Table 2.

Advantages and challenges of current dietary assessment methods used in nutrition surveys and the potential use of new technologies as presented at the 9th International Conference on Diet and Activity Methods (ICDAM9) Panel 2015

Survey, country	Dietary assessment method	Advantages of the current method	Challenges of the current method	Potential benefits of new technologies
Australian Health Survey 2011–13 (AHS), Australia	Two 24 h recalls including interviewer-assisted data collection via computerised Automated Multiple-Pass Method (AMPM)	Provides detailed intake data (additional information collected including supplement use and dietary behaviours); ease of application among those with low literacy and older adults	Expensive and time consuming; possible recall bias; trained interviewer required; respondent burden	Online FFQ – the Australian Eating Survey (AES): Lower respondent burden (as takes 15 min to complete); relatively inexpensive; does not require trained interviewers; fewer data processing requirements: provides personalised dietary feedback in real time; possibility to monitor response rates
Danish National Survey of Diet and Physical Activity (DANSDA), Denmark 4–75 years old: 2003–2008, 2011–2013, and 6–36 months old: 2006–2007	Paper 7-d estimated pre-coded diary with open-answer possibilities and pre-coded answer options for the most commonly eaten foods and dishes in the Danish diet	Ease of application among those with low technology usage and older adults; ease of coding process due to precoding	Expensive and time consuming; trained interviewer required; respondent burden; slow data processing and reporting timeline; generic-level food intake information	Web-based 7-d food record (6–36 months old, 2014–2015): Lower respondent burden; richer foods and portion size options; partly automated food coding; advanced food identification and search features; automated prompts through web; personal text messages
The Dutch National Food Consumption Survey (DNFCS), the Netherlands	Two 24 h recalls using computerised GloboDiet with trained interviewers	Provides detailed intake data (provides additional information including supplement use)	Expensive and time consuming; possible recall bias; trained interviewer required; respondent burden; slow data processing and reporting timeline; difficulty to keep up-to-date food composition database; low respondent motivation (method perceived as ‘old-fashioned’)	Barcoding technology (in combination with GloboDiet): Advanced linkage of food consumption and food composition data using artificial intelligence techniques Use of mobile applications instead of GloboDiet to achieve more advanced level of food identification
National Diet and Nutrition Survey Rolling Programme (NDNS RP), UK	Paper 4-d estimated food diary	Provides detailed intake data (provides additional information on supplement use); ease of application among those with low technology usage and older adults; provides contextual eating information	Expensive and time consuming; trained interviewer required; large respondent burden (high motivation required); slow data processing and reporting timeline	Web-based 24 h recall: Cost-effective and time saving; less respondent burden; possible increase in response rates of those with high motivation for automated methods (e.g. teenagers); ease of data processing and reporting