Weighed food diaries (diet diaries or food records) are prospective dietary assessment methods, providing descriptions of the foods consumed and eating occasions [1]. These methods provide excellent estimates for energy, nutrients, foods and food groups. The outcomes measured by weighed food diaries are described in Table D.8.1. Recommendations are based upon multiple days of food diary entries rather than a single day in order to account for daily variation in diet.
Table D.8.1 Dietary outcomes assessed by weighed food diaries over multiple days.
Dietary outcome | Possible to assess? |
---|---|
Energy and nutrient intake of total diet | Yes |
Intake of specific nutrients or food | Yes |
Infrequently consumed foods | Maybe |
Dietary pattern | Yes |
Habitual diet | Yes* |
Within-individual comparison | Yes* |
Between-individual comparison | Yes |
Meal composition | Yes |
Frequency of eating/meal occasions | Yes |
Eating environment | Yes |
Adult report of diet at younger age | No |
* possible when repeated measures were collected over time.
Measurements of weighed food diaries involve respondents or investigators weighing every item of food and drink consumed at the time of consumption. The following are also recorded as much as possible:
Timeframe
Procedure
Estimates of diet can only be derived following extensive data entry. One person may consume more than 50 items per day, and the number of food items in a population-based study can easily become thousands. Data entry should consider the following issues:
Each dietary entry may include the following attributes:
Outcomes can vary depending on aims, level of detail of information, and the number of days recorded. Outcomes extracted from diaries may be averaged across multiple days of measurement to estimate a ‘typical’ daily consumption.
Example of dietary estimates from weighed food diaries include:
Key characteristics are described in Table D.8.2.
Strengths
Limitations
Table D.8.2 Characteristics of weighed food diaries.
Characteristic | Comment |
---|---|
Number of participants | Up to ~1000 |
Cost of development | Low |
Cost of use | Medium |
Participant burden | Very high |
Researcher burden of data collection | Medium |
Researcher burden of coding and data analysis | High |
Risk of reactivity bias | Yes |
Risk of recall bias | Minimised if diary completed at time of consumption |
Risk of social desirability bias | Yes |
Risk of observer bias | Minimised |
Participant literacy required | Yes |
Suitable for use in free-living | Yes |
Requires individual portion size estimation | No |
Considerations relating to the use of weighed food diaries for assessing diet in specific populations are described in Table D.8.3.
Table D.8.3 Diet assessment by weighed food diaries in different populations.
Population | Comment |
---|---|
Pregnancy | Suitable. |
Infancy and lactation | Requires proxy. |
Toddlers and young children | Requires proxy. Completed by parents of young children aged 7-9 years, weighed dietary records have shown good agreement with estimates of energy expenditure made by doubly labelled water [6]. |
Adolescents | Under-reporting apparent in adolescents [6,7]. |
Adults | Under-reporting reported in adults [8]. |
Older Adults | May require proxy depending on cognitive function. Larger size diaries can be created for children and for the elderly who do not see well. |
Ethnic groups | Requires language/cultural specificity. |
Other |
A method-specific instrument library is being developed for this section. In the meantime, please refer to the overall instrument library page by clicking here to open in a new page.
Weighed food diaries are known as a resource-intensive method. Thus, they may not be adopted readily in an epidemiological study with a large sample size. However, food diaries, whether estimated or weighed, are realistic and conceivable to implement in a subset of a study population, although this still requires expert knowledge on data entry and further processing. Food diary data in a subset should then be combined with the dietary data of an entire study population deriving from another dietary assessment (e.g. multiple 24-h recalls, food frequency questionnaires). Unique statistical approaches are required to accurately merge multiple dietary datasets obtained from different methods [9].