Abstract

Accurately estimating portion sizes remains a challenge in dietary assessment. Digital images used in online 24-hour dietary recalls may be conducive to accuracy. The current analyses were conducted to examine the accuracy of portion size estimation by women with low incomes who completed 24-hour dietary recalls using the online Automated Self-Administered 24-hour Dietary Assessment Tool (ASA24) in the Food and Eating Assessment Study II. True dietary intake was observed for 3 meals on 1 day through a controlled feeding study conducted from May through July 2016. The following day, participants completed an unannounced 24-hour dietary recall using ASA24, independently or with assistance in a small-group setting. Participants included 302 women aged 18 to 82 years living in the Washington, DC, area who met the income thresholds for the Supplemental Nutrition Assistance Program. The accuracy of portion size estimation was assessed by comparing the weight truly consumed (observed) and the weight reported for predetermined categories of foods and beverages. The differences between observed and reported portions were examined and linear regression tested differences by recall condition. Analyses were conducted by condition and repeated with stratification by racial/ethnic identity, education, and body mass index. On average across foods and beverages, reported portion sizes were 7.4 g (95% CI, 4.3-10.5) and 6.4 g (95% CI, 2.8-10.0) higher than observed portion sizes in the independent and assisted conditions, respectively. Portion sizes were overestimated for small pieces and shaped foods in both conditions, as well as for amorphous/soft foods in the assisted condition and underestimated for single-unit foods in both conditions. Misestimation was fairly consistent by participants' race/ethnicity, education, and body mass index, to varying magnitudes. Women with low incomes overestimated the amounts of foods and beverages consumed across several categories using online 24-hour dietary recalls with digital images to support portion size estimation. Assistance with ASA24 had little impact on accuracy.

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