One hundred and five individuals (45 males; 60 females) completed all study visits. Participants were primarily Caucasian (85% of sample), with remaining participants self-identified as Asian (8%), African American (4%), or “other” (4%). Mean age of participants was 39±2 yrs (range: 21–93 yrs), which was distributed across the adult age range as follows: 21–39 yrs, 60%; 40–59 yrs, 23%; ≥ 60 yrs, 17%. Body mass index was widely distributed (mean=25.6±0.6 kg/m2; range 16.2–62.5 kg/m2), although participants were primarily of “normal” BMI status (BMI <18.5 kg/m2, 2%; 18.5–24.9 kg/m2, 53%; 25.0–29.9 kg/m2, 30%; >30.0 kg/m2, 15%). Of 72 participants who provided information on their educational level, most reported being college-educated (n=67).
Results from the validity and test-retest reliability assessment of the BEVQ are presented in . Of the 21 beverage variables assessed (grams and energy for 19 individual beverage categories, plus SSB and total beverages), responses on the two assessment tools (BEVQ1, FIR) were significantly correlated (all P<0.001) with two exceptions: sweetened coffee and mixed alcoholic drinks. Responses between the BEVQ1 and FIR were not different for intake (g) of water, juice drinks, vegetable juice, milk (all types), soft drinks (regular and diet), light beer, liquor, mixed alcoholic drinks, wine, and total beverage intake. Differences in beverage energy content between assessment tools were < 35 kcal across all categories, although this difference was significant for 100% fruit juice, sweet tea, sweetened coffee, beer, meal replacement and energy drinks. Significant mean differences were detected in total beverage and sweetened beverage energy intake determined using the two tools, although this difference was minimal (63 and 44 kcal, respectively). These two variables were, however, each significantly correlated between the tools. Reliability was acceptable (r=0.45−0.87; all p<0.001), as food frequency questionnaires considered reliable typically report correlations ranging 0.5–0.7 (17
). Significant correlations were detected between all variables, although the correlation for energy drinks was lower than that for other beverage categories. No significant differences were found between BEVQ responses based on the two study sessions (BEVQ1, BEVQ2), or between the two visit sequences (data not shown). Urinary SG measurements were not significantly different across visits (1.0146±0.0008 vs. 1.0146±0.0008 UG; mean difference: −0.000019±0.007 UG). As would be expected for a possible biomarker of total fluid intake, SG was negatively correlated with grams of total daily beverage consumption (BEVQ) at time one and time two (r=−0.202 and r=−0.238; p<0.05, respectively). SG was also negatively correlated with BEVQ water intake (g) at time one (r=−0.236, p<0.05) and time two (r=−0.319, p<0.01). Thus, the BEVQ appears to be a valid, reliable, and easily-administered questionnaire for assessing beverage intake in adults.
Validity and test-retest reliability of a beverage intake questionnaire (BEVQ): Comparison to a four-day food intake record (FIR) and results of two BEVQ administrations.
Beverage consumption is timely topic in the weight management field (12
) and particularly for SSB, there are broad public health implications (13
). This tool may be useful for researchers and clinicians interested in assessing habitual beverage consumption patterns, particularly in large-scale investigations where lengthier, resource-intensive dietary intake assessment techniques are not feasible. Among dietetic practitioners, this tool could be utilized as rapid method to assess beverage consumption as part of a Nutrition Assessment in the Nutrition Care Process, and potentially in Nutrition Monitoring and Evaluation.
The present findings are consistent with others using more extensive dietary intake assessment methods, reporting a mean beverage energy intake of 458 kcal per day (27
). Water is the most consumed beverage in the US, followed by coffee, soft drinks, whole milk, fruit juices, and alcohol (27
). The present findings are consistent with this pattern, with the exception of whole milk. In the general population, the majority of beverage energy (~50%) comes from SSB, such as regular soft drinks, fruit drinks, sweet tea, and energy drinks (27
). In this sample, SSB contribute ~40% of total beverage energy. Furthermore, Block (29
) reported that energy containing soft drinks are the greatest contributor to total daily energy intake (i.e., all food and beverages) at 7.1%, while beer was also among the top contributors (2.6% of total energy). In this sample, soft drinks were the fifth highest contributor of energy from beverages, preceded by fat-free milk (greatest contributor of energy), fruit juice, reduced-fat milk, and sweet tea. These differences may be attributed to the demographics of our sample, as age, weight status, educational level and socioeconomic status may influence beverage consumption (30
After completing this initial evaluation of the BEVQ, several limitations were determined. Questions from participants during completion of the BEVQ suggested some refining may be needed, for example the BEVQ does not include a category for hot cocoa and participants were uncertain how to report sports drink intake. Beverage category descriptions may also need modification, for example, “coffee with cream and/or sugar” may be misinterpreted as coffee with cream. Participants were uncertain as to whether milk in cereal and coffee should be included in their responses. To address this issue, future versions will include additional respondent instructions such as to only report consumption of liquids when consumed as beverages. It is possible that the BEVQ underestimates certain beverage categories due to the upper limits on quantities (60 fl oz per day), for example water intake. However, estimated BEVQ mean daily water intake is similar to that reported by National Health and Nutrition Examination Surveys (NHANES)(31
) and the present findings did not indicate a ceiling effect. A final limitation is the use of a self-reported FIR for validation, as underreporting errors are common (24
). However, FIR are recommended for validation of food-frequency questionnaires due to a reduced likelihood of correlated errors (17
), when direct measurement of food intake is not feasible. Future work will determine if reducing the length of the tool is possible without impacting results, if the tool is sensitive to changes in beverage intake, and if the tool may be used in low-literacy populations. Due to the primarily Caucasian composition of this sample, future studies including larger numbers of minorities are warranted to determine if the BEVQ is a valid tool across ethnic/racial groups.