OBJECTIVE: Some beverages are nutrient dense, but they are often excluded from nutrient density calculations. The purpose of this study was to assess whether the energy-nutrient association changed when beverages were included in these calculations. DESIGN: Applying a cross-sectional design, a 24-hour dietary recall was collected on each participant. Subjects/ SETTING: 440 young adults (ages 19-28 years) in Bogalusa, Louisiana participated in this study. STATISTICAL ANALYSIS: Mean nutrient intakes and food group consumption were examined across the energy density (ED) tertiles using two calculation methods: one with food and all beverages (excluding water) (ED1) and one including food and only energy containing beverages (ED2). Regression models were used and multiple comparisons were performed using the Tukey-Kramer procedure. A p-value < 0.05 was considered to be significant. RESULTS: With increasing ED, there was a significant increase in the consumption of total meats (ED1 p < 0.05; ED2 p < 0.01). In contrast, there was a significant decrease in consumption of fruits/juices (ED1 p < 0.01; ED2 p < 0.0001), vegetables (ED1 p < 0.01; ED2 p < 0.05), beverages (both p < 0.0001) and total sweets with increasing ED (both p < 0.0001). There was a significantly higher mean intake of total protein (grams) (ED2 p < 0.0001), amino acids (ED1 histidine/leucine p < 0.05; ED2 p < 0.0001), and total fat (grams) (ED1 p < 0.0001; ED2 p < 0.0001) with higher ED compared to lower ED. The percent energy from protein (ED1 p < 0.05; ED2 p < 0.0001), total fat (both p < 0.001) and saturated fatty acids (both p < 0.0001) significantly increased and the percent energy from carbohydrate (both p < 0.0001) and sucrose (both p < 0.0001) significantly decreased with increasing ED. CONCLUSION: This study suggests that ED may influence the ND of the diet depending on whether energy containing beverages are included or excluded in the analysis.
OBJECTIVE: Some beverages are nutrient dense, but they are often excluded from nutrient density calculations. The purpose of this study was to assess whether the energy-nutrient association changed when beverages were included in these calculations. DESIGN: Applying a cross-sectional design, a 24-hour dietary recall was collected on each participant. Subjects/ SETTING: 440 young adults (ages 19-28 years) in Bogalusa, Louisiana participated in this study. STATISTICAL ANALYSIS: Mean nutrient intakes and food group consumption were examined across the energy density (ED) tertiles using two calculation methods: one with food and all beverages (excluding water) (ED1) and one including food and only energy containing beverages (ED2). Regression models were used and multiple comparisons were performed using the Tukey-Kramer procedure. A p-value < 0.05 was considered to be significant. RESULTS: With increasing ED, there was a significant increase in the consumption of total meats (ED1 p < 0.05; ED2 p < 0.01). In contrast, there was a significant decrease in consumption of fruits/juices (ED1 p < 0.01; ED2 p < 0.0001), vegetables (ED1 p < 0.01; ED2 p < 0.05), beverages (both p < 0.0001) and total sweets with increasing ED (both p < 0.0001). There was a significantly higher mean intake of total protein (grams) (ED2 p < 0.0001), amino acids (ED1histidine/leucine p < 0.05; ED2 p < 0.0001), and total fat (grams) (ED1 p < 0.0001; ED2 p < 0.0001) with higher ED compared to lower ED. The percent energy from protein (ED1 p < 0.05; ED2 p < 0.0001), total fat (both p < 0.001) and saturated fatty acids (both p < 0.0001) significantly increased and the percent energy from carbohydrate (both p < 0.0001) and sucrose (both p < 0.0001) significantly decreased with increasing ED. CONCLUSION: This study suggests that ED may influence the ND of the diet depending on whether energy containing beverages are included or excluded in the analysis.
Authors: E Obarzanek; S A Hunsberger; L Van Horn; V V Hartmuller; B A Barton; V J Stevens; P O Kwiterovich; F A Franklin; S Y Kimm; N L Lasser; D G Simons-Morton; R M Lauer Journal: Pediatrics Date: 1997-07 Impact factor: 7.124
Authors: T A Nicklas; J Dwyer; P Mitchell; M Zive; D Montgomery; L Lytle; J Cutler; M Evans; A Cunningham; K Bachman; M Nichaman; P Snyder Journal: Prev Med Date: 1996 Jul-Aug Impact factor: 4.018
Authors: Jenny H Ledikwe; Heidi M Blanck; Laura Kettel Khan; Mary K Serdula; Jennifer D Seymour; Beth C Tohill; Barbara J Rolls Journal: J Nutr Date: 2005-02 Impact factor: 4.798
Authors: Sungshim Lani Park; Iona Cheng; Sarah A Pendergrass; Anna M Kucharska-Newton; Unhee Lim; Jose Luis Ambite; Christian P Caberto; Kristine R Monroe; Fredrick Schumacher; Lucia A Hindorff; Matthew T Oetjens; Sarah Wilson; Robert J Goodloe; Shelly-Ann Love; Brian E Henderson; Laurence N Kolonel; Christopher A Haiman; Dana C Crawford; Kari E North; Gerardo Heiss; Marylyn D Ritchie; Lynne R Wilkens; Loïc Le Marchand Journal: Am J Epidemiol Date: 2013-07-02 Impact factor: 4.897