Dietary Inflammatory Index and Biomarkers of Lipoprotein Metabolism, Inflammation and Glucose Homeostasis in Adults
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Subject Recruitment
2.2. Clinical and Anthropometric Data
2.3. Diet and Lifestyle Data
2.4. Dietary Inflammatory Index
2.5. Biological Analyses
2.6. Lipoprotein Particle Profiling
2.7. Statistical Analysis
3. Results
3.1. Clinical and Demographic Characteristics Stratified by E-DII Median
3.2. Dietary Composition and Food Pyramid Servings
3.3. Lipoprotein Profiles Stratified by E-DII Median
3.4. Inflammatory Profiles Stratified by E-DII Median
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
- Naja, F.; Shivappa, N.; Nasreddine, L.; Kharroubi, S.; Itani, L.; Hwalla, N.; Mehio Sibai, A.; Hebert, J.R. Role of inflammation in the association between the western dietary pattern and metabolic syndrome among Lebanese adults. Int. J. Food Sci. Nutr. 2017, 68, 997–1004. [Google Scholar] [CrossRef] [PubMed]
- Ahluwalia, N.; Drouet, L.; Ruidavets, J.B.; Perret, B.; Amar, J.; Boccalon, H.; Hanaire-Broutin, H.; Ferrieres, J. Metabolic syndrome is associated with markers of subclinical atherosclerosis in a French population-based sample. Atherosclerosis 2006, 186, 345–353. [Google Scholar] [CrossRef] [PubMed]
- Alberti, K.G.; Eckel, R.H.; Grundy, S.M.; Zimmet, P.Z.; Cleeman, J.I.; Donato, K.A.; Fruchart, J.C.; James, W.P.; Loria, C.M.; Smith, S.C., Jr. Harmonizing the metabolic syndrome: A joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009, 120, 1640–1645. [Google Scholar] [PubMed]
- Alberti, K.G.; Zimmet, P.; Shaw, J. The metabolic syndrome—A new worldwide definition. Lancet 2005, 366, 1059–1062. [Google Scholar] [CrossRef]
- Moller, D.E.; Kaufman, K.D. Metabolic syndrome: A clinical and molecular perspective. Annu. Rev. Med. 2005, 56, 45–62. [Google Scholar] [CrossRef] [PubMed]
- Shin, D.; Kongpakpaisarn, K.; Bohra, C. Trends in the prevalence of metabolic syndrome and its components in the United States 2007–2014. Int. J. Cardiol. 2018, 259, 216–219. [Google Scholar] [CrossRef] [PubMed]
- Hanley, A.J.; Festa, A.; D’Agostino, R.B., Jr.; Wagenknecht, L.E.; Savage, P.J.; Tracy, R.P.; Saad, M.F.; Haffner, S.M. Metabolic and inflammation variable clusters and prediction of type 2 diabetes: Factor analysis using directly measured insulin sensitivity. Diabetes 2004, 53, 1773–1781. [Google Scholar] [CrossRef] [PubMed]
- Shulman, G.I. Cellular mechanisms of insulin resistance. J. Clin. Investig. 2000, 106, 171–176. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hotamisligil, G.S. Inflammatory pathways and insulin action. Int. J. Obes. Relat. Metab. Disord. 2003, 27, S53–S55. [Google Scholar] [CrossRef] [PubMed]
- Ruan, H.; Lodish, H.F. Insulin resistance in adipose tissue: Direct and indirect effects of tumor necrosis factor-alpha. Cytokine Growth Factor Rev. 2003, 14, 447–455. [Google Scholar] [CrossRef]
- Hu, F.B.; Meigs, J.B.; Li, T.Y.; Rifai, N.; Manson, J.E. Inflammatory markers and risk of developing type 2 diabetes in women. Diabetes 2004, 53, 693–700. [Google Scholar] [CrossRef] [PubMed]
- Spranger, J.; Kroke, A.; Mohlig, M.; Hoffmann, K.; Bergmann, M.M.; Ristow, M.; Boeing, H.; Pfeiffer, A.F. Inflammatory cytokines and the risk to develop type 2 diabetes: Results of the prospective population-based European Prospective Investigation into Cancer and Nutrition (EPIC)—Potsdam Study. Diabetes 2003, 52, 812–817. [Google Scholar] [CrossRef] [PubMed]
- Hotamisligil, G.S. Inflammation and metabolic disorders. Nature 2006, 444, 860–867. [Google Scholar] [CrossRef] [PubMed]
- Calder, P.C.; Ahluwalia, N.; Brouns, F.; Buetler, T.; Clement, K.; Cunningham, K.; Esposito, K.; Jonsson, L.S.; Kolb, H.; Lansink, M.; et al. Dietary factors and low-grade inflammation in relation to overweight and obesity. Br. J. Nutr. 2011, 106, S1–S78. [Google Scholar] [CrossRef] [PubMed]
- Calder, P.C.; Ahluwalia, N.; Albers, R.; Bosco, N.; Bourdet-Sicard, R.; Haller, D.; Holgate, S.T.; Jonsson, L.S.; Latulippe, M.E.; Marcos, A.; et al. A consideration of biomarkers to be used for evaluation of inflammation in human nutritional studies. Br. J. Nutr. 2013, 109, S1–S34. [Google Scholar] [CrossRef] [PubMed]
- Shivappa, N.; Steck, S.E.; Hurley, T.G.; Hussey, J.R.; Hebert, J. R Designing and developing a literature-derived, population-based dietary inflammatory index. Public Health Nutr. 2014, 17, 1689–1696. [Google Scholar] [CrossRef] [PubMed]
- Mazidi, M.; Shivappa, N.; Wirth, M.D.; Hebert, J.R.; Mikhailidis, D.P.; Kengne, A.P.; Banach, M. Dietary inflammatory index and cardiometabolic risk in US adults. Atherosclerosis 2018, 276, 23–27. [Google Scholar] [CrossRef] [PubMed]
- Shivappa, N.; Steck, S.E.; Hurley, T.G.; Hussey, J.R.; Ma, Y.; Ockene, I.S.; Tabung, F.; Hebert, J.R. A population-based dietary inflammatory index predicts levels of C-reactive protein in the Seasonal Variation of Blood Cholesterol Study (SEASONS). Public Health Nutr. 2014, 17, 1825–1833. [Google Scholar] [CrossRef] [PubMed]
- Wirth, M.D.; Burch, J.; Shivappa, N.; Violanti, J.M.; Burchfiel, C.M.; Fekedulegn, D.; Andrew, M.E.; Hartley, T.A.; Miller, D.B.; Mnatsakanova, A.; et al. Association of a dietary inflammatory index with inflammatory indices and metabolic syndrome among police officers. J. Occup. Environ. Med. 2014, 56, 986–989. [Google Scholar] [CrossRef] [PubMed]
- Tabung, F.K.; Steck, S.E.; Zhang, J.; Ma, Y.; Liese, A.D.; Agalliu, I.; Hingle, M.; Hou, L.; Hurley, T.G.; Jiao, L.; et al. Construct validation of the dietary inflammatory index among postmenopausal women. Ann. Epidemiol. 2015, 25, 398–405. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Shivappa, N.; Hebert, J.R.; Rietzschel, E.R.; De Buyzere, M.L.; Langlois, M.; Debruyne, E.; Marcos, A.; Huybrechts, I. Associations between dietary inflammatory index and inflammatory markers in the Asklepios Study. Br. J. Nutr. 2015, 113, 665–671. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wirth, M.D.; Sevoyan, M.; Hofseth, L.; Shivappa, N.; Hurley, T.G.; Hebert, J.R. The Dietary Inflammatory Index is associated with elevated white blood cell counts in the National Health and Nutrition Examination Survey. Brain Behav. Immun. 2017, 69, 296–303. [Google Scholar] [CrossRef] [PubMed]
- Shivappa, N.; Godos, J.; Hebert, J.R.; Wirth, M.D.; Piuri, G.; Speciani, A.F.; Grosso, G. Dietary Inflammatory Index and Cardiovascular Risk and Mortality-A Meta-Analysis. Nutrients 2018, 10, 200. [Google Scholar] [CrossRef] [PubMed]
- Kearney, P.M.; Harrington, J.M.; Mc Carthy, V.J.; Fitzgerald, A.P.; Perry, I.J. Cohort Profile: The Cork and Kerry Diabetes and Heart Disease Study. Int. J. Epidemiol. 2012, 42, 1253–1262. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Craig, C.L.; Marshall, A.L.; Sjostrom, M.; Bauman, A.E.; Booth, M.L.; Ainsworth, B.E.; Pratt, M.; Ekelund, U.; Yngve, A.; Sallis, J.F.; et al. International physical activity questionnaire: 12-country reliability and validity. Med. Sci. Sports Exerc. 2003, 35, 1381–1395. [Google Scholar] [CrossRef] [PubMed]
- Harrington, J. Validation of a Food Frequency Questionnaire as a Tool for Assessing Nutrient Intake; National University of Ireland Galway: Galway, Ireland, 1997. [Google Scholar]
- Riboli, E.; Elmstahl, S.; Saracci, R.; Gullberg, B.; Lindgarde, F. The Malmo Food Study: Validity of two dietary assessment methods for measuring nutrient intake. Int. J. Epidemiol. 1997, 26, S161–S173. [Google Scholar] [CrossRef] [PubMed]
- Grundy, S.M.; Cleeman, J.I.; Daniels, S.R.; Donato, K.A.; Eckel, R.H.; Franklin, B.A.; Gordon, D.J.; Krauss, R.M.; Savage, P.J.; Smith, S.C., Jr.; et al. Diagnosis and management of the metabolic syndrome. An American Heart Association/National Heart, Lung and Blood Institute Scientific Statement. Executive summary. Cardiol. Rev. 2005, 13, 322–327. [Google Scholar] [CrossRef] [PubMed]
- McCance, R.A. Widdowson, E.M. Mc. Cance and Widdowson.’s The Composition of Foods; The Royal Society of Chemistry: Cambridge, UK, 2002. [Google Scholar]
- Jeyarajah, E.J.; Cromwell, W.C.; Otvos, J.D. Lipoprotein particle analysis by nuclear magnetic resonance spectroscopy. Clin. Lab. Med. 2006, 26, 847–870. [Google Scholar] [CrossRef] [PubMed]
- Shalaurova, I.; Connelly, M.A.; Garvey, W.T.; Otvos, J.D. Lipoprotein insulin resistance index: A lipoprotein particle-derived measure of insulin resistance. Metab. Syndr. Relat. Disord. 2014, 12, 422–429. [Google Scholar] [CrossRef] [PubMed]
- Pimenta, A.M.; Toledo, E.; Rodriguez-Diez, M.C.; Gea, A.; Lopez-Iracheta, R.; Shivappa, N.; Hebert, J.R.; Martinez-Gonzalez, M.A. Dietary indexes, food patterns and incidence of metabolic syndrome in a Mediterranean cohort: The SUN project. Clin. Nutr. 2015, 34, 508–514. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sokol, A.; Wirth, M.D.; Manczuk, M.; Shivappa, N.; Zatonska, K.; Hurley, T.G.; Hebert, J.R. Association between the dietary inflammatory index, waist-to-hip ratio and metabolic syndrome. Nutr. Res. 2016, 36, 1298–1303. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Neufcourt, L.; Assmann, K.E.; Fezeu, L.K.; Touvier, M.; Graffouillere, L.; Shivappa, N.; Hebert, J.R.; Wirth, M.D.; Hercberg, S.; Galan, P.; et al. Prospective association between the dietary inflammatory index and metabolic syndrome: Findings from the SU.VI.MAX study. Nutr. Metab. Cardiovasc. Dis. 2015, 25, 988–996. [Google Scholar] [CrossRef] [PubMed]
- Wood, L.G.; Shivappa, N.; Berthon, B.S.; Gibson, P.G.; Hebert, J.R. Dietary inflammatory index is related to asthma risk, lung function and systemic inflammation in asthma. Clin. Exp. Allergy 2015, 45, 177–183. [Google Scholar] [CrossRef] [PubMed]
- Patterson, C.C.; Smith, A.E.; Yarnell, J.W.; Rumley, A.; Ben-Shlomo, Y.; Lowe, G.D. The associations of interleukin-6 (IL-6) and downstream inflammatory markers with risk of cardiovascular disease: The Caerphilly Study. Atherosclerosis 2010, 209, 551–557. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cesari, M.; Penninx, B.W.; Newman, A.B.; Kritchevsky, S.B.; Nicklas, B.J.; Sutton-Tyrrell, K.; Rubin, S.M.; Ding, J.; Simonsick, E.M.; Harris, T.B.; et al. Inflammatory markers and onset of cardiovascular events: Results from the Health ABC study. Circulation 2003, 108, 2317–2322. [Google Scholar] [CrossRef] [PubMed]
- Kizer, J.R.; Benkeser, D.; Arnold, A.M.; Mukamal, K.J.; Ix, J.H.; Zieman, S.J.; Siscovick, D.S.; Tracy, R.P.; Mantzoros, C.S.; Defilippi, C.R.; et al. Associations of total and high-molecular-weight adiponectin with all-cause and cardiovascular mortality in older persons: The Cardiovascular Health Study. Circulation 2012, 126, 2951–2961. [Google Scholar] [CrossRef] [PubMed]
- Wannamethee, S.G.; Whincup, P.H.; Lennon, L.; Sattar, N. Circulating adiponectin levels and mortality in elderly men with and without cardiovascular disease and heart failure. Arch. Intern. Med. 2007, 167, 1510–1517. [Google Scholar] [CrossRef] [PubMed]
- Georgousopoulou, E.N.; Kouli, G.M.; Panagiotakos, D.B.; Kalogeropoulou, A.; Zana, A.; Chrysohoou, C.; Tsigos, C.; Tousoulis, D.; Stefanadis, C.; Pitsavos, C. Anti-inflammatory diet and 10-year (2002–2012) cardiovascular disease incidence: The ATTICA study. Int. J. Cardiol. 2016, 222, 473–478. [Google Scholar] [CrossRef] [PubMed]
- Tyrovolas, S.; Koyanagi, A.; Kotsakis, G.A.; Panagiotakos, D.; Shivappa, N.; Wirth, M.D.; Hebert, J.R.; Haro, J.M. Dietary inflammatory potential is linked to cardiovascular disease risk burden in the US adult population. Int. J. Cardiol. 2017, 240, 409–413. [Google Scholar] [CrossRef] [PubMed]
- Arsenault, B.J.; Lemieux, I.; Despres, J.P.; Gagnon, P.; Wareham, N.J.; Stroes, E.S.; Kastelein, J.J.; Khaw, K.T.; Boekholdt, S.M. HDL particle size and the risk of coronary heart disease in apparently healthy men and women: the EPIC-Norfolk prospective population study. Atherosclerosis 2009, 206, 276–281. [Google Scholar] [CrossRef] [PubMed]
- Garvey, W.T.; Kwon, S.; Zheng, D.; Shaughnessy, S.; Wallace, P.; Hutto, A.; Pugh, K.; Jenkins, A.J.; Klein, R.L.; Liao, Y. Effects of insulin resistance and type 2 diabetes on lipoprotein subclass particle size and concentration determined by nuclear magnetic resonance. Diabetes 2003, 52, 453–462. [Google Scholar] [CrossRef] [PubMed]
- Rizzo, M.; Pernice, V.; Frasheri, A.; Berneis, K. Atherogenic lipoprotein phenotype and LDL size and subclasses in patients with peripheral arterial disease. Atherosclerosis 2008, 197, 237–241. [Google Scholar] [CrossRef] [PubMed]
- Horne, B.D.; Anderson, J.L.; John, J.M.; Weaver, A.; Bair, T.L.; Jensen, K.R.; Renlund, D.G.; Muhlestein, J.B.; Muhlestein and Intermountain Heart Collaborative (IHC) Study Group. Which white blood cell subtypes predict increased cardiovascular risk? J. Am. Coll. Cardiol. 2005, 45, 1638–1643. [Google Scholar] [CrossRef] [PubMed]
- Mayr, H.L.; Itsiopoulos, C.; Tierney, A.C.; Ruiz-Canela, M.; Hebert, J.R.; Shivappa, N.; Thomas, C.J. Improvement in dietary inflammatory index score after 6-month dietary intervention is associated with reduction in interleukin-6 in patients with coronary heart disease: The AUSMED heart trial. Nutr. Res. 2018, 55, 108–121. [Google Scholar] [CrossRef] [PubMed]
- Phillips, C.M.; Perry, I.J. Does inflammation determine metabolic health status in obese and nonobese adults? J. Clin. Endocrinol. Metab. 2013, 98, E1610–E1619. [Google Scholar] [CrossRef] [PubMed]
- Phillips, C.M.; Perry, I.J. Lipoprotein particle subclass profiles among metabolically healthy and unhealthy obese and non-obese adults: Does size matter? Atherosclerosis 2015, 242, 399–406. [Google Scholar] [CrossRef] [PubMed]
- Lee, P.H.; Macfarlane, D.J.; Lam, T.H.; Stewart, S.M. Validity of the International Physical Activity Questionnaire Short Form (IPAQ-SF): A systematic review. Int. J. Behav. Nutr. Phys. Act. 2011, 8, 115. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hebert, J.R.; Clemow, L.; Pbert, L.; Ockene, I.S.; Ockene, J.K. Social desirability bias in dietary self-report may compromise the validity of dietary intake measures. Int. J. Epidemiol. 1995, 24, 389–398. [Google Scholar] [CrossRef] [PubMed]
- Hinchion, R.; Sheehan, J.; Perry, I. Primary care research: Patient registration. Ir. Med. J. 2002, 95, 249. [Google Scholar] [PubMed]
Min and Max of E-DII Scores | <Median E-DII −5.10 to −1.28 | >Median E-DII −1.28 to 3.68 | p |
---|---|---|---|
E-DII | −2.51 ± 0.02 | −0.06±0.03 | <0.001 |
Age (years) | 59.9 ± 0.17 | 59.5±0.17 | 0.04 |
Gender (% male) | 38.6 | 59.4 | <0.001 |
BMI (kg/m2) | 28.40 ± 0.15 | 28.72 ± 0.15 | 0.12 |
Waist (cm) | 95.48 ± 0.41 | 98.32 ± 0.41 | <0.001 |
Total cholesterol (mmol/L) | 5.25 ± 0.03 | 5.31 ± 0.03 | 0.24 |
LDL-C (mmol/L) | 3.13 ± 0.03 | 3.22 ± 0.03 | 0.04 |
HDL-C (mmol/L) | 1.48 ± 0.01 | 1.42 ± 0.01 | <0.001 |
Triglycerides (mmol/L) | 1.34 ± 0.02 | 1.45 ± 0.03 | 0.004 |
FPG (mmol/L) | 5.17 ± 0.04 | 5.21 ± 0.04 | 0.03 |
Insulin (µIU/mL) | 11.02 ± 0.29 | 12.10 ± 0.35 | 0.06 |
HOMA | 2.71 ± 0.09 | 2.98 ± 0.10 | 0.06 |
QUICKI | 0.28 ± 0.002 | 0.27 ± 0.002 | 0.26 |
SBP (mm Hg) | 128.5 ± 0.52 | 130.6 ± 0.54 | 0.005 |
DBP (mm Hg) | 79.9 ± 0.31 | 80.5 ± 0.31 | 0.17 |
Current smokers (%) | 12.6 | 16.7 | 0.008 |
Moderate and heavy alcohol consumers (%) | 78.9 | 80.5 | 0.49 |
Low intensity physical activity (%) | 43.5 | 52.9 | <0.001 |
Type 2 diabetes (%) | 8.9 | 8.5 | 0.71 |
CVD (%) | 10.7 | 10.1 | 0.66 |
MetS (%) | 21.5 | 25.4 | 0.04 |
Obesity (%) | 36.3 | 34.0 | 0.14 |
Hypertension (%) | 46.5 | 43.7 | 0.24 |
Anti-inflammatory medication (%) | 4.1 | 4.3 | 0.82 |
Lipid lowering medication (%) | 6.9 | 6.4 | 0.65 |
Min and Max of E-DII Scores | <Median E-DII −5.10 to −1.28 | >Median E-DII −1.28 to 3.68 | p |
---|---|---|---|
Dietary composition | |||
Kilocalories | 2056 ± 26 | 2000 ± 25 | 0.80 |
Fat (% EI) | 33.74 ± 0.22 | 33.77 ± 0.28 | 0.06 |
SFA (% EI) | 34.49 ± 0.20 | 34.57 ± 0.20 | 0.79 |
PUFA (% EI) | 19.98 ± 0.18 | 19.90 ± 0.18 | 0.830 |
MUFA (% EI) | 31.60 ± 0.10 | 31.53 ± 0.10 | 0.28 |
Carbohydrate (% EI) | 49.23 ± 0.27 | 48.64 ± 0.28 | 0.07 |
Protein (% EI) | 18.42 ± 0.13 | 18.76 ± 0.14 | 0.08 |
Sugar (% EI) | 20.57 ± 0.23 | 20.71 ± 0.25 | 0.37 |
Alcohol (% EI) | 1.51 ± 0.09 | 1.65 ± 0.10 | 0.13 |
Fibre (% EI) | 2.62 ± 0.02 | 2.57 ± 0.02 | 0.08 |
Daily food pyramid shelf servings | |||
Bread, cereal, potatoes, grain and rice | 5.03 ± 0.09 | 5.51 ± 0.10 | <0.001 |
Fruit and vegetables | 9.00 ± 0.18 | 5.75 ± 0.11 | <0.001 |
Dairy | 1.77 ± 0.04 | 2.11 ± 0.05 | <0.001 |
Meat, fish, poultry and eggs | 2.25 ± 0.03 | 2.55 ± 0.05 | <0.001 |
Fats, high fat/sugar foods and drinks | 5.85 ± 0.10 | 9.95 ± 0.18 | <0.001 |
Min and Max of E-DII Scores | <Median E-DII −5.10 to −1.28 | >Median E-DII −1.28 to 3.68 | p |
---|---|---|---|
Lipoprotein Particle Concentration | |||
Total TRL (nmol/L) | 65.84 ± 1.40 | 67.60 ± 1.36 | 0.37 |
Large VLDL (nmol/L) | 2.31 ± 0.136 | 3.05 ± 0.16 | <0.001 |
Medium VLDL (nmol/L) | 26.91 ± 0.79 | 28.54 ± 0.79 | 0.14 |
Small VLDL (nmol/L) | 36.62 ± 0.89 | 36.01 ± 0.83 | 0.61 |
IDL (nmol/L) | 105.42 ± 2.68 | 120.66 ± 2.98 | <0.001 |
Total LDL (nmol/L) | 1232.54 ± 12.96 | 1294.55 ± 13.24 | 0.001 |
Large LDL (nmol/L) | 623.12 ± 10.02 | 570.03 ± 9.24 | <0.001 |
Small LDL (nmol/L) | 504.00 ± 12.92 | 603.84 ± 13.65 | <0.001 |
Total HDL (mol/L) | 38.51 ± 0.20 | 38.20 ± 0.20 | 0.27 |
Large HDL (mol/L) | 7.46 ± 0.14 | 6.53 ± 0.13 | <0.001 |
Medium HDL (mol/L) | 13.82 ± 0.20 | 13.24 ± 0.19 | 0.04 |
Small HDL (mol/L) | 17.22 ± 0.18 | 18.42 ± 0.19 | <0.001 |
Lipoprotein Particle Size | |||
VLDL (nm) | 44.61 ± 0.20 | 45.48 ± 0.22 | 0.003 |
LDL (nm) | 20.93 ± 0.02 | 20.81 ± 0.02 | <0.001 |
HDL (nm) | 9.35 ± 0.02 | 9.23 ± 0.02 | <0.001 |
LP-IR score | 30.74 ± 0.69 | 37.08 ± 0.72 | <0.001 |
Min and Max of E-DII Scores | <Median E-DII −5.10 to −1.28 | >Median E-DII −1.28 to 3.68 | p |
---|---|---|---|
Inflammatory score | 7.74 ± 0.12 | 8.29 ± 0.10 | <0.001 |
C3 (mg/dL) | 134.31 ± 0.78 | 136.90 ± 0.76 | 0.04 |
CRP (mg/L) | 2.19 ± 0.12 | 2.45 ± 0.11 | 0.03 |
IL-6 (pg/mL) | 2.72 ± 0.14 | 3.02 ± 0.15 | <0.001 |
TNF-α (pg/mL) | 6.23 ± 0.08 | 6.51 ± 0.09 | 0.001 |
Adiponectin (ng/mL) | 6.05 ± 0.13 | 5.41 ± 0.13 | <0.001 |
Leptin (ng/mL) | 2.85 ± 0.12 | 2.78 ± 0.10 | 0.11 |
Resistin (ng/mL) | 5.64 ± 0.10 | 5.78 ± 0.11 | 0.50 |
WBC (109/L) | 5.85 ± 0.07 | 6.14 ± 0.06 | 0.001 |
Neutrophils (109/L) | 3.23 ± 0.04 | 3.48 ± 0.04 | <0.001 |
Lymphocytes (109/L) | 1.83 ± 0.02 | 1.86 ± 0.03 | 0.37 |
Monocytes (109/L) | 0.51 ± 0.005 | 0.54 ± 0.01 | <0.001 |
Eosinophils (109/L) | 0.20 ± 0.004 | 0.21 ± 0.005 | 0.06 |
Basophils (109/L) | 0.031 ± 0.001 | 0.033 ± 0.001 | 0.03 |
Neutrophil to lymphocyte ratio | 1.89 ± 0.03 | 2.04 ± 0.03 | <0.001 |
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Phillips, C.M.; Shivappa, N.; Hébert, J.R.; Perry, I.J. Dietary Inflammatory Index and Biomarkers of Lipoprotein Metabolism, Inflammation and Glucose Homeostasis in Adults. Nutrients 2018, 10, 1033. https://doi.org/10.3390/nu10081033
Phillips CM, Shivappa N, Hébert JR, Perry IJ. Dietary Inflammatory Index and Biomarkers of Lipoprotein Metabolism, Inflammation and Glucose Homeostasis in Adults. Nutrients. 2018; 10(8):1033. https://doi.org/10.3390/nu10081033
Chicago/Turabian StylePhillips, Catherine M., Nitin Shivappa, James R. Hébert, and Ivan J. Perry. 2018. "Dietary Inflammatory Index and Biomarkers of Lipoprotein Metabolism, Inflammation and Glucose Homeostasis in Adults" Nutrients 10, no. 8: 1033. https://doi.org/10.3390/nu10081033
APA StylePhillips, C. M., Shivappa, N., Hébert, J. R., & Perry, I. J. (2018). Dietary Inflammatory Index and Biomarkers of Lipoprotein Metabolism, Inflammation and Glucose Homeostasis in Adults. Nutrients, 10(8), 1033. https://doi.org/10.3390/nu10081033