Age 2- to 5-Year Sugar-Sweetened Beverage Intakes Predict Age 5- to 17-Year BMI Cluster Assignment, but Not %BF or FMI Cluster Assignment, Following Energy Adjustment. (29th May 2020)

• Record Type: Journal Article
• Authors: Marshall, Teresa; Curis, Alexandra; Cavanaugh, Joseph; Warren, John; Levy, Steven
• Is Part Of: Current developments in nutrition. Volume 4(2020)Supplement 2
• Page Start: 1658
• Page End: 1658
• Publication Date: 2020-05-29
• Subjects: Nutrition -- Periodicals; Nutritional Physiological Phenomena; Nutrition; Periodicals; Periodicals; Fulltext; Internet Resources; Periodicals; 612.3
• DOI: 10.1093/cdn/nzaa063_056
• Languages: English
• ISSNs: 2475-2991

Abstract

Abstract: Objectives: Sugar-sweetened beverage (SSB) intakes have been associated with obesity, generally assessed using body mass index (BMI). BMI is a surrogate measure of obesity, with % body fat (%BF) and fat mass index (FMI) considered more direct measures of BF. Our objectives were to predict age 5- to 17-year low, middle, and high BMI, %BF, and FMI cluster assignments from age 2- to 5-year beverage and energy intakes. Methods: Iowa Fluoride Study/Iowa Bone Development Study participants were recruited at birth and followed longitudinally. Participants (n = 299) with at least two beverage questionnaires and 3-day diet records completed between 2–5 years and at least four of six dual-energy X-ray absorptiometry (DXA) scans at 5, 9, 11, 13, 15, and 17 years were included in analyses. Beverage intakes (i.e., SSB, juice, water, milk) were calculated from beverage questionnaires and energy intakes from diet records. %BF and FMI were obtained from DXA scans. Ward's method for hierarchical clustering was used to identify low, medium, and high BMI, %BF and FMI clusters. Multinomial cumulative logit models were used to predict the dependent variables (BMI, %BF and FMI cluster assignments) from the independent variables (beverage and energy intakes) with adjustment for sex and/or socioeconomic status (SES). Results: In multivariable models, SSB intake adjusted for other beverage intakes and sex was significantly associated with BMI, %BF, and FMI cluster, while energy intake adjusted for sex was also significantly associated with BMI, %BF, and FMI cluster. In a full model including all beverage and energy intakes, which was adjusted for sex and SES, both SSB and energy intakes were significantly associated with BMI, but not %BF or FMI. In the full model, for each 8 oz/day increase in SSB at 2–5 years, the odds of being in a higher BMI cluster as opposed to a lower cluster at 5–17 years increased by 73% (95% CI: 7%, 179%). In the full model, each 100 kcal/day increase in energy increased the odds of being in a higher BMI cluster by 11% (95% CI: 1%, 21%). Conclusions: In separate models, both SSB and energy intakes predicted BMI, %BF and FMI cluster. When included in the same model, both SSB and energy intakes predicted BMI, yet neither predicted %BF or FMI, likely due to collinearity resulting from the association between SSB and energy intakes. Funding Sources: NIH; RJ Carver Trust; Iowa Delta Dental.