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What variables are there when choosing what method to use to estimate dietary intake? (4)
- -whether you want information about dietary
- behaviours or amounts of foods, nutrients, and nonnutrient
- food constituents consumed
- - whether you want to assess absolute or relative
- amounts of foods and/or nutrients
- - whether you want historical or current patterns
- - time, resources, money etc that you hav4e
What are the methods of estimating usual dietary intake? (4)
- Food Frequency Questionaire
- 24Hour Recall
- Food Record
- Direct Observation
What are considered short term instruments? When are the most used?
- - 24hr recall, food records, food diaries
- - Oftern used in population surverys for monitoring health and nutrition
What are considered long term instruments? When are the most used?
- - FFQ
- -Often used in large cohort or case control studies to examine die health relationships
What are some variable approached to using fooddiaries/ records? (4)
- - Trained or untrained respondents
- - Detailed review or not
- - Highly standardized coding rules or not
- - Development of electronic methods: PDA, cell
What the strengths of food diaries/ records?(4)
- - Intake is quantified, detailed
- - Can include weekends
- - Could be relatively accurate (detail/training)
- - Data are rich in details (Nutrient, Cooking practices, Meal and eating frequency)
What the limitations of food diaries/ records?(7)
- -Recording influences diet (reactive tool)- Biased measurement
- - Requires literacy
- - High respondent and investigator burden
- - Multiple days required to estimate usual intake
- - Sample selection bias
- - Completion worse over time
- - Underreporting is typical- Worse with overweight/obese
What is a 24 Hour Recall?
- -Ascertain descriptions and amounts of foods consumed
- in 24 hour period prior to interview
- - Can be interviewer administered or self-administered by computer (US National Cancer Institute is developing a
- web-based tool;
What are some variable approached to using 24 hour recalls? (8)
- -Training of interviewers
- - Standardization of probing questions
- - Multiple passes through the day
- - Computer vs. paper/pencil administration
- - In-person vs. telephone
- - Portion size models or measurement aids
- - Quality and completeness of nutrient database
- -Development of self-administered automated
- -5 systems administered via computer or internet
What the strengths of 24 hour recalls?(6)
- -low respondent burden and high compliance- less
- chance of selection bias due to burden
- - can be suitable for illiterate subjects
- - standardised protocol can be used
- - unlikely to interfere with dietary behaviour
- - can get through relatively large numbers of subjects in
- one day
- ! can get details on cooking practises, brands, meal
- frequency etc.
What the limitationss of 24 hour recalls?(6)
- -Imperfect knowledge and memory- relies on this
- - Relies heavily on getting a portion size estimation
- - Multiple days required to estimate usual intake- single day is a snap-shot
- - Costly to administer if face-to face- Highly trained interviewers
- - Some evidence that reporting declines with multiple administrations
- - Underreporting is typical- Worse with overweight/obese
Disadvantages of 24 hour recalls (3)
- - relies heavily on memory
- - portion size estimation issues
- - a single 24 hour recall only gives a snapshot of that
- persons intake
- (simply having a bad day cannot be used to make judgements that person likely nutrition status
What are some variable approached to using FFQ? (8)
- - Number of foods, clarity of questions
- - Portion size questions: pictures vs. text description
- - Time frame
- - Development of food list, nutrient database
- - Type of administration: computer vs. paper
- - Specificity to population of interest
- - Supplement intake
- - Food preparation
FFQ Strengths (4)
- -Can assess intakes of very large numbers of people
- (can be distributed/collected by mail and self
- -Atempts to estimate 'usual' individual intake of foods with one administration
- - Does not affect eating behavior-
- -Lower cost of administering/processing-optic-readable scanned forms and Computer-generated data
FFQ: limitations (8)
- - Lack details ( finite food list, details of cookin methods, specific food type lost
- -Cognitively complex
- - Requires literacy
- - Affected by recent diet
- - Severe measurement error: prone to bias
- - Different FFQs can behave quite differently-FFQ designed to
- assess calcium intake is NOT appropriate if you want to
- measure intakes of fruit and vegetables
- - Different populations respond differently
- -Problems with assessing foods
How to assess a FFQ? (4)
- 1. What was the original purpose of the
- 2. Who was the target population? Are
- questionnaires developed in Europe suitable for
- use in Canada?
- 3. When was the questionnaire developed? Are the
- foods and portion sizes still relevant?
- 4. Has a previous validation been carried out, was it acceptable
How to analyze food records/recalls?
What questions/ limts are there with this method of analysis?
- Databases ( USDA, CANDI)
- Foods away from home?
- Foods prepared at home?
- Fortified/enriched foods?
- How good is it at accurately determining nutrients?
- Updating of the systerm with changes to food supply?
- New food compound of health interest?
- Supplement use?
When reading literature what consideration should you make when analyzing food estimation? (3)
- - What database was used?
- - Are valid estimates possible - intake data collected to obtain a reliable and valid estimate of food in the population of interest., completion of the database
- -Is the correction level of precision reported
How are dietary patterns measured?
- - Used to assess dietary intake (food records, FFQ)
- for case-control, survey & cohort studies
- - Cluster, Factor or Index analysis
- - Cluster & Factor determine patterns from collected
- food intake
- - Indexes are pre-determined based on definition of
- healthy eating
- - Healthy Eating Index, Dietary Quality Index,
- Alternate Healthy Eating Index
- -limitations in using these?
What are the limitations of biomarkers used in nutrition studies?
- -Very few short term available, few long term
- EXAMPLES: see readings
- - Concentration: reflect the biological response to intake - Cannot be used to assess amount consumed, Correlate to amount consumed, May reflect short or long term intakes, Some are appropriate for risk assessment
- -Most nutrients tightly controlled: no relationship to intake
What are some innovations in estimating intake (5)
- -Web-based, automated FFQs
- - Self-administered, automated, web-based,
- 24-hour dietary recalls
- - Real time data collection of food records
- - Voice recognition software
- - Combining methods: FFQ with 24-hour recalls
What is External Validity?
How is it increased? (2)
- study design)- extent to which results from a study can be extended to universe that is broader than population
- Increased by:
- a) subject selection - random selection, differences in confounding recruitment methods (including incentives)
- b) subject number - sufficient statistical poer to detect differences between groups
- -- Still need quality control of measures and judgment
- about degree to which results can be extrapolated
What is internal Validity?
- adequacy of measurement - how well does it measure what it is intended to measure (index or indicator reflects what it is intended to
Components of internal validity (4) and how they are affected
- 1) Reliability (reproducibility)- Degree to which repeated measures give same value
- -Affected by:
- a) True variation in the measurement
- b) Random error (or random variation)
- c) Systematic errors
- 2) Face Validity - judgment (often by experts) that tool measures what it is supposed to
- 3) Content Validity - are all components of the
- construct (e.g. diet) measured by the tool?
- 4) Criterion validity - how well the tool performs
- compared with another tool (gold standard?) known
- to measure the same thing?
How to ensure internal validity? (4)
- 1) Reliability
- - Standardize protocols; calibrate instruments
- - Use protocols suitable for situation
- - Include test-retest as part of study design
- 2) Get expert opinion before implementing tool
- 3) Conceptualize content of construct and choose tools accordingly (e.g. based on literature)
- 4) Compare between and among tools
When does changing a tool change the validity of your measures? How might you minimize the likelihood that changed to you method have been invalidates** EXAM
- How to make you tools still useful
What is a confounding variable?
How can you control this? (2)
A special type of bias (therefore affects validity)1 A characteristic or variable that is distributed differently in the study and control groups, and affects the outcome being assessed. Eg. (Randomization, stratification)
- Ways to control
- 1) study design - randomization, stratificaton, recruitment restirction, matching
- 2) Post Data Collection - stratification (in analysis) - multivariate analysis
Validity measures diary /food record (2)
- -complete and accurate record of all food consumed, where the choice of food consumed has not been influenced by the act of recording
- Valid FFQ
- - accurate reflection of typical food intake over
- a designated period of time - undistorted by false memory or desire to appear "norma"
What is a measuresment error?
Difference between the true value and the value obtained from a measurem
What is a systematic error (bias)?
What is negative bias and positive bias?
-Source of error in which measurements consistently depart from the true values ( if a instrument has a systematic error then the average of many repeat measures does not approximate the true value)
- Bias is either negative or positive
- 1)Negative bias - means that dietary intakes are
- systematically under-estimated
- 2) Positive bias - means that dietary intakes are
- systematically over-estimated
- Eg. Doubly labelled water studies suggest that obese
- people are likely to systematically under-report
- energy intake
What is Random Error (5)?
- -Unpredictable error
- affects reproducibility (or precision) of a method
- - caused by true variation in intake + measurement error
- - reduces the strength of associations observed between diet and markers for disease
- - reduces the statistical power of studies
What is precision?
How valid it is in nutrition studies
- The ability of a measurement to be reproduced - i.e.
- produces the same answer on repeat administrations
- -Almost impossible to achieve at the individual level food intake varies widely over time
- i.e. if you did 24 hour recalls on 1 person on 4
- different occasions, you would be unlikely to get
- exactly the same energy and nutrient intakes on each
What are the major sources of measurements of error (9)
- 1) Respondent error: either random or systematic
- OR inability/unwillingness to comply with protocols
- 2) Interviewer bias:
- - Monday interview vs friday, interviewers with desires to promote healthy eating may obtain biased results, interviewed may not click with certain individuals but have very good rapport with others
- 3) Respondent memory lapses
- -use memory aids (e.g. food models, photographs)
- - not such a big problem if the time period between food intake and recall of the intake is short
- - foods contributing to the main part of the meal are remembered better than minor or odd foods
- 4) Incorrect estimation of portion size
- - probably a large source of measurement error
- -using average portion weight instead of a estimate can result in substantial error
- 5) Honest vs desirable responses
- 6) Foods served vs foods consumed
- 7) Subject characteristics (obesity, age,
- motivation, etc)
What influences random (1) and systematic errors (3)
- Random error- within person error
- Systematic error- Person-specific bias
- - Constant additive error
- - Intake-related bias
How can you get coding and computation errors (4)
- Can arise from poor descriptions of foods
- - Inaccurate conversion from estimates or household measures to actual weights
- - May not have appropriate tables for food composition data
- - Systematic mistakes when entering data - e.g. entering data - eg. orange juice as concentrated OJ can result in vitamin C estimates 5x greater than they should be