| Literature DB >> 27527152 |
Miguel Ruiz-Canela1,2,3, Maira Bes-Rastrollo4,5,6, Miguel A Martínez-González7,8,9.
Abstract
Inflammation is an underlying pathophysiological process in chronic diseases, such as obesity, type 2 diabetes mellitus and cardiovascular disease. In fact, a number of systematic reviews have shown the association between inflammatory biomarkers, such as CRP, IL-1β, IL-6, TNF-α, IL-4, or IL-10, and cardio-metabolic diseases. Diet is one of the main lifestyle-related factors which modulates the inflammatory process. Different individual foods and dietary patterns can have a beneficial health effect associated with their anti-inflammatory properties. The dietary inflammatory index (DII) was recently developed to estimate the inflammatory potential of overall diet. The aim of this review is to examine the findings of recent papers that have investigated the association between the DII, cardio-metabolic risk factors and cardiovascular disease. The relevance of the DII score in the association between inflammation and cardio-metabolic diseases is critically appraised, as well as its role in the context of healthy dietary patterns. We conclude that the DII score seems to be a useful tool to appraise the inflammatory capacity of the diet and to better understand the relationships between diet, inflammation, and cardio-metabolic diseases.Entities:
Keywords: cardiovascular disease; dietary inflammatory index; inflammation; metabolic syndrome; mortality; type-2 diabetes
Mesh:
Year: 2016 PMID: 27527152 PMCID: PMC5000663 DOI: 10.3390/ijms17081265
Source DB: PubMed Journal: Int J Mol Sci ISSN: 1422-0067 Impact factor: 5.923
Association between the DII score and the incidence of cardiovascular disease.
| Study Name | Design | # Food Parameters | Follow-up 1 (Years) | N Total (CVD Cases) | Groups | Adjusted Relative Risk (95% CI) | Covariables |
|---|---|---|---|---|---|---|---|
| GOS 2 [ | Cohort | 22 using FFQ | 5 | 1363 (76) | Negative DII (ref) vs. Positive DII | OR = 2.00 (1.01–3.96) | Family history of CVD, blood pressure, sedentary, diabetes, smoking, waist circumference, age, total energy intake |
| PREDIMED 3 [ | Cohort | 32 using FFQ | 4.7 | 7216 (277) | Quartile 1 (ref) vs. Quartile 4 | HR = 1.73 (1.15–2.60) | Age, sex, overweight/obesity, waist-to-height ratio, total energy intake, smoking status, diabetes, hypertension, dyslipidemia, family history of premature cardiovascular disease, physical activity, educational level, intervention group, center |
| SUN 4 [ | Cohort | 28 using FFQ | 8.9 | 18,794 (117) | Quartile 1 (ref) vs. Quartile 4 | HR = 2.03 (1.06–3.88) | Age, sex, hypertension, dyslipidaemia, diabetes, smoking status, family history of cardiovascular disease, total energy intake, physical activity, body mass index, educational level, other cardiovascular diseases, special diet at baseline, snacking, average time sitting, average time spent watching television |
| SU.VI.MAX 5 [ | Cohort | 36 using 24-h dietary records | 11.4 | 7743 (292) | Quartile 1 (ref) vs. Quartile 4 | HR = 1.16 (0.79–1.69) | Sex, energy intake, supplementation group, number of 24-h records, education level, marital status, smoking status, physical activity, body mass index |
| 11.4 | 7602 (93) | Quartile 1 (ref) vs. Quartile 4 | HR = 2.26 * (1.08–4.71) | ||||
| NHANES 6 [ | Cross-sectional | 27 using 24-h dietary records | NA | 15,693 (1734) | Quartile 1 (ref) vs. Quartile 4 | OR = 1.30 (1.06–1.58) | Family member smoking status, personal smoking status, age, body mass index |
1 Mean or median except the GOS study; 2 GOS: Geelong Osteoporosis study; 3 PREDIMED: Prevention with Mediterranean Diet (PREvención con DIeta MEDiterránea); 4 SUN: University of Navarra Follow-up (Seguimiento Universidad de Navarra); 5 SU.VI.MAX: Antioxidant Vitamins and Minerals Supplementation (SUpplémentation en VItamines et Minéraux AntioXydants); 6 NHANES: National Health and Nutrition Examination Survey III follow-up; * HR for myocardial infarction in the stratified analysis; #: number; ref: reference.
Figure 1Cumulative incidence of CVD in the PREDIMED study [28] according to tertiles of the DII score.
Figure 2Cumulative incidence of CVD in the the SUN cohort [29] according to quartiles of the DII score (merging the two intermediate quartiles to build a medium category). The data are adjusted for sex, age, hypertension, dyslipidemia, diabetes, smoking, family history of premature CVD, and total energy intake.
Association between the DII score and the metabolic syndrome 1.
| Study Name | Design | # Food Parameters | Follow-up (Years) | N Total (Cases) | Groups | Adjusted Relative Risk (95% CI) | Covariables |
|---|---|---|---|---|---|---|---|
| PONS 2 [ | Cross-sectional | 22 using FFQ | NA | 3862 (1159) | Quartile 1 (ref) vs. Quartile 4 | OR = 0.96 (0.77–1.19) | Body mass index, age |
| BCOPS 3 [ | Cross-sectional | Not reported | NA | 464 (125) | Quartile 1 (ref) vs. Quartile 4 | OR = 0.87 (0.46–1.63) | Age, sex |
| SUN 4 [ | Cohort | 28 using FFQ | 8.3 | 6851 (346) | Quintile 1 (ref) vs. Quintile 5 | HR * = 0.86 (0.60–1.23) | Age, sex, smoking, alcohol consumption, snacking between main meals, use of special diets, television watching, physical activity, changes in weight over the last 5 years prior, body mass index |
| SU.VI.MAX 5 [ | Cohort | 36 using 24-h dietary records | 12.4 | 3726 (524) | Quartile 1 (ref) vs. Quartile 4 | HR = 1.39 (1.01–1.92) | Age, sex, supplementation group, number of 24 h records, energy intake, education level, smoking status, physical activity, body mass index |
1 MetSyn was defined as the presence of at least three of these components: Abdominal obesity; high blood pressure; low HDL cholesterol; high triglycerides and high glucose level; 2 PONS: Polish-Norwegian Study; 3 BCOPS: Buffalo Cardio-Metabolic Occupational Police Stress; 4 SUN: University of Navarra Follow-up (Seguimiento Universidad de Navarra); 5 SU.VI.MAX: Antioxidant Vitamins and Minerals Supplementation (SUpplémentation en VItamines et Minéraux AntioXydants); #: Number; ref: reference; * Data provided by the authors.
Association between the DII score and all-cause mortality.
| Study Name | Design | # Food Parameters | Follow-up (Years) | N Total (Cases) | Groups | Adjusted Relative Risk (95% CI) | Covariables |
|---|---|---|---|---|---|---|---|
| NHANES 1 III [ | Cohort | 27 using 24-h dietary records | 13.5 | 12,438 (2795) | Tertile 1 (ref) vs. Tertile 3 | HR = 1.34 (1.19, 1.51) | Age, sex, race, diabetes status, hypertension, physical activity, BMI, poverty index, smoking |
| NHANES 1 III [ | Cohort | 27 using 24-h dietary records | NA | 2681 (896) | Tertile 1 (ref) vs. Tertile 3 | HR = 1.39 (1.13, 1.72) | Age, sex, race, HbA1C, current smoking, physical activity, body mass index, systolic blood pressure |
| Iowa Women’s Health study [ | Cohort | 37 using FFQ | 20.7 | 37,525 (17,793) | Quartile 1 (ref) vs. Quartile 4 | HR = 1.08 (1.03–1.13) | Age, body mass index, smoking status, pack-years of Smoking, hormone replacement therapy use, education, diabetes, hypertension, heart disease, cancer, total energy intake |
| SU.VI.MAX 2 [ | Cohort | 36 using 24-h dietary records | 1.24 | 8089 (207) | Tertile 1 (ref) vs. Tertile 3 | HR * = 2.10 (1.15–3.84) | Age, sex, intervention group, number of 24-hour dietary records, body mass index, physical activity, smoking status, educational level, family history of cancer in first-degree relatives, family history of CVD in first-degree relatives, energy intake without alcohol, and alcohol intake |
| HR ** = 1.09 (0.67–1.77) | |||||||
| Swedish Mammography Cohort [ | Cohort | 27 using FFQ | 15 | 33,747 (7095) | Quintile 1 (ref) vs. Quintile 5 | HR = 1.41 (1.21–1.64) | Age, energy intake, body mass index, education, smoking status, physical activity, alcohol intake |
1 NHANES: National Health and Nutrition Examination Survey III follow-up; 2 SU.VI.MAX: Antioxidant Vitamins and Minerals Supplementation (SUpplémentation en VItamines et Minéraux AntioXydants); #: number; ref: reference; * HR for the placebo group; ** HR for the antioxidant supplementation group.