002): 496-509.
Cusson, Valérie. “Évaluation du lien entre l’état de santé dentaire et l’état nutritionnel chez les personnes âgées.” (2015).
Deschesnes, Bruno Riverin. Étude transversale sur le statut en vitamine D et ses déterminants chez les Cris du nord du Québec. Diss. Université Laval, 2014.
Doran, Lori, and Susan Evers. “Energy and nutrient inadequacies in the diets of low-income women who breast-feed.” Journal of the American dietetic association 97.11 (1997): 1283-1287.
Egeland, Grace M., et al. “Food insecurity and nutrition transition combine to affect nutrient intakes in Canadian Arctic communities.” The Journal of nutrition 141.9 (2011): 1746-1753.
Egeland, Grace M., et al. “Food insecurity and nutrition transition combine to affect nutrient intakes in Canadian Arctic communities.” The Journal of nutrition141.9 (2011): 1746-1753.
Eid, Lara. “Association entre l’insécurité alimentaire et les apports en nutriments chez les Premières Nations de la Colombie-Britannique.” (2011).
El Hayek, Jessy, Grace Egeland, and Hope Weiler. “Higher body mass, older age and higher monounsaturated fatty acids intake reflect better quantitative ultrasound parameters in Inuit preschoolers.” International journal of circumpolar health 71 (2012).
El Hayek, Jessy, Grace Egeland, and Hope Weiler. “Vitamin D status of Inuit preschoolers reflects season and vitamin D intake.” The Journal of nutrition140.10 (2010): 1839-1845.
El Hayek, Jessy, et al. “Forearm Bone Mineral Density Varies as a Function of Adiposity in Inuit Women 40–90 Years of Age During the Vitamin D–Synthesizing Period.” Calcified tissue international 90.5 (2012): 384-395.
El Hayek, Jessy. Correlates of vitamin D status in Inuit preschoolers and adults and correlates of. Diss. McGill University, 2011.
Evers, Susan E., and Michelle D. Hooper. “Dietary intake and anthropometric status of 7 to 9 year old children in economically disadvantaged communities in Ontario.” Journal of the American College of Nutrition 14.6 (1995): 595-603.
Fogler-Levitt, Elizabeth, et al. “Utilization of home-delivered meals by recipients 75 years of age or older.” Journal of the American Dietetic Association 95.5 (1995): 552-557.
Fowler, Jennifer K., Susan E. Evers, and M. Karen Campbell. “Inadequate Dietary Intakes: Among Pregnant Women.” Canadian Journal of Dietetic Practice and Research 73.2 (2012): 72-77.
Gallant, Annette R., et al. “Validity of the night eating questionnaire in children.”International Journal of Eating Disorders 45.7 (2012): 861-865.
Gaudreau, Pierrette, et al. “Nutrition as a determinant of successful aging: description of the Quebec longitudinal study Nuage and results from cross-sectional pilot studies.” Rejuvenation research 10.3 (2007): 377-386.
Gougeon, L., et al. “Dietary patterns and incidence of depression in a cohort of community-dwelling older Canadians.” The journal of nutrition, health & aging: 1-6.
Goulet, Eric DB, et al. “No difference in insulin sensitivity between healthy postmenopausal women with or without sarcopenia: a pilot study.” Applied Physiology, Nutrition, and Metabolism 32.3 (2007): 426-433.
Goulet, Eric, et al. “INSULIN SENSITIVITY AMONG HEALTHY, NONOBESE POSTMENOPAUSAL WOMEN WITH VARIOUS DEGREES OF SKELETAL MUSCLE MASS.” Journal of Exercise Physiology Online 11.1 (2008).
Goulet, Eric, et al. “Sensibilidad a la Insulina en Mujeres Saludables, no Obesas y Post-Menopáusicas con Diferentes Niveles de Masa de Músculo Esquelético.” PubliCE Premium (2008).
Gray-Donald, Katherine, et al. “Protein intake protects against weight loss in healthy community-dwelling older adults.” The Journal of nutrition 144.3 (2014): 321-326.
Hamdan, N. M., et al. “Do implant overdentures improve dietary intake? a randomized clinical trial.” Journal of dental research (2013): 0022034513504948.
Henderson, Mélanie, Andrea Benedetti, and Katherine Gray-Donald. “Dietary composition and its associations with insulin sensitivity and insulin secretion in youth.” British Journal of Nutrition 111.03 (2014): 527-534.
Hennessy-Priest, Kathleen A., et al. “Zinc-fortified foods do not improve intake of total dietary zinc for Ontario preschoolers.” Journal of the American College of Nutrition 27.5 (2008): 561-568.
Hennessy-Priest, Kathleen, et al. “Folic acid food fortification prevents inadequate folate intake among preschoolers from Ontario.” Public health nutrition 12.09 (2009): 1548-1555.
Hooper, Michelle, and Susan Evers. “What do Ontario children eat for breakfast? Food group, energy and macronutrient intake.” Canadian Journal of Dietetic Practice and Research 64.1 (2003): 28-30.
Huet, Catherine, Renata Rosol, and Grace M. Egeland. “The prevalence of food insecurity is high and the diet quality poor in Inuit communities.” The Journal of nutrition 142.3 (2012): 541-547.
Huet, Catherine. Prevalence and correlates of food insecurity in Inuit communities. Diss. McGill University, 2010.
Jacobs, Ira, et al. Physical performance and carbohydrate consumption in CF Commandos during a 5-day field trial. No. DCIEM-89-RR-48. DEFENCE AND CIVIL INST OF ENVIRONMENTAL MEDICINE DOWNSVIEW (ONTARIO), 1989.
Jamieson, Jennifer A. Correlates of iron status, hemoglobin and anemia in Inuit adults. Diss. McGill University, 2012.
Jamieson, Jennifer A., et al. “Higher n3-fatty acid status is associated with lower risk of iron depletion among food insecure Canadian Inuit women.” BMC public health 13.1 (2013): 289.
Jamieson, Jennifer A., et al. “Traditional food intake is correlated with iron stores in Canadian Inuit men.” The Journal of nutrition 142.4 (2012): 764-770.
Jobin, Louise. La relation entre une dépression légère et la dénutrition chez les personnes âgées en perte d’autonomie à domicile. Université de Sherbrooke, 2004.
Johnson-Down, Louise M., and Grace M. Egeland. “How is nutrition transition affecting dietary adequacy in Eeyouch (Cree) adults of Northern Quebec, Canada?.” Applied Physiology, Nutrition, and Metabolism 38.3 (2012): 300-305.
Johnson-Down, Louise, and Grace M. Egeland. “Adequate nutrient intakes are associated with traditional food consumption in Nunavut Inuit children aged 3–5 years.” The Journal of nutrition 140.7 (2010): 1311-1316.
Johnson-Down, Louise, et al. “Appropriate calcium fortification of the food supply presents a challenge.” The Journal of nutrition 133.7 (2003): 2232-2238.
Johnson-Down, Louise, et al. “Primary food sources of nutrients in the diet of Canadian adults.” Canadian Journal of Dietetic Practice and Research 67.1 (2006): 7-13.
Kâ, Khady, et al. “Circulating undercarboxylated osteocalcin and gingival crevicular fluid tumour necrosis factor‐α in children.” Journal of clinical periodontology 41.5 (2014): 467-472.
Keller, Heather H., et al. “Activity limitation and food intake in community-living seniors.” Canadian Journal on Aging/La Revue canadienne du vieillissement 18.01 (1999): 47-63.
Khalil, Abdelouahed, et al. “Antioxidant-rich food intakes and their association with blood total antioxidant status and vitamin C and E levels in community-dwelling seniors from the Quebec longitudinal study NuAge.” Experimental gerontology 46.6 (2011): 475-481.
Khalil, Cynthia Bou, Louise Johnson-Down, and Grace M. Egeland. “Emerging obesity and dietary habits among James Bay Cree youth.” Public health nutrition 13.11 (2010): 1829-1837.
Khalil, Cynthia Bou. Emerging Obesity and Dietary Habits Among James Bay Cree Youth: 3 Communities. Diss. McGill University, 2008.
Krondl, Magdalena, et al. “Subjectively healthy elderly consuming a liquid nutrition supplement maintained body mass index and improved some nutritional parameters and perceived well-being.” Journal of the American Dietetic Association 99.12 (1999): 1542-1548.
Krondl, Magdalena, et al. “Tailoring of nutritional support for older adults in the community.” Journal of Nutrition for the Elderly 23.2 (2003): 17-32.
Kuhnlein, Harriet V., et al. “Arctic indigenous peoples experience the nutrition transition with changing dietary patterns and obesity.” The Journal of nutrition134.6 (2004): 1447-1453.
Kuperberg, Karen N. KAREN N. KUPERBERG. Diss. The University of Guelph, 2002.
Kuperberg, Karen, and Susan Evers. “Feeding patterns and weight among First Nations children.” Canadian Journal of Dietetic Practice and Research 67.2 (2006): 79-84.
Labonté, Mélissa. “Effet des vitamines C et E combinées à un programme d’exercices en musculation sur la masse musculaire chez des sujets âgés.” (2006).
Legrand, Melissa, et al. “Mercury exposure in two coastal communities of the Bay of Fundy, Canada.” Environmental research 98.1 (2005): 14-21.
Leuenberger, Paula K., et al. “Determination of peak trabecular bone density: interplay of dietary fiber, carbohydrate, and androgens.” The American journal of clinical nutrition 50.5 (1989): 955-961.
Ménard, Julie, et al. “Efficacy of intensive multitherapy for patients with type 2 diabetes mellitus: a randomized controlled trial.” Canadian Medical Association Journal 173.12 (2005): 1457-1466.
MacLellan, Debbie, Jennifer Taylor, and Kyla Wood. “Food intake and academic performance among adolescents.” Canadian Journal of Dietetic Practice and Research 69.3 (2008): 141-144.
Mailhac, Aurélie. Boissons sucrées en relation avec l’insulinorésistance chez les jeunes cris de la Baie James. Diss. Université Laval, 2014.
Mannion, Cynthia A., Katherine Gray-Donald, and Kristine G. Koski. “Association of low intake of milk and vitamin D during pregnancy with decreased birth weight.” Canadian Medical Association Journal 174.9 (2006): 1273-1277.
Mannion, Cynthia A., and Robin J. Lindop. “Vitamin/mineral supplements and calcium-based antacids increase maternal calcium intake.” Journal of the American College of Nutrition 28.4 (2009): 362-368.
Mannion, Cynthia A., et al. “Lactating women restricting milk are low on select nutrients.” Journal of the American College of Nutrition 26.2 (2007): 149-155.
Mark, S., et al. “Higher vitamin D intake is needed to achieve serum 25 (OH) D levels greater than 50 nmol/l in Quebec youth at high risk of obesity.” European journal of clinical nutrition 65.4 (2011): 486-492.
Matta, Joane, et al. “Interrelated factors favoring physical performance and activity in older adults from the NuAge cohort study.” Experimental gerontology 55 (2014): 37-43.
Matta, Joane, et al. “Interrelated factors favoring physical performance and activity in older adults from the NuAge cohort study.” Experimental gerontology55 (2014): 37-43.
McKEOWN-EYSSEN, GAIL E., KA SING YEUNG, and E. L. I. Z. A. B. E. T. H. BRIGHT-SEE. “Assessment of past diet in epidemiologic studies.”American journal of epidemiology 124.1 (1986): 94-103.
Mutoni, Sandrine. “Dietary patterns associated with diet quality among First Nations women living on reserves in British Columbia.” (2012).
Nancarrow, Tanya L., Hing Man Chan, and Harriet V. Kuhnlein. “Climate change impacts on dietary nutrient status of Inuit in Nunavut, Canada.” The FASEB Journal 22.1_MeetingAbstracts (2008): 1096-7.
Nash, Danielle M., et al. “Determinants of Diet Quality in Pregnancy: Sociodemographic, Pregnancy-specific, and Food Environment Influences.” Journal of nutrition education and behavior 45.6 (2013): 627-634.
Nash, Danielle M., et al. “Determinants of Diet Quality in Pregnancy: Sociodemographic, Pregnancy-specific, and Food Environment Influences.”Journal of nutrition education and behavior 45.6 (2013): 627-634.
Nutrition Journal 2012, 11:73 (18 September 2012)
Onyango, Adelheid, Katherine Tucker, and Thomas Eisemon. “Household headship and child nutrition: A case study in western Kenya.” Social Science & Medicine 39.12 (1994): 1633-1639.
Osher, Susan. ONE-CARBON METABOLISM IN ADULTS WlTH MAJOR DEPRESSION. Diss. University of Toronto.
Ounpuu, Stephanie, Donna M. Woolcott, and Geoffrey W. Greene. “Defining Stage-of-Change for Lower-Fat Eating.” Journal of the American Dietetic Association 100.6 (2000): 674-679.
Pacey, A., T. Nancarrow, and G. M. Egeland. “Prevalence and risk factors for parental-reported oral health of Inuit preschoolers: Nunavut Inuit Child Health Survey, 2007–2008.” Rural Remote Health 10.2 (2010): 1368.
Pacey, Angela, Hope Weiler, and Grace M. Egeland. “Low prevalence of iron-deficiency anaemia among Inuit preschool children: Nunavut Inuit Child Health Survey, 2007–2008.” Public health nutrition 14.08 (2011): 1415-1423.
Pacey, Angela. Iron deficiency and iron deficiency anemia among preschool aged Inuit children living in Nunavut. Diss. McGill University, 2009.
Palaniappan, U., et al. “Implications of day-to-day variability on measurements of usual food and nutrient intakes.” The Journal of nutrition 133.1 (2003): 232-235.
Palaniappan, Uma, et al. “Fruit and vegetable consumption is lower and saturated fat intake is higher among Canadians reporting smoking.” The Journal of nutrition 131.7 (2001): 1952-1958.
Phillips, Sandy, Linda Jacobs Starkey, and Katherine Gray-Donald. “Food habits of Canadians: food sources of nutrients for the adolescent sample.”Canadian Journal of Dietetic Practice and Research 65.2 (2004): 81-84.
Pomerleau, Joceline, Truls Østbye, and Elizabeth Bright-See. “Potential underreporting of energy intake in the Ontario Health Survey and its relationship with nutrient and food intakes.” European journal of epidemiology 15.6 (1999): 553-557.
Presse, Nancy, et al. “A minimum of six days of diet recording is needed to assess usual vitamin K intake among older adults.” The Journal of nutrition 141.2 (2011): 341-346.
Presse, Nancy. “Vitamine K et fonctions cognitives chez la personne âgée en santé: une approche épidémiologique nutritionnelle.” (2012).
Pronovost, Amy. Vitamin D status and bone health in Inuit women 40 years of age and older. Diss. McGill University, 2009.
Rahi, Berna, et al. “Decline in functional capacity is unaffected by diet quality alone or in combination with physical activity among generally healthy older adults with T2D from the NuAge cohort.” Diabetes research and clinical practice 105.3 (2014): 399-407.
Rahi, Berna, et al. “The combined effects of diet quality and physical activity on maintenance of muscle strength among diabetic older adults from the NuAge cohort.” Experimental gerontology 49 (2014): 40-46.
Ritter, Heidi. Food Group Contribution to the Energy and Nutrient Intake of the Adult Canadian Population. Diss. McGill University, 2000.
Riverin, Bruno, et al. “Prevalence of vitamin D insufficiency among healthy school-age Cree children.” Paediatrics & child health 19.3 (2014): e15-9.
Rossi, Monsieur Paul-Georges. “Quebec cm.” – Rapport – Portions maximales des aliments traditionnels chez les Cris de la Baie James. Louise Johnson-Down M Sc. DtP 26 Novembre 2014
Rossiter, Melissa D., Susan E. Evers, and Amy C. Pender. “Adolescents’ diets do not comply with 2007 Canada’s food guide recommendations.” Appetite 59.3 (2012): 668-672.
Roy, A., S. E. Evers, and M. K. Campbell. “Dietary supplement use and iron, zinc and folate intake in pregnant women in London, Ontario.” Chronic Dis Inj Can 32.2 (2012): 76-83.
Roy, A., S. E. Evers, and M. K. Campbell. “Utilisation de suppléments alimentaires et apport en fer, en zinc et en folate chez les femmes enceintes de london, Ontario.”
Roy, Amrita, et al. “Higher zinc intake buffers the impact of stress on depressive symptoms in pregnancy.” Nutrition research 30.10 (2010): 695-704.
Sénéchal, M., et al. “Weight gain since menopause and its associations with weight loss maintenance in obese postmenopausal women.” Clinical interventions in aging 6 (2011): 221.
Sénéchal, Martin, et al. “Effects of rapid or slow weight loss on body composition and metabolic risk factors in obese postmenopausal women. A pilot study.” Appetite 58.3 (2012): 831-834.
Saudny, Helga, Donna Leggee, and Grace Egeland. “Design and methods of the adult Inuit health survey 2007–2008.” International journal of circumpolar health 71 (2012).
Schmid, M. A., et al. “Traditional food consumption and nutritional status of Dalit mothers in rural Andhra Pradesh, South India.” European journal of clinical nutrition 60.11 (2006): 1277-1283.
Schmid, Martina, et al. “Intervention with traditional food as a major source of energy, protein, iron, vitamin C and vitamin A for rural Dalit mothers and young children in Andhra Pradesh, South India.” Asia Pacific journal of clinical nutrition 16.1 (2007): 84.
Shang, Lei, et al. “The association between food patterns and adiposity among Canadian children at risk of overweight.” Applied Physiology, Nutrition, and Metabolism 39.2 (2013): 195-201.
Shatenstein, Bryna, et al. “Examining the relative validity of an adult food frequency questionnaire in children and adolescents.” Journal of pediatric gastroenterology and nutrition 51.5 (2010): 645-652.
Sontrop, Jessica, et al. “Depressive symptoms during pregnancy in relation to fish consumption and intake of n‐3 polyunsaturated fatty acids.” Paediatric and perinatal epidemiology 22.4 (2008): 389-399.
Sparks, Sarah M. NUTRIENT COMPOSITION OF ELEMENTARY CHILDREN’S LUNCHES: CHANGES IN LUNCHTIME NUTRIENT INTAKES ASSOCIATED WITH THE INTRODUCTION OF SCHOOL NUTRITION POLICIES. Diss. University of Prince Edward Island, 2012.
Sparks, Sarah. Nutritional Quality of Children’s School Lunches: Changes in lunchtime nutrient intakes from 2007 to 2010. Diss. Masters thesis, 2012.
St-Arnaud-McKenzie, Danielle, Hélène Payette, and Katherine Gray-Donald. “Low physical function predicts either 2-year weight loss or weight gain in healthy community-dwelling older adults. The NuAge longitudinal study.” The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 65.12 (2010): 1362-1368.
St-Arnaud-McKenzie, Danielle, Hélène Payette, and Katherine Gray-Donald. “Low physical function predicts either 2-year weight loss or weight gain in healthy community-dwelling older adults. The NuAge longitudinal study.” The Journals of Gerontology Series A: Biological Sciences and Medical Sciences65.12 (2010): 1362-1368.
Stroud, Jill, et al. “Dietary intake and growth of preschoolers (3-5 years old) living in southwestern Ontario.” The FASEB Journal 21.6 (2007): A1051.
Tabacchi, Garden, et al. “Validation and reproducibility of dietary assessment methods in adolescents: a systematic literature review.” Public health nutrition17.12 (2014): 2700-2714.
Taylor, Jennifer P., et al. “Nutritional quality of children’s school lunches: differences according to food source.” Public health nutrition 15.12 (2012): 2259-2264.
Taylor, Jennifer, Magdalena Krondl, and Venket Rao. “Acetylsalicylic acid dose fails to affect energy intake of osteoarthritic elderly.” Journal of nutrition for the elderly 8.3-4 (1989): 79-96.
Traynor, Marie M., et al. “Vegetable and fruit food frequency questionnaire serves as a proxy for quantified intake.” Canadian Journal of Public Health/Revue Canadienne de Sante’e Publique (2006): 286-290.
Troppmann, Leticia, Katherine Gray-Donald, and Timothy Johns. “Supplement use: Is there any nutritional benefit?.” Journal of the American Dietetic Association 102.6 (2002): 818-825.
Tucker, Ketherine L., and Christine Lamba. “Work Patterns, Prenatal Care, and Nutritional Status of Pregnant Subsistence Farmers in Southern Malawi. Agreement# IC-58/19.” (1989).
Van Hulst, Andraea, et al. “Associations between children’s diets and features of their residential and school neighbourhood food environments.” Can J Public Health 103.9 (2012): eS48-eS54.
Verrall, Tanya, and Katherine Gray-Donald. “Impact of a food-based approach to improve iron nutrition of at-risk infants in northern Canada.” Preventive medicine 40.6 (2005): 896-903.
Wang, J. W., et al. “Adiposity and glucose intolerance exacerbate components of metabolic syndrome in children consuming sugar‐sweetened beverages: QUALITY cohort study.” Pediatric obesity 8.4 (2013): 284-293.
Wang, JiaWei, et al. “Consumption of added sugars from liquid but not solid sources predicts impaired glucose homeostasis and insulin resistance among youth at risk of obesity.” The Journal of nutrition 144.1 (2014): 81-86.
Yohannes, Sennait. Traditional Food Consumption, Anthropometry, Nutrient intake and the Emerging Relationship between Inuit Youth and Traditional Knowledge in a Baffin Island Community. Diss. McGill University, 2009.
Yuan, Wen Lun, et al. “Influence of dairy product consumption on children’s blood pressure: results from the QUALITY cohort.” Journal of the Academy of Nutrition and Dietetics 113.7 (2013): 936-941.
Zienczuk, Natalia, et al. “Dietary correlates of an at-risk BMI among Inuit adults in the Canadian high arctic: cross-sectional international polar year Inuit health survey, 2007-2008.” Nutrition journal 11.1 (2012): 73.
Folate and Vitamin A and other nutrients in CNF 2010
The most recent version of the Canadian Food File (CNF) deals with Folate and Vitamin A differently. Please read the User guide (a free download with the trial version of CANDAT10) to get an understanding of the logic behind the changes. Once you have done this simply run a Food Profile within CANDAT and look at the available nutrients and their codes. This will give you an insight into the changes in this new version of the CNF. You can also run a nutrient distribution report (Task100, Option 3) to see all the available nutrients and their relative presence in the foods. In particular this is important for folate. Folate used to have nutrient code 435, it is now 815.
Getting started
1.Download the software
From this first page of the website choose the Downloads & Trials button and navigate to the appropriate download. For the Candat application there are 4 possibilities, all with identical features. Choose the USA or Canadian version, based on your preference. Either version can access the other’s database, the ersion you choose installs with that country’s database activavted. The software allows you to change to the other database, possibly to source foods not found in your preferred database.
The other possibility depends on your computer. Choose the 32 bit version unless you have a 64 bit computer. Below, the 32 bit Canada trial is chosen.
Add the chosen version to your cart and checkout. Checkout will require your contact information and will create an account for you if you check the “create account” box..
If you choose to create an account you will always have access to your downloads without having to go through the purchase process (even if the purchase is for $0). There is no cost to create or maintain an account.
This is your confirmation of the order having been received. It has active links to download the software. You will also receive a confirmation email with these details.
If you have created an account and have signed in to the website with your account information you will be able to view and change the details of your account. Among other information you will see the list of your available downloads.
You can always install the most recent version of CANDAT over your existing version. None of your created data will be over-written, including configurations you may have set within your own CANDAT environment.
You should now use your usual download process to download the CANDAT executable and store it on an easily accessible area of your computer. “Desktop” is not a bad choice.
2.Install Candat
The process of installing CANDAT simply requires the execution of the downloaded software.
using an icon that looks like this if it is on your desktop
That should lead to the Welcome to Candat Setup Wizard, unless you are like me and have a security panel come up to confirm that you do indeed want to run this setup software.
By clicking on “Run” here we do get the Setup Wizard to start.
This is the beginning of the setup, click on “Next”
A more complete licence will be provided once you purchase Candat. Click on “I accept the agreement” and click on “Next”
These release notes give you more information on the environment in which Candat will work. Click on “Next” to continue…
This is where Candat will be installed. Click on “Next” to continue….
Each user on your computer can have his or her own area. This is where you would select the area. Report and data files will be stored in sub-directories of this area. Click on “Next” to continue…..
The folder of the start menu where Candat icons will be stored. No need to change this. Click on “Next” to continue….
… and a confirmation of your start-up choices. Click on “Next” to continue….
After the installation you will get a few useful notes. This information is also covered in the documentation should you need it. Click on “Next” to continue….
… and you are done! Congratulations. Click on “Finish” to end the installation.
This Icon should now appear on your desktop and is all you need to start using Candat on your computer.
3.Before Starting, Important Expectations:
Candat does not work like windows programs because it is not a windows program. Candat is mostly for data entry and producing reports. It is much more efficient to use the keyboard for that kind of work, you do not have to constantly remove your hand from the keys to click on a new field.
Candat does not use the mouse. It uses the tab and arrow keys as well as shortcuts using function keys (“F1”,“F5”, “F6”, Esc)
Candat will work on all windows environments, including windows environments on Apple computers, something that most windows programs today cannot do
This has allowed us to develop Candat to be the full featured program it is.
You will find Candat very easy to use and consistent. Consider it a powerful “calculation engine” with outputs that can be read by windows programs such as Excel and Word and statistical packages such as SPSS and SAS.
4.Start the trial
When this first menu appears I check the following:
Am I in the right database… the CDN10 (bottom right of the menu, under Databases) tells me I am in the Canadian nutrient file, most recent version
note the function keys references… they are always useful in Candat, not too many to remember
I still have 30 days left in my trial.
I am now ready to proceed.
5.Access the database through “Food Profile”
The first thing I do is access the database just to be sure the data works fine. For that I press the “F5” key to bring up a secondary menu, the Note Options. The nice thing about this “F5” key is that it is available to me wherever I happen to be in Candat. In this case I just want to access the Food Profile (see below) to check data.
Pressing “F5” gives me the Note Options below. To activate the Food Profile I can simply move the cursor down to that option or I can press “3” on the keyboard.
The prompts lead me to getting the desired information.
I happen to have multiple user food file in my environment. The food search feature of food profile can search foods from my specified user file too. In this case, I am choosing to include the “FOODHAB” file, Food Habits of Canadians. I could also choose <none> to just search the master and institute food file.
The following prompt appears at the bottom of the screen and is where the search becomes interesting. This window requires a food code which can be found by pressing “F6”.
There are many places in Candat that require a food code. One can enter a single word or part of a word, a combination of words separated by spaces or a combination of words separated by commas.
For instance, if I want to see all the foods that have avocado or guacamole, I would enter the following:
..and get a list of the found foods (I have already highlighted.my choice of the dip).
A small note about these “RESULTS BY KEYWORD”. All the foods presented have either avocado or guacamole in their descriptions. The letters “M” and “U” between the code and the descriptions indicate the source of the foods. “M” for Master food file, “U” for User food file. An “I” here would have indicated the Institute food file.
I simply press Esc. or Enter to bring that food code to the bottom of the page, Esc. again or Enter will bring up that food profile.
Food code…
…and profile
The resulting profile (below) contains all of the nutrients for that food, as well as the recommended daily intakes. This food has only one screen of nutrients but other foods will have multiple screens (pages) of nutrients. You can scroll down to see all the nutrients by pressing the “Page Down” key. If you press “Ctrl Page Down” you can scroll through a screen at a time.
Pressing “F6” in the Food Unit field shows the units that are available, we choose tablespoons in this case (see below).
… and choose 2 as the Amount. By pressing Enter twice we activate the “R” in the RECALC field and the profile recalculates to show the profile for that unit and amount (see below).
We only show part of the profile to demonstrate the choice of 2 tablespoons. Take note of the Weight and Ml reflecting a 2 tablespoon quantity.
Pressing Esc. repeatedly brings you back to where you were. A small aside, you can also press “F6” when prompted for Keywords. This will bring up your search history and you can choose one of those for your search.
If you have reached this point successfully you now know that you have installed Candat and have accessed one of its foods and manipulated the data and seen the results. You have also had some good experience with the “F5”, “F6”, Esc., and Enter keys. Now on to the real work. The next pages will introduce you to the modules and tasks of Candat, specifically, the task where you enter food recall information and get results.
Subject intake data
A typical Candat scenario
The navigation shown below is a good example of the navigation available throughout CANDAT. You will get used to using the function keys, particularly the keys “F6”, “F5”, “F1” and “Esc”.
Modules and tasks
The first to appear once Candat is started is the TASK MODULES screen. It contains a list of the modules available in CANDAT. Within each module is a list of tasks, each prefixed with a task number. For example, in module 3. Subject files… you will get a series of 300 level tasks. These tasks are related to subject entry, validation, reporting, etc… but all tasks that have to do with subjects.
You will see 300 related tasks in module 5. Questionnaire definition and input. That is because some of those tasks work with questionnaire data once it has been converted to subject files. Just an added convenience if you happen to be working with questionnaire data.
For now, choose the Subject module so that we can enter a simple recall to see how CANDAT works.
Subject files maintenance and reports
Subject file maintenance
This is where subject data is entered, on a per day, per meal basis. You can also configure general information about this subject file here.
Once you have started the task you may choose a user food file to activate. As you enter food codes this will allow CANDAT to automatically validate foods that may not be in the Master food file or Institute food file.
The next step allows you to select an existing subject file or create a new one.
We have chosen to create a new subject file which we have called “demo”, for the purposes of this tutorial. Please note that subject files can hold an unlimited number of subjects.
When first created we need to know whether this subject file will be used for questionnaires. Questionnaire subject files have a few more components to them. These can also be added later if you wish.
Up to 25 subject variables can be created per subject. This is where you define what those variables are. The variable names will serve to identify the data on reports.
This menu shows you what can be done with subject files. A bit overwhelming at first but necessary as your study evolves and you need to manage more and more of your data. For now we will just concentrate on entering subject recall data.
Candat allows up to 10 characters for a subject code. We have tried to make this a bit meaningful, as you can probably see from the characters. This can also be another place for you to classify the subjects. You must, however, make sure that the code you create is unique.
This is where you would populate the variable data that you defined before. Note that the definitions are specific to the subject file though the variable data changes from subject to subject (of course).
…and now we are able to enter actual food recall information, up to 7 days per subject. Specify the date using yyyymmdd coding. The date is important as Candat uses it to figure out the day of the week in “week-weighted” reports.
This is the main data entry screen for food data. You can also change the date here. A convenient way to navigate this screen is through the tab key and the arrow cursor controls. The “F6” key is especially convenient:
in the Meal Code field it will give you a selection of valid meal codes (note that you can define your own meal codes, up to 999 or them!)
in the Food Code field it will allow you to search foods. It will insert the code of the food you choose
in the Unit Code field it will give you a list of valid units for that food and insert the code of the one you choose
All you have left to enter is the Quantity. The Food Frequency field is not used in recalls, it is meant for questionnaire data.
The next few screen pictures will show you data at various stages as well as detail information of your input you can see by pressing the “F1” key.
This screen shows a few foods entered for a breakfast. The highlighted area shows the foods that were entered. It was generated by pressing the “F1” key on the date field. It could also have been generated by pressing the “F1” key on the Unit Code field. Pressing the “F1” key on the other fields will translate the code for the information it generates. For example, if pressed on the “1” under Meal Code, it would show “Breakfast”, if pressed on the food code “28730” it would show “Coffee Brewed”.
How do you know which codes to enter? You just use the “F6” key. The “F6” key pressed in the Meal Code field would give you a list of valid meals (the list you defined if you did that). By selecting the meal you wish the code is automatically inserted. Under the Food Code field “F6” generates the same search it did in the Food Profile area above. The selected food has its code inserted. “F6” in the Unit Code field lists all the units valid for that code. Again, selecting the desired unit inserts its code in the right place and generates the description.
Experiment a bit, add a few more code, fill in the day. When you are done simply press Esc to be prompted for another day of entry.
You can continue entering intake dates until you have the maximum of 7 per subject or you can stop at this point by entering a “0” for the date.
A “0” date will bring up the subject editing menu where you can perform other actions on this subject.
When you are done simply press the Esc key repeatedly until you reach the menu to choose another task:
At this point the prompts become intuitive. In a big study we would do a lot of data entry, perhaps even by multiple data entry clerks. Their subject files could be combined, all the data validated using tasks 310 and 330, the nutrient data compiled and reports produced using task 340.
The validation from task 310 is shown here… if we had made entry errors they would appear in the last column. This validation is also a good way of checking against your entry data to make sure the right foods were coded and none were missed.
and then we simply skip to task 340 to show you some of the possible ways of reporting.
Toggle the Options to Yes for those you would like to see in reports. There are many ways of setting your options.
“Ctrl Y” selects them all to “Yes”,
“Ctrl N” selects them all to “No”,
“Y” make a “Yes”
“N” makes “No”
Just pressing “Enter” changes an entry back and forth.
For this example we will choose them all, “Ctrl Y”
…and press Esc to go to the next screen.
This allows us to select the nutrient we wish to see in the report.
We can add as many nutrients as we wish, pressing “F6” (standard now) on a code field allows us to choose nutrients we want to add. This process is shown below.
Here we have added LUTEIN, nutrient 837, you should see it in your reports, along with the others.
You can also choose to view other data in your reports, you can see the expressions and ratios we have chosen here…
The next few prompts allow you to select the subjects you wish to analyze and other reporting options such as printing, files to save, etc… they are explained below;
As you use Candat the above 4 screen shots will be very familiar to you. They are the standard selection sequence of database records, whether they be subjects (as they are here) or foods, recipes or questionnaires, the main databases used in Candat.
You can choose to sort by one of your selected nutrients, in this case we will leave the first nutrient, protein, as our sorting nutrient. Note that if you sort by nutrient and you view your reports at the food detail level, the foods will not be in the order entered but in the order of the selected nutrient value.
A nutrient report title which will appear on your printed reports…
In Candat you can define your own food groups. Food groups you define are stored in “category” files, each category file containing a list of food groups defined for that category and each food group containing a list of foods. Pressing “F6” here gives you a choice of available category files. Candat comes with the Canadian and USA category files pre-defined.
In this case we will bypass the category file selection by pressing Enter. This will have the effect of cancelling the reporting by food groups we previously selected.
The next few screens ask us for the name of the files to store the results. You can use the same name for each, very convenient as the same name can represent a particular part of your study or some particular purpose for the report, as here, “demo”
At this point Candat produces all the reports, ends the task and provides you with this friendly reminder.
You can then proceed to Start the task again (if you want to produce reports with other options) or choose another task.
View Reports
Of course, once you reach this stage you will probably press the “F5” key to look at your results. We go through this with you in the screens beginning on the next page.
Pressing Enter here lists all the text files (.TXT) and, in this case, gives the only file there.
The menu below is presented when you press the slash (“/”). You can then choose one of the presented options to manage the selected file.
This is the printed results file that was generated by Candat. For the columns to line up properly in external programs the font must be a fixed font, for example Courier New.
This file can be opened with a word processor or a text editor and printed from there if needed. Most of the time these files are not printed. We recently examined a file of 82 subjects and it had over 3,600 pages. That file included each food and showed detail by subject, by day and by meal with a meals summary at the end of each day and a days summary at the end of each subject.
In specifying default printers for CANDAT you can use a printer driver that creates .pdf files directly. This is very convenient as CANDAT allows you to specify very large page sizes which can be viewed in landscape (sideways) mode. If you do not have a .pdf printer driver you can still create this very large .txt file and then convert it using freely available .txt to .pdf converters. One that we have found very useful can be found at
You can then use your favorite pdf reader application to easily browse through all the data.
You scan the .txt or the .pdf files to verify that the data you needed has indeed been generated. Once you are ready to use the data you can access it directly through the files in the SAVE folder. Those files can be imported directly either into a spreadsheet program or in a statistical program. Please see the next pages for examples of those files.
Once you have viewed the text files, you can proceed to the “save” files, the files that you can use to import your data into other programs.
Pressing Enter here give you a list of the save files generated by Candat.
Notice that the name of these files are the names we specified when we ran the reports. Some of these files document the layout of the data so that it can be provided to external programs that require that layout.
Most programs today will accept delimited files. Candat uses the “tab” character as a delimiter. The first row of these “tab-delimited” files contains a variable name which corresponds to the data in the following rows. You can change these variable names in three ways, if desired:
within Candat by changing the short description of the nutrient names;
by using an editor and changing the first row of the data file;
within the program you are using to view the data, using the features of that program (in spreadsheets you would change the first row, in statistical packages you would change the variable names).
The following pages are screen captures from these files and show what the information looks like. Remember, these files are formatted for computers to read, they may look a bit strange to you.
Some of the following files are wider than a screen. In Candat you view them by using the Ctrl-{arrow-right} key. In this case we have just done a screen capture of each screen that came up as we scrolled to the right. Remember, these files are meant to be used by computer programs.
1 of 5
2 of 5
3 of 5
4 of 5
5 of 5
1 of 4
2 of 4
3 of 4
4 of 4
This file has 25 fields, the first 10 only are shown here. No data was input after the weight field.
1 of 3
2 of 3
3 of 3
1 of 4
2 of 4
3 of 4
4 of 4
The DEMO.TXW and DEMO.WTD files look like the above DEMO.TXS files and are not reproduced here for simplicity. They would be different if there were multiple days in the week and some of the days in the week included weekend days as well.
I am sure that when you enter your own data and start looking at these reports you will get a good feeling for how thorough and accurate they really are.
A small aside but important note: You will notice that some of the values in the reports are negative. These are missing values generated by foods that did not have values for particular nutrients. In totals they are counted as zero. Statistical software usually treats missing values differently than regular values and take them into consideration in some calculations.
This concludes the “getting started” tutorial. By now you should have acquired the keyboarding skills required to get your information into and out of Candat and be sufficiently confident to explore the other areas of Candat.
Remember we are here to answer each and every one of your questions. Candat is the calculation engine that generates your data. You can now use whatever software you wish to complete your analyses and present or publish your data.
If you have any difficulties with the software please contact us and let us know. It is the only way we can help.
