Abstract
Background: Chronic inflammation is a central mechanism involved in cardiovascular diseases, cancer, diabetes, and chronic respiratory diseases, 4 leading causes of mortality. Diet is a major source of pro- and anti-inflammatory bioactive compounds. The Dietary Inflammatory Index (DII) was designed to estimate the overall inflammatory potential of the diet.
Objective: Our aim was to study the prospective association between the DII and mortality, as well as assess whether antioxidant supplementation could modulate this association.
Design: The Supplémentation en Vitamines et Minéraux Antioxydants study was a randomized, double-blind, placebo-controlled trial in which participants received low-dose antioxidants or a placebo from 1994 to 2002. In this observational prospective analysis, 8089 participants (mean ± SD age at baseline: 49.0 ± 6.3 y) were followed between 1994 and 2007 (median: 12.4 y). The DII was calculated from repeated 24-h dietary records; higher scores correspond to more proinflammatory diets. A total of 207 deaths occurred during follow-up, including 123 due to cancer and 41 due to cardiovascular events. Multivariate Cox proportional hazards models were computed.
Results: Sex-specific tertiles of the DII were positively associated with cardiovascular + cancer mortality (HR for tertile 3 compared with tertile 1 = 1.53; 95% CI: 1.01, 2.32; P-trend = 0.05) and specific cancer mortality (HR for tertile 3 compared with tertile 1 = 1.83; 95% CI: 1.12, 2.99; P-trend = 0.02). The corresponding P value was 0.07 for all-cause mortality. The DII was statistically significantly associated with increased all-cause mortality in the placebo group (HR for tertile 3 compared with tertile 1 = 2.10; 95% CI: 1.15, 3.84; P-trend = 0.02) but not in the antioxidant-supplemented group (P-trend = 0.8; P-interaction = 0.098).
Conclusion: These results suggest that a proinflammatory diet is associated with increased all-cause and cancer mortality and antioxidants may counteract some of the proinflammatory effects of the diet. This trial was registered at clinicaltrials.gov as NCT00272428.
Keywords: antioxidants, Dietary Inflammatory Index, inflammation, mortality, prospective study
INTRODUCTION
Chronic inflammation has been broadly acknowledged as a central mechanism in metabolic disorders associated with morbidity and mortality (1). In a meta-analysis of 54 long-term prospective studies, Kaptoge et al. (2) showed that blood C-reactive protein (CRP)8 concentration, a biomarker of systemic inflammation, was positively associated with vascular mortality and death from several cancers. Since then, several prospective studies showed positive associations between biomarkers of inflammation, such as C-reactive protein (3), IL-6 (3, 4), TNF-α receptor 1 (4), and chitinase 3–like protein 1 (5), and mortality.
The effect of diet on chronic inflammation has been widely investigated (6–8). Pro- or anti-inflammatory properties have been attributed to several bioactive components of the diet, based on experimental and epidemiologic studies (6–11). A literature-derived scoring system, the Dietary Inflammatory Index (DII), has been developed to estimate the pro- and anti-inflammatory potential of the overall diet and to investigate its possible relations with health outcomes (12).
Although several studies have been published regarding the associations between the DII and incidence of chronic diseases (13–29), only 2 studies, restricted to women, have investigated the relation between the pro- and anti-inflammatory potential of the diet measured with the DII and mortality (30, 31), and none has studied how this association is modulated by antioxidant supplementation.
Experimental studies have shown that chronic inflammation and oxidative stress are interrelated, and both contribute to the etiology of the main causes of death by chronic diseases, that is, cardiovascular diseases (CVDs), cancer, diabetes, and chronic respiratory diseases (1, 32, 33). Thus, we hypothesized that a proinflammatory diet could increase mortality risk and that the addition of antioxidants to the diet may counteract this association. Therefore, our objectives were 1) to investigate the relation between the DII and mortality (all causes, CVD, and cancer) in a large French prospective cohort and 2) to determine whether this relation is modulated by antioxidant supplementation.
METHODS
Study population
The Supplémentation en Vitamines et Minéraux Antioxydants (SU.VI.MAX) study is a population-based, double-blind, placebo-controlled, randomized trial (registered at clinicaltrials.gov as NCT00272428) initially performed to evaluate the effect of a daily intake of antioxidant supplements on ischemic heart disease and cancer incidence. All participants took a daily capsule containing a combination of 120 mg ascorbic acid, 30 mg vitamin E, 6 mg β-carotene, 100 μg selenium, and 20 mg zinc or a placebo (34). These antioxidants corresponded to vitamins and minerals that were frequently consumed as part of a balanced diet rich in fruits and vegetables and for which a protective effect against the development of chronic diseases was suggested by experimental and/or epidemiologic literature available at this time (35, 36). Participants were advised against taking any self-prescribed dietary supplement during the trial. During the first year of the study (1994–1995), 13,017 subjects were enrolled (7876 women aged 35–60 y and 5141 men aged 45–60 y). The intervention study lasted until 2002, and health event monitoring was pursued until September 2007. At the end of the intervention phase, the 7.5-y antioxidant supplementation was associated with lower total cancer incidence and all-cause mortality in men but not in women. In total, 5.2% of all participants were lost to follow-up.
Subjects provided written informed consent. The study was conducted according to the Declaration of Helsinki guidelines and was approved by the Ethics Committee for Studies with Human Subjects at the Paris-Cochin Hospital (CCPPRB No. 706) and the “Commission Nationale de l’Informatique et des Libertés” (CNIL No. 334641).
Baseline data collection
At enrollment, all participants completed questionnaires regarding sociodemographics, smoking status, physical activity, family history of CVD and cancer, and medication use. They also underwent a clinical examination and anthropometric measurements by study nurses and physicians. Age at menopause (natural or artificial) was self-reported by women during follow-up.
Dietary data were collected by using the Minitel Telematic Network (an Internet prototype), widely used in France as an adjunct to the telephone, at the beginning of the study. Participants were invited to provide a 24-h dietary record every 2 mo (randomly distributed over weekends and weekdays). To comply with the prospective design, we used dietary records from the first 2 y of follow-up. The participants had to select the foods consumed at breakfast, lunch, dinner, and/or any other occasion throughout the day among a predefined list of ∼1,000 items. Portion sizes were estimated by using a validated picture booklet distributed at enrollment (37). Participants were advised to declare all types of seasoning (such as garlic, ginger, pepper, or onion) when completing their 24-h records. In addition, the amounts of food or seasoning consumed from composite dishes were estimated by using French recipes validated by nutrition professionals. Energy, alcohol, and nutrient intakes were estimated by using a published French food composition table (38). The Phenol-Explorer database was used to estimate intake of total polyphenols, as well as intakes of the main groups and subgroups of polyphenols (www.phenol-explorer.eu) (39, 40).
DII computation
The computation of the DII has been described in detail previously (12). Briefly, the DII is a score initially designed with 45 dietary variables determined from a literature review of 1943 articles published up to 2010. A literature-derived inflammatory effect score was assigned to every micronutrient, macronutrient, or food variable associated with an increase (+1), a decrease (−1), or no effect (0) on 6 inflammatory biomarkers: IL-1β, IL-4, IL-6, IL-10, TNF-α, and CRP.
Mean intake of every food variable is transformed with standardized values from a world database into a z score, then converted to a percentile and centered. Finally, the centered percentile score for each food variable was multiplied by its associated coefficient, and then these were summed across the 45 dietary variables, thus providing an individual DII score. In the present study, the DII was based on 36 dietary variables that were available in our database. The following variables were computed into the score as proinflammatory factors: total intakes of energy, protein, carbohydrate, total fat, SFAs, cholesterol, vitamin B-12, and iron, whereas intakes of MUFAs, PUFAs, n–3 fatty acids, n–6 fatty acids, alcohol, fiber, magnesium, niacin, thiamine, riboflavin, vitamin B-6, vitamin A, vitamin C, vitamin D, vitamin E, folic acid, β-carotene, anthocyanidins, flavan-3-ol, flavonols, flavanones, flavones, isoflavones, garlic, ginger, pepper (seasoning), onion, and tea were entered as anti-inflammatory factors. Lower DII scores represented more anti-inflammatory diets, whereas higher DII scores represented more proinflammatory diets.
Vital status and causes of death
Information about vital status and causes of death was received from relatives or physicians during follow-up. At the end of follow-up, vital status of all subjects of the cohort and causes of death were verified with the national death registry (CépiDC). Causes of death from chronic diseases were classified by using the International Classification of Diseases, 10th Revision, Clinical Modification (41).
Statistical analysis
Among the 13,017 participants of the SU.VI.MAX study, 8112 provided at least 3 valid 24-h dietary records within the first 2 y of follow-up. To perform our analysis in a prospective design, we excluded subjects for whom death occurred within the first 3 y of follow-up (n = 23); leaving 8089 subjects for analysis (participants’ flowchart, Supplemental Figure 1). Less than 5% of all covariate values were missing and were replaced by the modal value. Food and nutrient intakes were assessed by using mean intakes calculated from all dietary records provided during the first 2 y of follow-up for each participant.
Baseline characteristics of participants were compared between subjects who died during follow-up (all causes) and those who did not by using χ2 tests or Student’s t tests, as appropriate.
HRs and 95% CIs obtained from Cox proportional hazards models were used to estimate the association between the DII (continuous and sex-specific tertiles) and overall mortality, CVD + cancer mortality, and cancer-specific mortality. Statistical power was too limited to perform the analysis for CVD mortality separately (41 deaths due to CVD). Participants contributed person-time until the date of death, the date of the last completed questionnaire, or 30 September 2007, whichever occurred first. We confirmed that the proportional hazards assumption was satisfied through examination of the log-log (survival) compared with log-time plots. Tests for linear trend were performed by using the ordinal score of tertiles of the DII.
Multivariable models were adjusted for age (timescale in the Cox model), sex (male/female), antioxidant supplementation group of the initial SU.VI.MAX trial (antioxidant/placebo), number of dietary records (continuous), BMI (in kg/m2; <25, ≥25 to <30, or ≥30), physical activity (irregular, <1 h/d walking equivalent, or ≥1 h/d walking equivalent), smoking status (never, former, or current), educational level (primary, secondary, or university), first-degree family history of CVD (yes or no), first-degree family history of cancer (yes or no), daily mean energy intake without alcohol (residual method) (42), and daily mean alcohol intake.
Two-factor interactions were tested between the DII (continuous and sex-specific tertiles) and the antioxidant supplementation group of the initial SU.VI.MAX trial (antioxidant/placebo), alcohol intake (median cutoff), and smoking status (never/ever smokers) with the introduction of the corresponding product of 2 variables into the model. Each dietary component included in the DII has a unique inflammatory effect score and is derived from literature review of the association between each of these dietary components and inflammation (12). However, because PUFAs and n–3 and n–6 fatty acids are all included as independent components in the original DII, we also performed a sensitivity analysis by using a DII including PUFAs but excluding n–3 and n–6 fatty acids. Moreover, because available data for zinc composition were of poor quality in our data set (either missing or not validated), they were not included in the DII for the main analysis. However, sensitivity analyses were carried out with a modified DII that included zinc information (although limited).
All tests were 2-sided, and P < 0.05 was considered statistically significant. The SAS software version 9.3 (SAS Institute) was used for analyses.
RESULTS
During follow-up, 207 deaths occurred within the population, including 123 caused by cancer and 41 by CVD. Thus, with a type I error probability of 0.05 and a power of 0.8, we were able to detect RRs ≤0.6 or ≥1.5 for the comparison of the incidence of all-cause mortality between tertiles 3 and 1 of the DII. The median follow-up time was 12.4 y. DII scores ranked from −5.4 to 6.0 for women (mean ± SD: 0.6 ± 1.7) and −5.1 to 6.1 for men (mean ± SD: 0.8 ± 1.5). The characteristics of the study population are described in Table 1. At baseline, subjects who died during follow-up were older, were more often men, consumed more alcohol, had a higher physical activity, were more frequently former or current smokers, and were more likely to be overweight or obese compared with those who did not die during follow-up. Participants who provided at least three 24-h dietary records (n = 8112) were more likely to be men and to have a higher education level and were less likely to be smokers or obese compared with participants who provided fewer than three 24-h dietary records (n = 4905).
TABLE 1.
Baseline characteristics of the study population, SU.VI.MAX cohort, France, 1994–20071
| Noncases (n = 7882) | Overall mortality (n = 207) | Mortality by CVD or cancer (n = 164) | Cancer-specific mortality (n = 123) | P value | |
| DII | 0.7 ± 1.92 | 0.8 ± 1.7 | 0.8 ± 1.7 | 0.8 ± 1.7 | 0.6 |
| Age, y | 48.9 ± 6.3 | 52.5 ± 5.4 | 53 ± 5.4 | 52.9 ± 5.4 | <0.0001 |
| Sex, n (%) | <0.0001 | ||||
| Male | 3209 (40.7) | 117 (56.5) | 89 (54.3) | 56 (45.5) | |
| Female | 4673 (59.3) | 90 (43.5) | 75 (45.7) | 67 (54.5) | |
| Intervention group, n (%) | 0.7 | ||||
| Antioxidants | 3951 (50.1) | 101 (58.8) | 79 (48.1) | 57 (46.3) | |
| Placebo | 3931 (49.9) | 106 (51.2) | 85 (51.8) | 66 (53.7) | |
| Educational level, n (%) | 0.1 | ||||
| Primary | 1575 (20.0) | 54 (26.1) | 42 (25.6) | 26 (21.6) | |
| Secondary | 2982 (37.8) | 73 (35.3) | 60 (36.6) | 48 (39.0) | |
| University | 3325 (42.2) | 80 (38.6) | 62 (37.8) | 49 (39.8) | |
| Smoking status, n (%) | 0.0003 | ||||
| Never smoker | 3809 (48.3) | 73 (33.2) | 58 (35.4) | 45 (36.6) | |
| Former smoker | 3031 (38.5) | 92 (44.4) | 72 (43.9) | 52 (42.3) | |
| Current smoker | 1042 (13.2) | 42 (20.3) | 34 (20.7) | 26 (21.1) | |
| Physical activity, n (%) | 0.04 | ||||
| Irregular | 1966 (24.9) | 36 (17.4) | 27 (16.5) | 20 (16.3) | |
| <1 h/d of walking or equivalent | 2374 (30.1) | 71 (34.3) | 58 (35.4) | 47 (38.2) | |
| ≥1 h/d of walking or equivalent | 3542 (44.9) | 100 (48.3) | 79 (48.2) | 56 (45.5) | |
| BMI, n (%) | 0.05 | ||||
| <25 kg/m2 | 5099 (64.7) | 118 (57.0) | 93 (56.7) | 76 (61.8) | |
| ≥25–30 kg/m2 | 2289 (29.0) | 70 (33.8) | 55 (33.5) | 35 (28.5) | |
| ≥30 kg/m2 | 494 (6.3) | 19 (9.2) | 16 (9.8) | 12 (9.8) | |
| 24-h Dietary records, n | 9.4 ± 3.4 | 9.6 ± 3.1 | 9.5 ± 3.1 | 9.5 ± 3.1 | 0.4 |
| Without alcohol energy intake, kcal/d | 1962 ± 551.3 | 1984.6 ± 563.5 | 1997.6 ± 547.9 | 1989.5 ± 565.8 | 0.6 |
| Alcohol intake, g/d | 18.1 ± 20.7 | 23.2 ± 23.4 | 23.9 ± 23.2 | 22.4 ± 22.0 | 0.002 |
| Family history of cancer3 | 2728 (34.6) | 69 (33.3) | 53 (32.3) | 38 (30.9) | 0.7 |
| Family history of CVD3 | 3190 (40.5) | 87 (42.0) | 66 (40.2) | 49 (39.8) | 0.6 |
P value for the comparison between noncases and all death causes, by Student's t test or χ2 test where appropriate. CVD, cardiovascular disease; DII, Dietary Inflammatory Index; SU.VI.MAX, Supplémentation en Vitamines et Minéraux Antioxydants.
Mean ± SD (all such values).
In first-degree relatives.
Associations between the DII and mortality are shown in Table 2. The DII was positively associated with CVD + cancer mortality (HR per 1-point increment of the DII score = 1.14; 95% CI: 1.02, 1.27; P = 0.02; HR for tertile 3 compared with tertile 1 = 1.53; 95% CI: 1.01, 2.32; P = 0.05) and cancer-specific mortality (HR per 1-point increment of the DII score = 1.18; 95% CI: 1.04, 1.34; P = 0.01; HR for tertile 3 compared with tertile 1 = 1.83; 95% CI: 1.12, 2.99; P = 0.02). For all-cause mortality, the corresponding P values were 0.08 (continuous DII score) and 0.07 (DII score as sex-specific tertiles). The P-interaction between sex-specific tertiles of DII and the antioxidant supplementation group of the trial on all-cause mortality was 0.098 (Table 3). Mean ± SD DII scores were 0.7 ± 1.9 in the placebo group and 0.7 ± 1.9 in the antioxidant supplementation group (P = 0.4). In stratified analysis, the DII was positively associated with all-cause mortality within the placebo group (HR per 1-point increment of the DII score = 1.17; 95% CI: 1.02, 1.35; P = 0.03; HR for tertile 3 compared with tertile 1 = 2.10; 95% CI: 1.15, 3.84; P = 0.02) but not in the antioxidant supplementation group (both corresponding P values = 0.8). No interaction was detected between the DII and alcohol intake or smoking status (all P-interaction ≥ 0.3).
TABLE 2.
Associations between sex-specific tertiles of DII and mortality from multivariate Cox proportional hazards models, SU.VI.MAX cohort, France, 1994–20071
| n (cases/noncases) | HR (95% CI) | P-trend | |
| All-cause mortality | |||
| Continuous DII score | 207/7882 | 1.09 (0.99, 1.20) | 0.08 |
| T1 | 63/2633 | 1.00 (referent) | 0.07 |
| T2 | 69/2628 | 1.21 (0.83, 1.76) | |
| T3 | 75/2621 | 1.41 (0.97, 2.04) | |
| Mortality by CVD or cancer | |||
| Continuous DII score | 164/7882 | 1.14 (1.02, 1.27) | 0.02 |
| T1 | 49/2633 | 1.00 (referent) | 0.05 |
| T2 | 52/2628 | 1.15 (0.75, 1.77) | |
| T3 | 63/2621 | 1.53 (1.01, 2.32) | |
| Cancer-specific mortality | |||
| Continuous DII score | 123/7882 | 1.18 (1.04, 1.34) | 0.01 |
| T1 | 35/2633 | 1.00 (referent) | 0.02 |
| T2 | 38/2628 | 1.19 (0.71, 1.99) | |
| T3 | 50/2621 | 1.83 (1.12, 2.99) |
Sex-specific cutoffs for tertiles of DII adjusted for energy intake by the residual method were used. In men, lower bounds of tertiles 2 and 3 were 0.20 and 1.46. In women, lower bounds of tertiles 2 and 3 were −0.09 and 1.41. Multivariate Cox proportional hazards models were adjusted for age (timescale in the Cox model), sex, intervention group of the initial SU.VI.MAX trial, number of 24-h dietary records, BMI, 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. CVD, cardiovascular disease; DII, Dietary Inflammatory Index; SU.VI.MAX, Supplémentation en Vitamines et Minéraux Antioxydants; T, tertile.
TABLE 3.
Associations between sex-specific tertiles of DII and mortality from multivariate Cox proportional hazards models stratified by the antioxidant supplementation group, SU.VI.MAX cohort, France, 1994–20071
| n (cases/noncases) | HR (95% CI) | P-trend | P-interaction | |
| All-cause mortality (n = 207) | 0.098 | |||
| Placebo group | ||||
| Continuous DII score | 106/3931 | 1.17 (1.02, 1.35) | 0.03 | |
| T1 | 25/1323 | 1.00 (referent) | 0.02 | |
| T2 | 41/1315 | 2.17 (1.21, 3.91) | ||
| T3 | 40/1293 | 2.10 (1.15, 3.84) | ||
| Antioxidant supplementation group | ||||
| Continuous DII score | 101/3951 | 1.02 (0.89, 1.16) | 0.8 | |
| T1 | 38/1310 | 1.00 (referent) | 0.8 | |
| T2 | 28/1313 | 0.76 (0.46, 1.27) | ||
| T3 | 35/1328 | 1.09 (0.67, 1.77) | ||
| Mortality by CVD or cancer (n = 164) | 0.4 | |||
| Placebo group | ||||
| Continuous DII score | 85/3981 | 1.18 (1.01, 1.39) | 0.04 | |
| T1 | 23/1323 | 1.00 (referent) | 0.06 | |
| T2 | 29/1315 | 1.65 (0.85, 3.21) | ||
| T3 | 33/1293 | 1.92 (0.99, 3.71) | ||
| Antioxidant supplementation group | ||||
| Continuous DII score | 79/3951 | 1.11 (0.96, 1.28) | 0.2 | |
| T1 | 26/1310 | 1.00 (referent) | 0.3 | |
| T2 | 23/1313 | 0.88 (0.50, 1.56) | ||
| T3 | 30/1328 | 1.32 (0.77, 2.26) | ||
| Cancer-specific mortality (n = 123) | 0.3 | |||
| Placebo group | ||||
| Continuous DII score | 66/3931 | 1.24 (1.03, 1.50) | 0.03 | |
| T1 | 16/1323 | 1.00 (referent) | 0.02 | |
| T2 | 23/1315 | 2.09 (0.92, 4.78) | ||
| T3 | 27/1293 | 2.65 (1.18, 5.98) | ||
| Antioxidant supplementation group | ||||
| Continuous DII score | 57/3951 | 1.13 (0.95, 1.34) | 0.2 | |
| T1 | 19/1310 | 1.00 (referent) | 0.3 | |
| T2 | 15/1313 | 0.79 (0.40, 1.59) | ||
| T3 | 23/1328 | 1.43 (0.76, 2.68) |
Sex-specific cutoffs for tertiles of DII adjusted for energy intake by the residual method were used. In men, lower bounds of tertiles 2 and 3 were 0.20 and 1.46. In women, lower bounds of tertiles 2 and 3 were −0.09 and 1.41. Multivariate Cox proportional hazards models were adjusted for age (timescale in the Cox model), sex, number of 24-h dietary records, BMI, 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. CVD, cardiovascular disease; DII, Dietary Inflammatory Index; SU.VI.MAX, Supplémentation en Vitamines et Minéraux Antioxydants; T, tertile.
Sensitivity analyses have been carried out with a DII including PUFAs but excluding n–3 and n–6 fatty acids and with a DII including zinc intake. Similar results were observed. Both modified DIIs were positively associated with CVD + cancer mortality [P-trend = 0.02 (tertiles) and 0.04 (tertiles), respectively] and with cancer-specific mortality [P-trend = 0.01 (tertiles) for both]. The antioxidant supplementation of the SU.VI.MAX trial modified the association between both modified DII and all-cause mortality [P-interaction = 0.09 (tertiles) for both]: a positive association was observed in the placebo group [P-trend = 0.01 (tertiles) and 0.02 (tertiles), respectively] but not in the antioxidant-supplemented group [P-trend = 0.7 (tertiles) and 0.8 (tertiles), respectively] (data not tabulated).
DISCUSSION
For the first time in a large French cohort, this prospective study showed that a proinflammatory diet reflected by a higher DII score was associated with increased mortality (CVD + cancer and cancer-specific mortality). Because of its double-blind randomized placebo-controlled design, the SU.VI.MAX trial allowed us to investigate how this relation might be modulated by antioxidant supplementation. We found that a proinflammatory diet was positively associated with all-cause mortality in the placebo group of the trial only but not in the antioxidant-supplemented group.
The DII reflects the pro- and anti-inflammatory potential of an individual’s usual diet. Prior studies have shown the DII to be significantly and positively associated with several inflammatory biomarkers such as blood IL-6 (6, 8, 26, 43) and CRP (6, 24, 43) concentrations. In line with our findings, in a cohort of US women, the DII was associated with all-cause, cancer, and CVD mortality (30). In another cohort including Swedish women, the DII was associated with all-cause and digestive tract cancer mortality (31). To our knowledge, no other prospective study has previously tested for the association between the DII and mortality, and none had tested this relation in men. Our results are also consistent with epidemiologic studies that observed a direct relation between inflammatory biomarkers and mortality. The Emerging Risk Factors Collaboration team published a meta-analysis including 1.31 million person-years of observation from 54 long-term prospective studies and concluded that elevated CRP concentrations were positively associated with vascular mortality and mortality due to several cancers (2). After this meta-analysis, other studies also observed prospective associations between biomarkers of inflammation, such as CRP (3), IL-6 (3, 4), TNF-α receptor 1 (4), and chitinase 3–like protein 1 (5), and mortality.
Chronic diseases were responsible of 68% of deaths in the world in 2012 (44). Among them, CVD, cancer, diabetes, and chronic respiratory diseases were the 4 leading causes of death. Thus, our results also are consistent with prospective studies that have investigated the relations between the DII and the incidence of chronic diseases (14, 17, 19, 23, 25). Of these, one showed positive associations with lung cancer risk (17), 3 with colorectal cancer risk (19, 23, 25), and another with CVD risk (14). In addition, nonprospective case-control investigations found positive associations with colorectal (22, 27), prostate (20, 28), esophageal (13, 29), and pancreatic (21) cancers and asthma (26). However, no relation has been observed between the DII and breast cancer (16). In the SU.VI.MAX cohort, the DII was associated with increased risk of CVD (unpublished results, 2015) and some cancers (45).
The results of the present study also are in line with epidemiologic findings on the association between inflammatory biomarkers and chronic disease incidence. In their meta-analysis, Kaptoge et al. (2) showed that CRP concentration was associated with the risk of coronary heart disease, ischemic stroke, and lung disease. Gan et al. (46) found in a meta-analysis that chronic obstructive pulmonary disease risk was positively associated with several systemic inflammatory markers (circulating leukocytes, TNF-α, and fibrogen concentrations). As shown in meta-analyses (47, 48), epidemiologic studies reported positive associations between inflammatory biomarkers such as CRP or IL-6 and an increased risk of overall and lung cancer. In a previous prospective case-control study nested in the SU.VI.MAX cohort, we found that baseline plasma concentration of high-sensitivity CRP was associated with an increased risk of overall cancer and prostate cancer (49).
A prominent finding of this study is that a proinflammatory diet was associated with an increase in all-cause mortality in the placebo group of the SU.VI.MAX trial but not in the antioxidant-supplemented group. This result suggests that antioxidants may contribute to counteract some of the potentially deleterious effects of a proinflammatory diet. Mechanistic data from experimental studies support these observations. First, they show that inflammation figures in chronic disease etiology and mortality (1, 50). Second, they demonstrate the interrelation between inflammation and oxidative stress with respect to several chronic diseases (CVD and tumors) and metabolic dysregulation (diabetes and metabolic syndrome) (1, 32). Finally, long-term exposure to oxidative stress damages cellular and organ system structures and functions via pathways involving chronic inflammation (32).
Strengths of our study include its prospective design with long follow-up, the implementation of a literature-derived index to assess the overall inflammatory potential of the diet, and the randomized control trial design to test the potential modulatory effect of antioxidant supplementation at nutritional doses on the studied relation. Also, dietary intake was assessed by repeated 24-h dietary records (mean of 9.5 records per subject) accounting for intraindividual variability, including day-to-day and seasonal variations. Finally, a large range of confounding factors has been taken into account, thus limiting potential bias. Despite the study’s strengths, some limitations should be acknowledged. First, the limited number of deaths may have impaired our ability to detect some of the hypothesized associations. In particular, the limited number of cardiovascular deaths did not allow us to perform the analysis for this cause of death separately. This limited number of deaths is probably due to this study being performed on middle-aged adults (mean ± SD age at inclusion: 49.0 ± 6.3 y). Thus, caution is needed when extrapolating these results to an older population. Second, subjects were volunteers involved in a long-term nutrition study and thus were more health conscious than the general French population and, concomitantly, had potentially healthier behaviors. Also, the selection of participants who provided at least three 24-h dietary records increased the quality of dietary data but overrepresented compliant and healthy subjects (less obese, nonsmokers, better educated). In addition, although most of the 45 DII variables were taken into account (n = 36), some items (n = 9) were missing in our database and thus could not be included: caffeine, eugenol, saffron, selenium, turmeric, zinc, thyme/oregano, and rosemary (anti-inflammatory factors) and trans fatty acids (proinflammatory factor). However, it is unlikely that these missing variables have drastically influenced the results, because it has been shown that the ability of the DII to predict inflammation remained the same when the number of food variables was decreased from 45 to 28 (6). In addition, sensitivity analyses performed in this study (e.g., including the nonvalidated zinc information or including only PUFAs but not n–3 and n–6 fatty acids) showed very consistent and stable results.
To our knowledge, this study was the first to investigate the prospective association between the DII and mortality in a large population-based French cohort including both men and women. The randomized controlled design of the SU.VI.MAX trial allowed us to test the potential effect modification of the relation between the DII and mortality by antioxidant supplements. The results showed that a proinflammatory diet was associated with increased all-cause mortality in the placebo group but not in the antioxidant-supplemented group. Thus, in line with results from laboratory studies, our findings suggest that antioxidants may contribute to counteract some of the potential deleterious effects of a proinflammatory diet on mortality. These results provide interesting insights into the understanding of the relations between diet-related inflammation and mortality.
Acknowledgments
We thank Nathalie Arnault, statistician, for her technical contribution to the SU.VI.MAX study.
The authors’ responsibilities were as follows—LG and MT: designed the research; SH, PG, EK-G, and MT: conducted the research; NS, JRH, and MDW: designed and computed the DII score; LG: performed statistical analysis and wrote the manuscript; MT: supervised the study and had primary responsibility for final manuscript content; MD, FM, LN, NS, JRH, MDW, PL-M, SH, PG, CJ, EK-G, and MT: contributed to the data interpretation and revised each draft for important intellectual content; and all authors: read and approved the final manuscript. JRH owns controlling interest in Connecting Health Innovations LLC, a company planning to license the right to his invention of the DII from the University of South Carolina to develop computer and smartphone applications for patient counseling and dietary intervention in clinical settings. NS and MDW are employees of Connecting Health Innovations LLC. The other authors declared no conflicts of interest.
Footnotes
Abbreviations used: CRP, C-reactive protein; CVD, cardiovascular disease; DII, Dietary Inflammatory Index; SU.VI.MAX, Supplémentation en Vitamines et Minéraux Antioxydants.
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