Increased Dietary Inflammatory Index (DII) Is Associated With Increased Risk of Prostate Cancer in Jamaican Men (original) (raw)

Nutr Cancer. Author manuscript; available in PMC 2016 Aug 1.

Published in final edited form as:

PMCID: PMC4596719

NIHMSID: NIHMS718492

Nitin Shivappa

1Cancer Prevention and Control Program, University of South Carolina, Columbia, SC 29208, USA

2Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA

Maria D. Jackson

3Department of Community Health and Psychiatry, Faculty of Medical Sciences, University of West Indies, Kingston, Jamaica

Franklyn Bennett

4Department of Pathology, Faculty of Medical Sciences, University of West Indies, Kingston, Jamaica

James R. Hébert

1Cancer Prevention and Control Program, University of South Carolina, Columbia, SC 29208, USA

2Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA

5Department of Family and Preventive Medicine, University of South Carolina School of Medicine, Columbia, South Carolina, 29208, USA

1Cancer Prevention and Control Program, University of South Carolina, Columbia, SC 29208, USA

2Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA

3Department of Community Health and Psychiatry, Faculty of Medical Sciences, University of West Indies, Kingston, Jamaica

4Department of Pathology, Faculty of Medical Sciences, University of West Indies, Kingston, Jamaica

5Department of Family and Preventive Medicine, University of South Carolina School of Medicine, Columbia, South Carolina, 29208, USA

Address correspondence to Dr. James R. Hébert, Professor and Director, Cancer Prevention and Control Program, University of South Carolina, 915 Greene Street, Suite 241, Columbia, SC 29208. Phone: (803) 576-5666. Fax: (803) 576-5624. ude.cs@trebehj

Abstract

Purpose

Prostate cancer is the most common non-skin malignancy; and it accounts for the most cancer deaths among Jamaican males. Diet has been implicated in the etiology of prostate cancer, including through its effects on inflammation.

Method

We examined the association between a newly developed dietary inflammatory index (DII) and prostate cancer in a case-control study of 40-80 year-old Jamaican males. A total of 229 incident cases and 250 controls attended the same urology out-patient clinics at 2 major hospitals and private practitioners in the Kingston, Jamaica Metropolitan area between March 2005 and July 2007. The DII was computed based on dietary intake assessed using a previously validated food frequency questionnaire (FFQ) that was expanded to assess diet and cancer in this Jamaican population. Multivariable logistic regression was used to estimate odds ratios, with DII as continuous and expressed as quartiles. Logistic regression analysis adjusted for age, total energy intake, education, body mass index (BMI), smoking status, physical activity and family history of prostate cancer.

Results

Men in the highest quartile of the DII were at higher risk of prostate cancer [odds ratio (OR) = 2.39; 95% confidence interval (CI) =1.14–5.04 (Ptrend = 0.08)] compared to men in the lowest DII quartile.

Conclusion

These data suggest a pro-inflammatory diet, as indicated by increasing DII score, may be a risk factor for prostate cancer in Jamaican men.

Keywords: DII, diet, inflammation, prostate cancer, case-control design, Jamaica

Introduction

Prostate cancer is the leading non-skin cancer (age-standardized incidence rate = 78.1 per 100,000 per year) and the principal cause of cancer mortality among Jamaican males [1]. The Jamaican population is predominantly (91.6%) of African origin [2] and black men, compared to white and Asian men, have a higher incidence and mortality from the disease [3].

Chronic inflammation contributes to cancer development [4,5] and considerable evidence is accumulating on the role of chronic inflammation in prostate cancer [6-8]. While inflammation typically occurs as part of the body's response to tissue insult/injury [5,9] chronic inflammation is a persistent condition in which tissue destruction and repair occur simultaneously [10,11] and involves continuous recruitment of pro-inflammatory cytokines (associated with increased blood flow to the injured tissue, due to histamine released by damaged mast cells) [5].

Consistent with this chronic inflammation hypothesis, a case-control study showed that levels of CRP were higher in men with prostate cancer compared to those with benign prostatic hypertrophy [12]. Innate immunity and inflammation play a modest role in the development of prostate cancer [13] and in the Melbourne Collaborative Cohort Study higher levels of IL-6, a pro-inflammatory cytokine, was seen among malignant prostate cancer cases compared to those with benign disease [14].

Research into the role of diet-related inflammation and prostate cancer suggests that diet represents a complicated set of exposures that often interact, and whose cumulative effect modifies both inflammatory responses and health outcomes. A search of the literature using the National Library of Medicine, Medline® database, indicates that there are very few articles that include all four components on which we are focusing our attention; i.e. diet, inflammation, obesity, and cancer. The paucity of research is likely due to logistic issues resulting from limited funding and methodological complexity involved in linking diet, obesity, inflammation and cancers in the same study. In an effort to fill the obvious methodological, and related information, gap researchers at the University of South Carolina's Cancer Prevention and Control Program developed the Dietary Inflammatory Index (DII), which can be used in diverse populations in order to predict levels of inflammatory markers and related health outcomes [15,16]. The DII is based on reviewing and scoring the scientific literature on diet and inflammation, and obtaining nutritional surveillance data sets from around the world to which individuals' dietary intakes could be compared. A higher DII score indicates a pro-inflammatory dietary milieu and a lower DII score indicates that diet is more anti-inflammatory [15]. In a case-control study conducted among Italian men, higher DII score was associated with increased risk of prostate cancer [17]. Thus far, the DII has been found to be associated with C-reactive protein [16,18], interleukin-6 [19-21], and homocysteine [19]. Additionally, DII has been shown to be associated with glucose intolerance and dyslipidemia components of the metabolic syndrome [22,23], anthropometric measurements in Spain [24], asthma in Australia [25] respiratory conditions in Italy [26], bone mineral density among postmenopausal women in Iran [21], colorectal cancer in two case-control studies in Spain and Italy [27,28] and three cohort studies in the USA [29-31], and pancreatic cancer in an Italian case-control study [32]. The purpose of this study is to examine the association between the DII and prostate cancer in a case-control study of 40-80 year-old Jamaican men. Our working hypothesis is that higher DII scores (indicating pro-inflammatory diet) increases risk of prostate cancer. Previous research in this case-control study has revealed a strong positive association between a carbohydrate- rich dietary pattern and prostate cancer [33], which would be broadly consistent with this hypothesis.

Methods

Full details regarding the case-control design have been published elsewhere [33]. In brief, cases and controls were men attending urology clinics at the two main tertiary hospitals and private practitioners in the Kingston Metropolitan area in Jamaica. Data were collected between March 2005 and July 2007. Cases were men 40 to 80 years old, with newly diagnosed, and histologically confirmed prostate cancer. Controls were men with a normal digital rectal examination and total prostate specific antigen (PSA) < 4.0 _μ_g /L or total free PSA > 0.15.

Dietary intakes were assessed using a validated semi-quantitative food frequency questionnaire designed to assess diet and cancer in the Jamaican population [34]. Data were collected on the frequency of consumption for each food item, as well as the amount of food consumed using food models, commonly used household utensils, measuring cups, and a measuring tape. The FFQ was interviewer-administered. FFQ-derived dietary data were used to calculate DII scores for all participants. The DII is based on literature published through 2010 linking diet to inflammation. Individuals' intakes of food parameters on which the DII is based are then compared to a world standard database. A complete description of the DII is available elsewhere [15]. A description of validation work, including both dietary recalls and a structured questionnaire similar to an FFQ, is also available [16]. Briefly, to calculate DII for the participants of this study, the dietary data were first linked to the regionally representative world database that provided a robust estimate of a mean and standard deviation for each parameter. These then become the multipliers to express an individual's exposure relative to the “standard global mean” as a z-score. This is achieved by subtracting the “standard global mean” from the amount reported and dividing this value by the standard deviation. To minimize the effect of “right skewing” (a common occurrence with dietary data), this value is then converted to a centered percentile score. The centered percentile score for each food parameter for each individual was then multiplied by the respective food parameter effect score, which is derived from the literature review, in order to obtain a food parameter-specific DII score for an individual. All of the food parameter-specific DII scores are then summed to create the overall DII score for every participant in the study [15]. A total of 21 food parameters were available from the FFQ and therefore could be used to calculate DII (energy, carbohydrate, protein, total fat, alcohol, fiber, cholesterol, saturated fat, mono-unsaturated fat, poly unsaturated fat, omega-3, omega-6, vitamin B12, iron, zinc, vitamin A, vitamin C, vitamin D, vitamin E, folic acid, beta carotene.)

The DII was analyzed both as a continuous variable and categorized by quartiles of exposure. DII (as quartiles) was examined across the following characteristics: age, education, physical activity level, body mass index (BMI), smoking and family history of prostate cancer, food groups and nutrients using _ANOVA_-test or χ2 test for continuous and categorical variables, respectively. BMI was calculated and the World Health Organization's classification of BMI was used to determine overweight (BMI 25.0 kg/m2- 29.9 kg/m2) and obesity (BMI ≥ 30.0 kg/m2) [35]. Odds ratio and 95% confidence intervals (OR; 95% CI) were estimated using multivariable logistic regression models, adjusting only for age in the crude model and then fitting a model with additional adjustment for BMI, smoking status, physical activity, family history of prostate cancer, education and total energy intake. The covariates were chosen a priori as they were shown to be risk factors for prostate cancer. Tests for trend were carried out by calculating the median values for each of the quartiles of DII and including the median value in the model. Statistical tests were performed using SAS® 9.3 (SAS Institute Inc., Cary, NC); all p values were based on two-sided tests.

Results

A summary of the characteristics of prostate cancer cases and controls is presented in Table 1. Compared with controls, cases were older and less likely to report secondary or higher education and more likely to be physically active. A similar proportion of cases and controls were current smokers (cases, 14.8%; controls, 15.9%). Examination of anthropometric characteristics showed that, with the exception of cases being significantly shorter (cases, 169.5 ± 6.6 cm; controls, 171.6 ± 7.1 cm), both groups were similar on other factors including weight, BMI, waist and hip circumference and waist–hip ratio.

Table 1

Characteristics of prostate cancer cases and controls, Jamaican Prostate Case-Control Study, 2005-7

Characteristics Cases Controls
N =229 N =250
Age, (years): mean ± sd 67.8 ± 7.8 a 62.0 ± 10.5
Waist, cm: mean ± sd 88.6 ± 11.8 88.1 ± 12.5
Hip circumference, cm: mean ± sd 97.8±8.5 98.7±10.0
Weight, kg: mean ± sd 72.3 ± 14.1 74.4 ± 14.5
Height, cm: mean ± sd 169.5 ± 6.6 a 171.6 ± 7.1
Waist-to-Hip Ratio: mean ± sd 0.90±0.08 0.89±0.08
BMI, kg/m2: mean ± sd 25.1 ± 4.4 25.2 ± 4.6
Categorical variables:
Education (%)
Primary or less 90.4 a 80.5
Secondary 5.7 13.9
Tertiary (i.e., Post-Secondary) 3.9 5.6
Physical activity (%)
Inactive 18.7 a 20.3
Moderately inactive 20.9 28.7
Moderately active 39.6 41.0
Active 20.8 10.0
Smoking (%)
Nonsmoker 21.3 24.7
Ex-smoker 63.9 59.4
Current smoker 14.8 15.9
Overweight (%) 33.0 36.6
Obese (%) 12.6 13.1

Following exclusions due to missing information, the final analytic sample consisted of 479 men (229 cases and 250 controls) and had a mean DII value of -1.05 (SD= ±1.11). Participant characteristics by quartiles of DII are provided in Table 2. There were few differences in sociodemographic and health behavior characteristics by DII quartiles. Men in quartile 3 were less likely to have completed post-secondary education, more likely to be current smokers, less likely to be obese, more likely to be younger and less active, and to have higher CRP levels. Men in the highest quartile of DII scores had higher rate of obesity (24.6% for quartile 4 vs.23.1% for quartile 1). Table 3 shows the distribution of food groups across quartiles of DII. Men in quartile 4 had lower seafood, total fruit, total vegetables, and whole grains consumption compared to men in quartile 1. The food groups that showed the greatest reduction (≥10%) from quartile 1 to quartile 4 were total fruits (82%), fruit juice (68%), cereals (62%), beans and legumes (57%), starches (47%), dairy (43%), seafood (37%), whole grains (33%), eggs (23%) and poultry (12%). The food groups that showed greatest increase (≥ 10%) were red meat (10%), rice and pasta (16%), total meat (47%). The nutrients which showed the greatest reduction across DII quartiles were zinc (95%), linoleic acid (86%), vitamin B12 (76%) and folate (74%).

Table 2

Participant characteristics across quartiles of dietary inflammatory index (DII), Jamaican Prostate case-control study, 2005-7

Characteristics Quartile 1 Quartile 2 Quartile 3 Quartile 4
Age (years): mean ± sd 65.03±9.7 65.09±8.9 63.39±10.9 65.13±9.7
Body mass Index (kg/m2): mean ± sd 24.87±4.5 25.08±4.4 25.55±4.6 25.44±4.6
Overweight (% 25<BMI≤30 kg/m2) 28.3 22.5 27.8 21.4
Obese (% BMI>30 kg/m2) 23.1 29.2 23.1 24.6
C-Reactive Protein (mg/l): mean ± sd 2.62±2.2 2.93±2.7 3.39±4.6 3.00±2.7
Physical activity (%):
Inactive 23.0 29.0 24.0 24.0
Moderately inactive 20.8 24.8 27.2 27.2
Moderately active 29.7 25.2 28.2 16.8
Active 30.7 25.3 18.7 25.3
Smoking (%)
Non-smoker 25.0 29.3 27.6 18.1
Ex-smoker 26.7 23.8 24.4 25.1
Current smoker 25.3 26.7 30.7 17.3
Education (%)
Primary 113 (85.6) 113 (88.3) 109 (84.5) 91 (82.7)
Secondary 12 (9.1) 10 (7.8) 17 (13.2) 10 (9.1)
Tertiary 7 (5.3) 5 (3.9) 3 (2.3) 9 (8.2)

Table 3

Distribution of food groups intake across quartiles of DII, Jamaican Prostate case-control study, 2005-7

Food groups g/week (mean ± SD) % Change (Quartile 1-4)* Quartile 1 Quartile 2 Quartile 3 Quartile 4
Total fruits -82 1059.9±592.4 986.6±550.4 614±456.8 187.7±153.6
Fruit juice -68 242.5±233.0 259.4±248.1 221.0±262.4 76.9±95.0
Cereals -62 4.2±9.6 3.9±10.0 3.0±8.2 1.6±5.8
Total vegetables -60 554.1±372.6 541±412.3 411.7±340.2 222.1±215.7
Beans and legumes -57 132.1±144.5 125.5±137.9 92.9±77.2 56.9±65.5
Starches -47 318.9±151.7 287.7±198.8 265.1±165.6 169.2±110.6
Dairy -43 76.6±119.1 70.8±104.9 52.6±86.7 44.0±86.1
Seafood -37 70.2±44.6 64.4±48.1 46.6±39.0 44.2±42.7
Whole grains -33 109.6±116.3 153.6±199.3 93.7±146.2 73.5±125.4
Eggs -23 14.0±15.4 12.5±15.9 13.8±16.4 10.7±15.0
Poultry -12 70.1±55.9 75.5±53.6 74.9±50.6 61.9±55.7
Sugary foods -4 15.7±17.1 16.5±19.1 15.4±16.6 15.1±23.0
Non diet (i.e., sugar-sweetened) soft drinks +1 211.5±239.8 208.6±281.8 193.5±231.5 213.2±268.9
Red Meat +10 19.6±26.2 23.2±27.9 17.5±21.0 21.5±25.4
Rice and pasta +16 244.4±181.6 237.4±190.3 308.1±224.0 284.4±209.0
Total meat +47 12.9±21.1 18.5±29.5 19.8±27.2 19.0±25.9
Nutrients (units/d)
Energy (kcal/day) -38 3825.0±1426.8 3553.5±992.3 3066.3±902.3 2373.7±1005.6
Carbohydrates (g/day) -43 684.7±270.2 627.8±200.2 523.8±170.8 389.6±182.5
Proteins (g/day) -33 140.8±62.0 131.4±48.8 116.3±45.0 93.7±40.2
Fat (g/day) -30 90.6±41.9 90.0±32.5 79.3±28.9 63.5±29.9
Linoleic acid (g/d) -86 11.8±14.2 8.6±9.3 5.4±5.0 1.6±2.8
Vitamin B12 (ug/d) -76 22.9±16.3 19.6±14.5 14.0±12.1 5.5±8.6
Zinc (mg/d) -95 162.1±428.2 139.9±358.2 54.1±119.6 8.7±19.4
Folate (ug/d) -74 963.9±357.6 848.5±285.9 789.3±279.9 248.6±291.5

Odds ratios (OR) and 95% confidence intervals (CI) for the risk of prostate cancer according to quartiles of DII are shown in Table 4. Results obtained from modeling DII as a continuous variable in relation to risk of prostate cancer suggested a positive association after adjustment for covariates in analysis (OR=1.27 CI=0.98-1.50). When analysis was carried out with DII expressed as quartiles, and adjusting for age, no significant association was observed; although results were in the expected direction, with men in the highest quartile of DII having an apparent elevation in risk of total prostate cancer (OR = 1.27;CI = 0.73–2.19). However, in the model adjusting for family history of prostate cancer, education, BMI, smoking, physical activity and total energy intake men in the highest quartile of DII had increased odds for prostate cancer (quartile 4: OR=2.39; CI=1.14-5.04; Ptrend=0.08).

Table 4

Odds ratios and confidence intervals for quartiles of DII associated with total prostate cancer, Jamaican Prostate case-control study, 2005-7

Quartiles of Dietary Inflammatory Index OR (95% CI) P_trend_ DII (Continuous) OR (95% CI)
1 2 3 4
DII ≤-1.96 -1.97 to -1.42 -1.43 to -0.96 ≥-0.97
Cases / controls 65/67 64/68 50/82 64/55
Age-adjusted 1 (ref.) 0.85 (0.51, 1.42) 0.65 (0.38, 1.09) 1.27 (0.73, 2.19) 0.48 1.07 (0.90, 1.26)
Multivariate-adjusted a 1 (ref.) 0.96 (0.56, 1.66) 0.80 (0.46, 1.40) 2.39 (1.14, 5.04) 0.08 1.27 (0.98, 1.50)

Discussion

In this case-control study of Jamaican males aged 40-80 years, consuming a more pro-inflammatory diet, as reflected in higher DII scores, was associated with increased risk of prostate cancer. We found no association between DII and CRP, although there was a suggestion of a positive association. Our data showed that men with a high DII score had higher intakes of pro-inflammatory foods, including total meat, and red meat in particular. They also reported lower consumption of anti-inflammatory food groups such as fruits, fruit juice, vegetables, whole grains and sea food. Men in quartile 4 were observed to consume less food in general, and to report consuming foods that tend to be pro-inflammatory, such as sugar-sweetened soft drinks, and red meat. Men in quartile 4 also consumed very low amount of key nutrients such as zinc and folate, which have been shown to have a protective role in prostate carcinogenesis [36,37]. This result is consistent with what we have found in other developing country populations where higher-income, more educated individuals tend to be more likely to eat a westernized diet that is lower in anti-inflammatory foods and richer in pro-inflammatory foods than traditional fare [38,39]. However, it also must be kept in mind that comparatively few men in this study reported higher education.

The DII is different from other dietary indices, virtually all of which fall into three main categories: 1. Those derived from specific dietary prescriptions based on some external standard [e.g., Healthy Eating Index] [40,41], which was derived from adherence to the US Dietary guidelines [42]; 2. Those derived from findings within particular study populations (e.g., computing a pattern using principal component analysis [33]) or 3. Those that link to particular cultural patterns of dietary intake (e.g., the Mediterranean diet [43]). Previously, studies have been conducted to examine various dietary patterns and such indices and their association with prostate cancer in men [33,44]. In this Jamaican case-control study, analyses were conducted looking at dietary patterns and prostate cancer risk and it was observed that refined carbohydrate intake was associated with increased prostate cancer risk [33]. In a study conducted on the NIH-AARP study, authors tested the Healthy Eating Index-2005 (HEI-2005), Alternate Healthy Eating Index-2010 (AHEI-2010), and alternate Mediterranean diet score (aMED) in relation to prostate cancer risk and observed significant inverse associations between HEI-2005 and AHEI-2010 and prostate cancer risk [44]. Typically, the healthiest consumers within each of these patterns demonstrate a style of eating which most individuals would recognize as “nutritious.” For example, someone eating in a manner consistent with the Mediterranean Diet prescription would consume a diet high in whole-grain foods, fruit and vegetables, and fish; and it would be low in red meat and butter, with moderate alcohol and olive oil intake. The upshot of the research done on diet and inflammation over the past 50 years is that while common themes may indeed be present, the results are inconsistent. To summarize, while a general prescription has existed for some time, all of the research from the past half-century has not moved us much closer to understanding the exact relationship between diet, inflammation, and cancer-related health outcomes. Also, the general prescription has not generally led to meaningful changes on a population level – either generally, or with respect to targeted recommendations to prevent specific diseases such as prostate cancer [45,46].

The focus on individual nutrients is appealing for its simplicity. However, an important impediment to this approach is that nutrients are virtually never consumed alone. Because of the behavioral and metabolic relationships across food constituents, a nutrient effect is rarely, if ever, independent of the effect of other nutrients in the diet. Another issue is the high correlation between nutrients within human diets [4749], with a resulting loss of ability to provide robust unbiased estimates of effect due to multicollinearity [50]. By contrast, the whole foods approach does account for complexity of nutrient interactions within foods. However, as with individual nutrients, it does not address the issue of inter-correlation among foods within a diet.

This positive association of the DII with prostate cancer in this case-control study is very encouraging. One of the possible mechanisms for this association would be through the effect of pro inflammatory diet on insulin resistance by increasing systemic inflammation [51,52]. Consumption of food items such as meat and butter have been shown to increase systemic inflammation by increasing levels of high-sensitivity C-reactive protein, E-selectin and soluble vascular cell adhesion molecule-1 [51], which is responsible for increasing insulin resistance [52]. Increasing insulin resistance leads to increased circulating levels of insulin, which has been demonstrated to play a role in the development of prostate cancer by inhibiting apoptosis and stimulating cell proliferation [53]. It also influences the insulin-like growth factor (IGF) axis, resulting in alterations in sex hormone metabolism, and this is consistent with previous results from this study showing increased carbohydrate intake to be associated with prostate cancer risk and provides further support for this theory [33]. According to another theory, a diet rich in pro-inflammatory food parameters such as saturated fat causes proliferation, inflammation, and oxidative stress that can lead to benign prostatic hyperplasia, prostatitis, and cancer of the prostate [54]. Similarly, diets rich in anti-inflammatory food parameters, such as green tea, have been shown to decrease reactive oxygen species production leading to induction of apoptosis. Additionally, green tea has the ability to specifically target prostate cancer cells and kill them without affecting the growth of normal cells [55].

The influence of diet on cancer is difficult to measure precisely, and challenges in dietary exposure assessment are greatest in case-control studies. We used incident cases interviewed before they were made aware of their disease status; and in this manner avoided disease-associated information and interviewer-related bias. This approach strengthened the validity of the results by reducing recall bias; however, the temporal ordering among the relationships observed still cannot be determined. Notwithstanding the limitations of case-control studies in general, we believe that our findings of a positive association between the DII and prostate cancer are plausible and could point to a link to immune and hormonal factors [54,55,53].

The observed association between DII and prostate cancer was independent of socioeconomic status and other lifestyle characteristics. Obesity is known to be associated with inflammation; however, in this study we observed only a small difference in rates of obesity between quartile 4 and quartile 1 (24.6 % in quartile 4 vs 23.1 % in quartile 1). This may explain differences between socioeconomic status-associated patterns of obesity in Jamaica versus other places that have generally higher rates of both obesity and prostate cancer, such as the US.

A major debate has raged concerning the tension between over-treating indolent prostate cancers and under-treating virulent prostate cancers [56-58]. Indeed this forms the basis of the 2008 United States Preventive Services Task Force recommendation to avoid population-based screening [59,60]. Although this is less of a problem than it would be in a heavily screened population, there is some concern with not being able to distinguish indolent cancers from others. Future studies are needed to gain insight into the relationship between DII and the risk of prostate cancer aggressiveness; this would deepen understanding about the role of diet in determining extent and virulence of prostate cancer. The results from the current study are restricted to men, so using DII in studies with women would help to discern the generalizability of DII across genders.

Acknowledgments

Funding: This work was supported by the National Health Fund (HSF19), CHASE Fund, and the Planning Institute of Jamaica (77/854). Dr. Hébert was supported by an Established Investigator Award in Cancer Prevention and Control from the Cancer Training Branch of the National Cancer Institute (K05 CA136975).

Footnotes

Conflict of interest: All authors declare no conflict of interest

References

1. Gibson TN, Hanchard B, Waugh N, McNaughton D. Age-specific incidence of cancer in Kingston and St. Andrew, Jamaica, 2003-2007. West Indian Med J. 2010;59(5):456–464. [PubMed] [Google Scholar]

2. Statistical Institute of Jamaica. Population Census 2001: Jamaica 2003. Statistical Institute of Jamaica; 2009. [Google Scholar]

3. Greenlee RT, Murray T, Bolden S, Wingo PA. Cancer statistics, 2000. CA Cancer J Clin. 2000;50(1):7–33. [PubMed] [Google Scholar]

4. Touvier M, Fezeu L, Ahluwalia N, Julia C, Charnaux N, Sutton A, Mejean C, Latino-Martel P, Hercberg S, Galan P, Czernichow S. Association between prediagnostic biomarkers of inflammation and endothelial function and cancer risk: a nested case-control study. Am J Epidemiol. 2013;177(1):3–13. doi:kws359 [pii] 10.1093/aje/kws359 [doi] [PMC free article] [PubMed] [Google Scholar]

5. Keibel A, Singh V, Sharma MC. Inflammation, microenvironment, and the immune system in cancer progression. Curr Pharm Des. 2009;15(17):1949–1955. [PubMed] [Google Scholar]

6. Kopp TI, Friis S, Christensen J, Tjonneland A, Vogel U. Polymorphisms in genes related to inflammation, NSAID use, and the risk of prostate cancer among Danish men. Cancer Genet. 2013;20(13):00084–00087. [PubMed] [Google Scholar]

7. Cross AJ, Peters U, Kirsh VA, Andriole GL, Reding D, Hayes RB, Sinha R. A prospective study of meat and meat mutagens and prostate cancer risk. Cancer Res. 2005;65(24):11779–11784. [PubMed] [Google Scholar]

8. Nakai Y, Nonomura N. Inflammation and prostate carcinogenesis. Int J Urol. 2013;20(2):150–160. [PubMed] [Google Scholar]

9. Pan MH, Lai CS, Dushenkov S, Ho CT. Modulation of inflammatory genes by natural dietary bioactive compounds. J Agric Food Chem. 2009;57(11):4467–4477. [PubMed] [Google Scholar]

11. Philip M, Rowley DA, Schreiber H. Inflammation as a tumor promoter in cancer induction. Semin Cancer Biol. 2004;14(6):433–439. [PubMed] [Google Scholar]

12. Kim Y, Jeon Y, Lee H, Lee D, Shim B. The Prostate Cancer Patient Had Higher C-Reactive Protein Than BPH Patient. Korean J Urol. 2013;54(2):85–88. [PMC free article] [PubMed] [Google Scholar]

13. Kazma R, Mefford JA, Cheng I, Plummer SJ, Levin AM, Rybicki BA, Casey G, Witte JS. Association of the innate immunity and inflammation pathway with advanced prostate cancer risk. PLoS ONE. 2012;7(12):e51680. doi:10.1371/journal.pone.0051680 [doi] PONE-D-12-23873 [pii] [PMC free article] [PubMed] [Google Scholar]

14. Tindall EA, Severi G, Hoang HN, Southey MC, English DR, Hopper JL, Giles GG, Hayes VM. Interleukin-6 promoter variants, prostate cancer risk, and survival. Prostate. 2012;72(16):1701–1707. doi:10.1002/pros.22557 [doi] [PubMed] [Google Scholar]

15. Shivappa N, Steck SE, Hurley TG, Hussey JR, Hebert JR. Designing and developing a literature-derived, population-based dietary inflammatory index. Public health nutrition. 2014;17(8):1689–1696. doi: 10.1017/S1368980013002115. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

16. Shivappa N, Steck SE, Hurley TG, Hussey JR, Ma Y, Ockene IS, Tabung F, Hebert JR. A population-based dietary inflammatory index predicts levels of C-reactive protein in the Seasonal Variation of Blood Cholesterol Study (SEASONS) Public health nutrition. 2014;17(8):1825–1833. doi: 10.1017/S1368980013002565. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

17. Shivappa N, Bosetti C, Zucchetto A, Montella M, Serraino D, La Vecchia C, Hebert JR. Association between dietary inflammatory index and prostate cancer among Italian men. The British journal of nutrition. 2014:1–6. doi: 10.1017/S0007114514003572. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

18. Wirth MD, Burch J, Shivappa N, Violanti JM, Burchfiel CM, Fekedulegn D, Andrew ME, Hartley TA, Miller DB, Mnatsakanova A, Charles LE, Steck SE, Hurley TG, Vena JE, Hebert JR. Association of a dietary inflammatory index with inflammatory indices and metabolic syndrome among police officers. Journal of occupational and environmental medicine / American College of Occupational and Environmental Medicine. 2014;56(9):986–989. doi: 10.1097/JOM.0000000000000213. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

19. Shivappa N, Hebert JR, Rietzschel ER, De Buyzere ML, Langlois M, Debruyne E, Marcos A, Huybrechts I. Associations between dietary inflammatory index and inflammatory markers in the Asklepios Study. The British journal of nutrition. 2015;113(4):665–671. doi: 10.1017/S000711451400395X. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

20. Tabung FK, Steck SE, Zhang J, Ma Y, Liese AD, Agalliu I, Hingle M, Hou L, Hurley TG, Jiao L, Martin LW, Millen AE, Park HL, Rosal MC, Shikany JM, Shivappa N, Ockene JK, Hebert JR. Construct Validation of the Dietary Inflammatory Index among Postmenopausal Women. Annals of Epidemiology. (0) doi: http://dx.doi.org/10.1016/j.annepidem.2015.03.009. [PMC free article] [PubMed]

21. Wood LG, Shivappa N, Berthon BS, Gibson PG, Hebert JR. Dietary inflammatory index is related to asthma risk, lung function and systemic inflammation in asthma. Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology. 2015;45(1):177–183. doi: 10.1111/cea.12323. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

22. Alkerwi Aa, Shivappa N, Crichton G, Hébert JR. No significant independent relationships with cardiometabolic biomarkers were detected in the Observation of Cardiovascular Risk Factors in Luxembourg study population. Nutrition Research. (0) doi: http://dx.doi.org/10.1016/j.nutres.2014.07.017. [PMC free article] [PubMed]

23. Wirth MD, Burch J, Shivappa N, Violanti JM, Burchfiel CM, Fekedulegn D, Andrew ME, Hartley TA, Miller DB, Mnatsakanova A, Charles LE, Steck SE, Hurley TG, Vena JE, Hebert JR. Association of a dietary inflammatory index with inflammatory indices and metabolic syndrome among police officers. J Occup Environ Med. 2014;56(9):986–989. [PMC free article] [PubMed] [Google Scholar]

24. Ruiz-Canela M, Zazpe I, Shivappa N, Hebert JR, Sanchez-Tainta A, Corella D, Salas-Salvado J, Fito M, Lamuela-Raventos RM, Rekondo J, Fernandez-Crehuet J, Fiol M, Santos-Lozano JM, Serra-Majem L, Pinto X, Martinez JA, Ros E, Estruch R, Martinez-Gonzalez MA. Dietary inflammatory index and anthropometric measures of obesity in a population sample at high cardiovascular risk from the PREDIMED (PREvencion con DIeta MEDiterranea) trial. The British journal of nutrition. 2015:1–12. doi: 10.1017/S0007114514004401. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

25. Wood L, Shivappa N, Berthon BS, Gibson PG, Hebert JR. Dietary inflammatory index is related to asthma risk, lung function and systemic inflammation in asthma. Clinical & Experimental Allergy. 2014:n/a–n/a. doi: 10.1111/cea.12323. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

26. Maisonneuve P, Shivappa N, Hébert J, Bellomi M, Rampinelli C, Bertolotti R, Spaggiari L, Palli D, Veronesi G, Gnagnarella P. Dietary inflammatory index and risk of lung cancer and other respiratory conditions among heavy smokers in the COSMOS screening study. European journal of nutrition. 2015:1–11. doi: 10.1007/s00394-015-0920-3. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

27. Zamora-Ros R, Shivappa N, Steck SE, Canzian F, Landi S, Alonso MH, Hebert JR, Moreno V. Dietary inflammatory index and inflammatory gene interactions in relation to colorectal cancer risk in the Bellvitge colorectal cancer case-control study. Genes & nutrition. 2015;10(1):447. doi: 10.1007/s12263-014-0447-x. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

28. Shivappa N, Zucchetto A, Montella M, Serraino D, Steck SE, La Vecchia C, Hebert JR. Inflammatory potential of diet and risk of colorectal cancer in a case-control study from Italy. The British journal of nutrition. 2015 Accepted. [PubMed] [Google Scholar]

29. Shivappa N, Prizment AE, Blair CK, Jacobs DR, Jr, Steck SE, Hebert JR. Dietary inflammatory index and risk of colorectal cancer in the Iowa Women's Health Study. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. 2014;23(11):2383–2392. doi: 10.1158/1055-9965.EPI-14-0537. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

30. Tabung FK, Steck SE, Ma Y, Liese AD, Zhang J, Caan B, Hou L, Johnson KC, Mossavar-Rahmani Y, Shivappa N, Wactawski-Wende J, Ockene JK, Hebert JR. The association between dietary inflammatory index and risk of colorectal cancer among postmenopausal women: results from the Women's Health Initiative. Cancer causes & control : CCC. 2015;26(3):399–408. doi: 10.1007/s10552-014-0515-y. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

31. Wirth MD, Shivappa N, Steck SE, Hurley TG, Hébert JR. British Journal of Nutrition FirstView. 2015. The dietary inflammatory index is associated with colorectal cancer in the National Institutes of Health–American Association of Retired Persons Diet and Health Study; pp. 1–9. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

32. Shivappa N, Bosetti C, Zucchetto A, Serraino D, La Vecchia C, Hebert JR. Dietary inflammatory index and risk of pancreatic cancer in an Italian case-control study. The British journal of nutrition. 2014:1–7. doi: 10.1017/S0007114514003626. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

33. Jackson M, Tulloch-Reid M, Walker S, McFarlane-Anderson N, Bennett F, Francis D, Coard K. Dietary patterns as predictors of prostate cancer in Jamaican men. Nutr Cancer. 2013;65(3):367–374. [PubMed] [Google Scholar]

34. Jackson MD, Walker SP, Younger NM, Bennett FI. Use of a food frequency questionnaire to assess diets of Jamaican adults: validation and correlation with biomarkers. Nutr J. 2011;10(28):28. [PMC free article] [PubMed] [Google Scholar]

35. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser. 2000;894:i–xii. 1–253. [PubMed] [Google Scholar]

36. Costello LC, Feng P, Milon B, Tan M, Franklin RB. Role of zinc in the pathogenesis and treatment of prostate cancer: critical issues to resolve. Prostate cancer and prostatic diseases. 2004;7(2):111–117. doi: 10.1038/sj.pcan.4500712. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

37. Pelucchi C, Galeone C, Talamini R, Negri E, Parpinel M, Franceschi S, Montella M, La Vecchia C. Dietary folate and risk of prostate cancer in Italy. Cancer Epidemiol Biomarkers Prev. 2005;14(4):944–948. doi: 10.1158/1055-9965.EPI-04-0787. [PubMed] [CrossRef] [Google Scholar]

38. Hebert JR, Hurley TG, Steck SE, Miller DR, Tabung FK, Peterson KE, Kushi LH, Frongillo EA. Considering the value of dietary assessment data in informing nutrition-related health policy. Adv Nutr. 2014;5(4):447–455. doi:5/4/447 [pii] 10.3945/an.114.006189. [PMC free article] [PubMed] [Google Scholar]

39. Hebert JR. Epidemiologic studies of diet and cancer: The case for international collaboration. Austro-Asian J Cancer. 2005;4:125–134. [Google Scholar]

40. O'Neil CE, Nicklas TA, Zanovec M, Cho SS, Kleinman R. Consumption of whole grains is associated with improved diet quality and nutrient intake in children and adolescents: the National Health and Nutrition Examination Survey 1999-2004. Public Health Nutr. 2011;14(2):347–355. [PubMed] [Google Scholar]

41. Heroux M, Janssen I, Lam M, Lee DC, Hebert JR, Sui X, Blair SN. Dietary patterns and the risk of mortality: impact of cardiorespiratory fitness. Int J Epidemiol. 2010;39(1):197–209. [PMC free article] [PubMed] [Google Scholar]

42. Kennedy ET, Ohls J, Carlson S, Fleming K. The Healthy Eating Index: design and applications. J Am Diet Assoc. 1995;95(10):1103–1108. [PubMed] [Google Scholar]

43. Sjogren P, Becker W, Warensjo E, Olsson E, Byberg L, Gustafsson IB, Karlstrom B, Cederholm T. Mediterranean and carbohydrate-restricted diets and mortality among elderly men: a cohort study in Sweden. Am J Clin Nutr. 2010;92(4):967–974. doi:ajcn.2010.29345 [pii] 10.3945/ajcn.2010.29345. [PubMed] [Google Scholar]

44. Bosire C, Stampfer MJ, Subar AF, Park Y, Kirkpatrick SI, Chiuve SE, Hollenbeck AR, Reedy J. Index-based dietary patterns and the risk of prostate cancer in the NIH-AARP diet and health study. Am J Epidemiol. 2013;177(6):504–513. [PMC free article] [PubMed] [Google Scholar]

45. Kushi LH, Byers T, Doyle C, Bandera EV, McCullough M, McTiernan A, Gansler T, Andrews KS, Thun MJ. American Cancer Society Guidelines on Nutrition and Physical Activity for cancer prevention: reducing the risk of cancer with healthy food choices and physical activity. CA Cancer J Clin. 2006;56(5):254–281. quiz 313-254. doi:56/5/254 [pii] [PubMed] [Google Scholar]

46. Robien K, Ness KK, Klesges LM, Baker KS, Gurney JG. Poor adherence to dietary guidelines among adult survivors of childhood acute lymphoblastic leukemia. J Pediatr Hematol Oncol. 2008;30(11):815–822. doi:10.1097/MPH.0b013e31817e4ad9 [doi] 00043426-200811000-00006 [pii] [PMC free article] [PubMed] [Google Scholar]

47. Smith AF, Domel Baxter S, Hardin JW, Nichols MD. Conventional analyses of data from dietary validation studies may misestimate reporting accuracy: illustration from a study of the effect of interview modality on children's reporting accuracy. Public Health Nutr. 2007;10(11):1247–1256. [PMC free article] [PubMed] [Google Scholar]

48. Palli D, Masala G, Vineis P, Garte S, Saieva C, Krogh V, Panico S, Tumino R, Munnia A, Riboli E, Peluso M. Biomarkers of dietary intake of micronutrients modulate DNA adduct levels in healthy adults. Carcinogenesis. 2003;24(4):739–746. [PubMed] [Google Scholar]

49. Hebert JR, Gupta PC, Bhonsle RB, Sinor PN, Mehta H, Mehta FS. Development and testing of a quantitative food frequency questionnaire for use in Gujarat, India. Public Health Nutr. 1999;2(1):39–50. [PubMed] [Google Scholar]

50. Fraser GE. A search for truth in dietary epidemiology. Am J Clin Nutr. 2003;78(3 Suppl):521S–525S. [PubMed] [Google Scholar]

51. Esmaillzadeh A, Kimiagar M, Mehrabi Y, Azadbakht L, Hu FB, Willett WC. Dietary Patterns and Markers of Systemic Inflammation among Iranian Women. The Journal of Nutrition. 2007;137(4):992–998. [PubMed] [Google Scholar]

52. Festa A, D'Agostino R, Howard G, Mykkänen L, Tracy RP, Haffner SM. Chronic Subclinical Inflammation as Part of the Insulin Resistance Syndrome: The Insulin Resistance Atherosclerosis Study (IRAS) Circulation. 2000;102(1):42–47. doi: 10.1161/01.cir.102.1.42. [PubMed] [CrossRef] [Google Scholar]

53. Kaaks R, Lukanova A. Energy balance and cancer: the role of insulin and insulin-like growth factor-I. Proc Nutr Soc. 2001;60(1):91–106. [PubMed] [Google Scholar]

54. Vykhovanets EV, Shankar E, Vykhovanets OV, Shukla S, Gupta S. High-fat diet increases NF-kappaB signaling in the prostate of reporter mice. Prostate. 2011;71(2):147–156. [PMC free article] [PubMed] [Google Scholar]

55. Pandey M, Gupta S. Green tea and prostate cancer: from bench to clinic. Front Biosci (Elite Ed) 2009;1:13–25. [PMC free article] [PubMed] [Google Scholar]

56. Klotz LH. Active surveillance with selective delayed intervention: walking the line between overtreatment for indolent disease and undertreatment for aggressive disease. Can J Urol. 2005;12(Suppl 1):53–57. discussion 101-102. [PubMed] [Google Scholar]

57. Sandhu GS, Andriole GL. Overdiagnosis of prostate cancer. Journal of the National Cancer Institute Monographs. 2012;2012(45):146–151. doi: 10.1093/jncimonographs/lgs031. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

58. Schroder FH. Landmarks in prostate cancer screening. BJU international. 2012;110(Suppl 1):3–7. doi: 10.1111/j.1464-410X.2012.011428.x. [PubMed] [CrossRef] [Google Scholar]

59. Force USPST. Screening for prostate cancer: U.S. Preventive Services Task Force recommendation statement. Annals of internal medicine. 2008;149(3):185–191. [PubMed] [Google Scholar]

60. Chou R, Croswell JM, Dana T, Bougatsos C, Blazina I, Fu R, Gleitsmann K, Koenig HC, Lam C, Maltz A, Rugge JB, Lin K. Screening for prostate cancer: a review of the evidence for the U.S. Preventive Services Task Force. Annals of internal medicine. 2011;155(11):762–771. doi: 10.7326/0003-4819-155-11-201112060-00375. [PubMed] [CrossRef] [Google Scholar]