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Kim Y, Chen J, Wirth MD, Shivappa N, Hebert JR. Lower Dietary Inflammatory Index Scores Are Associated with Lower Glycemic Index Scores among College Students. Nutrients 2018; 10:nu10020182. [PMID: 29414858 PMCID: PMC5852758 DOI: 10.3390/nu10020182] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Revised: 01/31/2018] [Accepted: 02/02/2018] [Indexed: 01/04/2023] Open
Abstract
The association between the Dietary Inflammatory Index (DII®), the glycemic index (GI), and the glycemic load (GL) is not known, although it is known that carbohydrates are pro-inflammatory. We aimed to measure the association between the DII and both GI and GL among college students. In this cross-sectional study, 110 college students completed a 3-day food diary, which was used to calculate the DII, the GI, the GL, and the healthy eating index (HEI)-2010. Least square means and 95% confidence intervals of the GI, the GL, and the HEI-2010 were presented per DII tertile using generalized linear mixed models. Participants in tertile 1 of DII scores had lower GI and GL scores, but higher HEI-2010 scores than those in tertile 3. Pearson correlations showed that DII score was positively correlated with the GI score (r = 0.30, p < 0.01), but negatively correlated with the HEI-2010 (r = −0.56, p < 0.001). DII score was not correlated with GL score. Results from this study suggest that increased inflammatory potential of diet, as represented by higher DII scores, was associated with increased GI scores and lower quality of diet on the HEI-2010. Use of the DII suggests new directions for dietary approaches for preventing chronic diseases that moves beyond convention by decreasing systemic inflammation.
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Affiliation(s)
- Yeonsoo Kim
- Department of Human Environmental Studies, Central Michigan University, Mount Pleasant, MI 48858, USA.
| | - Jie Chen
- School of Human Ecology, Louisiana Tech University, Ruston, LA 71270, USA.
| | - Michael D Wirth
- South Carolina Statewide Cancer Prevention and Control Program, University of South Carolina, Columbia, SC 29208, USA.
- Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC 29208, USA.
- Connecting Health Innovations LLC, Columbia, SC 29201, USA.
- College of Nursing, University of South Carolina, Columbia, SC 29208, USA.
| | - Nitin Shivappa
- South Carolina Statewide Cancer Prevention and Control Program, University of South Carolina, Columbia, SC 29208, USA.
- Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC 29208, USA.
- Connecting Health Innovations LLC, Columbia, SC 29201, USA.
| | - James R Hebert
- South Carolina Statewide Cancer Prevention and Control Program, University of South Carolina, Columbia, SC 29208, USA.
- Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC 29208, USA.
- Connecting Health Innovations LLC, Columbia, SC 29201, USA.
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Louie JCY, Jones M, Barclay AW, Brand-Miller JC. Dietary glycaemic index and glycaemic load among Australian adults - results from the 2011-2012 Australian Health Survey. Sci Rep 2017; 7:43882. [PMID: 28262812 PMCID: PMC5338341 DOI: 10.1038/srep43882] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Accepted: 01/30/2017] [Indexed: 11/09/2022] Open
Abstract
This study aimed to determine the major food groups contributing to dietary glycaemic load (GL). Plausible food intake data collected using a multiple-pass 24 hour recall from a weighted sample of 6326 adult respondents (52% male) of the 2011-2012 Australian Health Survey dataset (AHS) were analysed. The GI of foods was estimated based on a previously published step-wise method. Descriptive statistics were calculated for dietary glycaemic index (GI), GL and contribution to GL by major food groups, stratified by age and sex. Trends across age groups were assessed using linear regression. Pearson's χ2 was used to test for differences between age groups for categorical demographics variables. The mean (SD) dietary GI and GL was 54 (7) and 135 (59) respectively and the top 3 contributors to dietary GL were breads (14.4%), cereal-based dishes (10.3%) and breakfast cereals (ready to eat) (6.6%). There were small but significant differences in the GL contribution pattern between the sexes. The findings indicate that the average dietary GI of Australian adults is similar to that of other population groups, with a large proportion of starchy and energy-dense nutrient-poor foods that contribute to a high GL.
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Affiliation(s)
- Jimmy Chun Yu Louie
- School of Life and Environmental Sciences, Faculty of Science, The University of Sydney NSW 2006, Australia.,Charles Perkins Centre, The University of Sydney NSW 2006, Australia.,School of Biological Sciences, Faculty of Science, The University of Hong Kong, Pokfulam, Hong Kong
| | - Molly Jones
- School of Life and Environmental Sciences, Faculty of Science, The University of Sydney NSW 2006, Australia
| | - Alan W Barclay
- Charles Perkins Centre, The University of Sydney NSW 2006, Australia.,Accredited Practising Dietitian, Sydney, Australia
| | - Jennie C Brand-Miller
- School of Life and Environmental Sciences, Faculty of Science, The University of Sydney NSW 2006, Australia.,Charles Perkins Centre, The University of Sydney NSW 2006, Australia.,Accredited Practising Dietitian, Sydney, Australia
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