Supporting Large-scale Nutrition Analysis Based on Dietary Survey Data

While online survey systems facilitate the collection on copious records on diet, exercise and other healthrelated data, scientists and other public health experts typically must download data from those systems into external tools for conducting statistical analyses. A more convenient approach would enable researchers to perform analyses online, without the need to coordinate additional analysis tools. This paper presents a system illustrating such an approach, using as a testbed the WAVE project, which is a 5year childhood obesity prevention initiative being conducted at Oregon State University by health scientists utilizing a web application called WavePipe. This web application has enabled health scientists to create studies, enrol subjects, collect physical activity data, and collect nutritional data through online surveys. This paper presents a new sub-system that enables health scientists to analyse and visualize nutritional profiles based on large quantities of 24-hour dietary recall records for sub-groups of study subjects over any desired period of time. In addition, the sub-system enables scientists to enter new food information from food composition databases to build a comprehensive food profile. Interview feedback from novice health science researchers using the new functionality indicated that it provided a usable interface and generated high receptiveness to using the system in practice.