Dietary patterns and associations with BMI in low-income, ethnic minority youth in the USA according to baseline data from four randomised controlled trials

Madison N LeCroy, Holly L Nicastro, Kimberly P Truesdale, Donna M Matheson, Carolyn E Ievers-Landis, Charlotte A Pratt, Sarah Jones, Nancy E Sherwood, Laura E Burgess, Thomas N Robinson, Song Yang, June Stevens, Madison N LeCroy, Holly L Nicastro, Kimberly P Truesdale, Donna M Matheson, Carolyn E Ievers-Landis, Charlotte A Pratt, Sarah Jones, Nancy E Sherwood, Laura E Burgess, Thomas N Robinson, Song Yang, June Stevens

Abstract

Few studies have derived data-driven dietary patterns in youth in the USA. This study examined data-driven dietary patterns and their associations with BMI measures in predominantly low-income, racial/ethnic minority US youth. Data were from baseline assessments of the four Childhood Obesity Prevention and Treatment Research (COPTR) Consortium trials: NET-Works (534 2-4-year-olds), GROW (610 3-5-year-olds), GOALS (241 7-11-year-olds) and IMPACT (360 10-13-year-olds). Weight and height were measured. Children/adult proxies completed three 24-h dietary recalls. Dietary patterns were derived for each site from twenty-four food/beverage groups using k-means cluster analysis. Multivariable linear regression models examined associations of dietary patterns with BMI and percentage of the 95th BMI percentile. Healthy (produce and whole grains) and Unhealthy (fried food, savoury snacks and desserts) patterns were found in NET-Works and GROW. GROW additionally had a dairy- and sugar-sweetened beverage-based pattern. GOALS had a similar Healthy pattern and a pattern resembling a traditional Mexican diet. Associations between dietary patterns and BMI were only observed in IMPACT. In IMPACT, youth in the Sandwich (cold cuts, refined grains, cheese and miscellaneous) compared with Mixed (whole grains and desserts) cluster had significantly higher BMI (β = 0·99 (95 % CI 0·01, 1·97)) and percentage of the 95th BMI percentile (β = 4·17 (95 % CI 0·11, 8·24)). Healthy and Unhealthy patterns were the most common dietary patterns in COPTR youth, but diets may differ according to age, race/ethnicity or geographic location. Public health messages focused on healthy dietary substitutions may help youth mimic a dietary pattern associated with lower BMI.

Keywords: BMI; Cluster analysis; Dietary patterns; Ethnic minorities; Youth.

Conflict of interest statement

Conflict of interest: None.

Figures

Figure 1.
Figure 1.
Mean z-score of each food/beverage group servings per 1000 calories for the selected k-means cluster solution for NET-Works (N=534). AUSB, artificially and unsweetened beverages; SSB, sugar-sweetened beverages
Figure 2.
Figure 2.
Mean z-score of each food/beverage group servings per 1000 calories for the selected k-means cluster solution for GROW (n=609). AUSB, artificially and unsweetened beverages; SSB, sugar-sweetened beverages
Figure 3.
Figure 3.
Mean z-score of each food/beverage group servings per 1000 calories for the selected k-means cluster solution for GOALS (N=241). AUSB, artificially and unsweetened beverages; SSB, sugar-sweetened beverages
Figure 4.
Figure 4.
Mean z-score of each food/beverage group servings per 1000 calories for the selected k-means cluster solution for IMPACT (N=360). AUSB, artificially and unsweetened beverages; SSB, sugar-sweetened beverages

Source: PubMed

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