Development of a Diet Quality Screener for Global Use: Evaluation in a Sample of US Women

Abstract

BackgroundValid and efficient tools for measuring and tracking diet quality globally are lacking. ObjectiveThe objective of the study was to develop and evaluate a new tool for rapid and cost-efficient diet quality assessment. DesignTwo screener versions were designed using Prime Diet Quality Score (PDQS), one in a 24-hour recall (PDQS-24HR) and another in a 30-day (PDQS-30D) food frequency format. Participants completed two 24-hour diet recalls using the Automated Self-Administered 24-hour Dietary Assessment Tool (ASA24) and 2 web-based diet quality questionnaires 7 to 30 days apart in April and May 2019. Both dichotomous/trichotomous and granular scoring versions were tried for each screener. Participants/settingThe study included 290 nonpregnant, nonlactating US women (mean age ± standard deviation 41 ± 11 years) recruited via Amazon Mechanical Turk. Main outcome measuresThe main outcome measures were Spearman rank correlation coefficients and linear regression beta-coefficients between ASA24 nutrient intakes from foods and beverages and PDQS values. Statistical analyses performedThe Spearman rank correlation and linear regression were used to evaluate associations of the PDQS values with ASA24 nutrient intakes from food, both crude and energy-adjusted. Correlations were de-attenuated for within-person variation in 24-hour recalls. Wolfe’s test was used to compare correlations of the 2 screening instruments (PDQS-24HR and PDQS-30D) with the ASA24. Associations between the ASA24 Healthy Eating Index 2015 and the PDQS values were also evaluated. ResultsPositive, statistically significant rank correlations between the PDQS-24HR values and energy-adjusted nutrients from ASA24 for fiber (r = 0.53), magnesium (r = 0.51), potassium (r = 0.48), vitamin E (r = 0.40), folate (r = 0.37), vitamin C (r = 0.36), vitamin A (r = 0.33), vitamin B6 (r = 0.31), zinc (r = 0.25), and iron (r = 0.21); and inverse correlations for saturated fatty acids (r = –0.19), carbohydrates (r = –0.22), and added sugar (r = –0.34) were observed. Correlations of nutrient intakes assessed by ASA24 with the PDQS-30D were not significantly different from those with the PDQS-24HR. Positive, statistically significant correlations between the ASA24 Healthy Eating Index 2015 and the PDQS-24HR (r = 0.61) and the PDQS-30D (r = 0.60) were also found. ConclusionsThe results of an initial evaluation of the PDQS-based diet quality screeners are promising. Correlations and associations between the PDQS values and nutrient intakes were of acceptable strength and in the expected directions, and the PDQS values had moderately strong correlations with the total Healthy Eating Index 2015 score. Future work should include evaluating the screeners in other population groups, including men, and piloting it across low- and middle-income countries.