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Epidemiology

Index-based dietary patterns and risk of lung cancer in the NIH–AARP diet and health study

Abstract

Background/Objectives:

Dietary pattern analysis considers combinations of food intake and may offer a better measure to assess diet–cancer associations than examining individual foods or nutrients. Although tobacco exposure is the major risk factor for lung cancer, few studies have examined whether dietary patterns, based on preexisting dietary guidelines, influence lung cancer risk. After controlling for smoking, we examined associations between four diet quality indices—Healthy Eating Index–2010 (HEI-2010), Alternate Healthy Eating Index–2010 (AHEI-2010), alternate Mediterranean Diet score (aMED) and Dietary Approaches to Stop Hypertension (DASH)—and lung cancer risk in the NIH–AARP (National Institutes of Health-American Association of Retired Persons) Diet and Health study.

Subjects/Methods:

Baseline dietary intake was assessed in 460 770 participants. Over a median of 10.5 years of follow-up, 9272 incident lung cancer cases occurred. Cox proportional hazards regression was used to estimate hazard ratios (HRs) and confidence intervals (CIs).

Results:

Comparing highest to lowest quintiles, HRs (95% CIs) for lung cancer were as follows: HEI-2010=0.83 (0.77–0.89), AHEI-2010=0.86 (0.80–0.92), aMED=0.85 (0.79–0.91) and DASH=0.84 (0.78–0.90). Among the individual components of the dietary indices, higher consumption of whole grains and fruits was significantly inversely associated with lung cancer risk for several of the diet indices. Total index score analyses stratified by smoking status showed inverse associations with lung cancer for former smokers; however, only HEI-2010 was inversely associated in current smokers and no index score was inversely associated among never smokers.

Conclusions:

Although smoking is the factor most strongly associated with lung cancer, this study adds to a growing body of evidence that diet may have a modest role in reducing lung cancer risk, especially among former smokers.

Introduction

Lung cancer is the second most common form of cancer in men and women in the United States and is the leading cause of cancer-related death.1 Although tobacco exposure is the single biggest cause of lung cancer, there is some evidence that diet may influence lung cancer risk. The World Cancer Research Fund reported probable lung cancer risk reduction with higher consumption of fruits and foods containing carotenoids.2 Studies of individual foods or nutrients also suggest that specific dietary components may be associated with lung cancer risk, but associations tend to be inconsistent across studies.3, 4, 5, 6, 7, 8, 9

Rather than focusing on a single food or nutrient, dietary pattern analysis considers overall diet to better account for foods being consumed in combination.10 Examining dietary patterns considers that individual dietary components can be highly correlated or have synergistic or antagonistic biologic interactions that produce associations with disease risk that cannot be captured by studying a single food or nutrient.11 In previous studies of dietary patterns and lung cancer risk,12, 13, 14, 15, 16, 17, 18, 19 all but one study12 used data-driven approaches, such as factor analysis, which create dietary groupings that are unique to each study and do not allow for comparison across studies. An alternative approach is to use indices to define patterns a priori, based on dietary guidelines or recommendations, which can be used to compare diet quality across study populations.

To our knowledge, no previous study has comprehensively assessed index-based dietary patterns and lung cancer risk. We examined the association between diet quality and risk of lung cancer in the NIH–AARP (National Institutes of Health-American Association of Retired Persons) Diet and Health Study using four index-based dietary patterns: the Healthy Eating Index 2010 (HEI-2010),20 the Alternate Healthy Eating Index-2010 (AHEI-2010),21 the alternate Mediterranean Diet score (aMED)22 and the Dietary Approaches to Stop Hypertension (DASH).23

Subjects and methods

Study population

The NIH–AARP Diet and Health Study has been described previously.24 From 1995 to 1996, mailed questionnaires were used to recruit men and women aged 50–71 years, who were AARP members and residents of six US states (California, Florida, Louisiana, New Jersey, North Carolina or Pennsylvania) or two metropolitan areas (Atlanta, Georgia, or Detroit, Michigan). Of the 566 398 individuals who completed the self-administered baseline questionnaire, we excluded those whose questionnaire was completed by a proxy (n=15 760), those with a previous cancer (except nonmelanoma skin cancer) (n=51 223) or a cancer cause of death record but no cancer registry data (n=2344) and those with end-stage renal disease (n=997). We further excluded 4389 individuals for whom energy intake was more than two sex-specific interquartile ranges above the 75th or below the 25th percentile, after conducting a Box-Cox log transformation of energy intake.25 Lastly, participants who were missing information on tobacco smoking were also excluded (15 966 men and 14 949 women). The final analytic population (n=460 770) included 277 174 men and 183 596 women. The NIH–AARP Diet and Health study was approved by the Special Studies Institutional Review Board of the National Cancer Institute and all participants provided informed consent.

Lung cancer case identification

Study participants were followed from enrollment in 1995–1996 through 31 December 2006. Cancer cases were identified through probabilistic linkage with 11 state cancer registry databases that included the 8 original states of study enrollment plus Arizona, Nevada and Texas. The cancer registry case ascertainment for this cohort is around 90%.26 Vital status was obtained by annual linkage to the Death Master File from the Social Security Administration, the National Death Index, cancer registry linkage and responses to mailings.

Cases were incident lung cancers with the International Classification of Diseases for Oncology, Third Edition, codes C34.0–C34.9. Date of diagnosis and tumor characteristics were obtained from the cancer registries. The histology types and corresponding International Classification of Diseases for Oncology, Third Edition codes of lung carcinomas included small cell (8002, 8041, 8042, 8043, 8044 and 8045), adenocarcinoma (bronchoalveolar: 8250–8254 and other: 8140, 8255, 8260, 8310, 8323, 8480, 8481, 8490, 8550 and 8574) and squamous cell (8050 and 8070–8075).

Dietary assessment

At baseline, participants completed a 124-item food frequency questionnaire (FFQ) developed at the National Cancer Institute. The FFQ asked about usual frequency of intake and portion sizes over the previous 12 months. The FFQ was validated for foods and nutrients using two nonconsecutive 24-h dietary recalls within a year of baseline in a subset of participants.27

The FFQ data were merged with the United States Department of Agriculture's MyPyramid Equivalents Database version 1.0, to construct guidance-based food group equivalents for whole grains, total grains, total vegetables, total fruits, low-fat dairy, protein foods (including poultry, fish, nuts, soy and legumes), solid fat, added sugars and alcohol. Variables were also created for vegetables (excluding white potatoes), red and processed meat, whole fruits, sugar-sweetened beverages and energy from alcohol. Additional nutrient variables were created for saturated fatty acids, polyunsaturated fatty acids, monounsaturated fatty acids, trans fat, omega fatty acids (EPA+DHA (eicosapentaenoic acid and docosahexaenoic acid)), sodium and alcohol by using the United States Department of Agriculture Survey Nutrient Database and the Nutrition Data System for Research. Food group equivalents and nutrient variables were used to create individual component scores and total index scores for the HEI-2010, AHEI-2010, aMED and DASH (Table 1).

Table 1 Components of each diet quality index and criteria for maximum scores for each component

HEI-2010 score

The HEI-2010 score is based on the Dietary Guidelines for Americans 201020 and assesses 12 diet components for a total of 100 points. Six components are worth 0–5 points: total vegetables, greens and beans (dark green vegetables and legumes that are not already counted as protein food), total fruits, whole fruits, seafood and plant proteins, and total protein foods. Five components are worth 0–10 points: whole grains, low-fat dairy, fatty acid ratio (polyunsaturated fatty acids+monounsaturated fatty acids:saturated fatty acids), refined grains and sodium. One component, empty calories (energy from solid fats, added sugars and alcohol in excess of 13 g/1000 kcal) is worth 0–20 points. Each component, except for the fatty acid ratio, is scored on a density basis (per 1000 kcal or as a percentage of energy).

AHEI-2010 score

The AHEI-2010 score, based on epidemiologic studies of foods and nutrients associated with chronic disease risk,21 has 11 components scored from 0 to 10 for a total score ranging from 0 to 110 points. For four components (sugar-sweetened beverages, red and processed meat, sodium and trans fat), higher intake corresponds to a lower score. For the remaining seven components (fruits, vegetables (excluding potatoes), nuts and legumes, whole grains, polyunsaturated fatty acids, EPA+DHA fatty acids and moderate alcohol consumption), higher intake corresponds to a higher score.

aMED score

For the aMED score, which assesses adherence to a traditional Mediterranean diet, 9 components are scored as 0 or 1 for a total of up to 9 points.22 One point is scored for intake at or greater than the sex-specific median for whole grains, vegetables (excluding potatoes), fruits, nuts, legumes, fish and fatty acid ratio (monounsaturated fatty acids:saturated fatty acids), as well as intake less than the sex-specific median for red and processed meat. For alcohol, one point is scored for moderate intake (10–25 g/day).

DASH score

The DASH score, which was developed from randomized controlled feeding trials that examined the effects of diet on blood pressure, scores 8 components from 0 to 5 for a total of up to 40 points.23 Scores are based on sex-specific quintiles and ranged from 1 point (lowest quintile) to 5 points (highest quintile) for whole grains, vegetables (excluding potatoes), fruits, nuts and legumes, and low-fat dairy components. For sodium, sugar-sweetened beverages, and red and processed meat, scores ranged from 1 (highest quintile) to 5 (lowest quintile).

Statistical analysis

Cox proportional hazards regression, with person-years as the underlying time metric, was used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) for lung cancer risk by quintile of diet score. Person-years were calculated as the time from return of the baseline questionnaire until diagnosis of a first primary cancer (excluding nonmelanoma skin cancer), death, emigration out of the cancer registry area, or the end of follow-up (31 December 2006), whichever occurred first.

Multivariable models adjusted for age (years), race (White, non-Whiteor missing), education (less than high school, high school, some college, college graduate or missing), body mass index (<18.5, 18.5 to <25, 25 to <30, 30 to <35, 35 to <40, 40 or missing kg/m2), physical activity (20 daily minutes reported rarely or never, 1–3 times per month, 1–2 times per week, 3–4 times per week, 5 times per week or missing), total energy intake (kcal), sex (for sex-combined models), cigarette smoking (never, former or current), time since smoking cessation among former smokers (1–4, 5–9 or 10 years), number of cigarettes smoked per day among former and current smokers (1–10, 11–20, 21–30, 31–40, 41–60 or 61 cigarettes per day), and pipe or cigar smoking (yes or no). Alcohol intake (g) was included in the models for HEI-2010 and DASH only; the AHEI-2010 and aMED scores include alcohol as a diet component. Effect estimates were not appreciably different for models with or without total energy; therefore, total energy was included in multivariable models to reduce measurement error and allow for comparisons across indices. To test for a linear trend, an ordinal term with the median values of each index-based score by quintile was entered into the model as a continuous variable. To examine the effects of individual components in each dietary score, separate models were run for each component (component i), adjusting for covariates and a modified total index score that did not include the respective component (modified total index score=total index score−component i). The proportional hazards assumption was tested and confirmed by modeling interaction terms of the diet quality index score and follow-up time in separate models.

Potential effect modification was examined for sex, age (split at the median age of 62 years old) and body mass index (18.5 to <25, 25 to <30 and 30 kg/m2) by including a cross-product interaction term of quintiles of the diet index of interest and the potential modifying factor as a categorical variable into multivariable models. As progressing disease has the potential to influence diet patterns, a sensitivity analysis was conducted by excluding lung cancer cases that were diagnosed within the first 3 years of follow-up.

Statistical analyses were conducted using SAS software version 9.2 (SAS Institute, Cary, NC, USA) and all P-values were two sided.

Results

During a median of 10.5 years of follow-up, 9272 incident lung cancer cases occurred (5856 men and 3416 women), including 3419 (36.9%) adenocarcinomas, 1686 (18.2%) squamous cell carcinomas and 1342 (14.5%) small cell carcinomas. Participants in the highest quintile of each diet score (best diet quality) were more likely to be college graduates, physically active, have a lower body mass index, consume less alcohol and were less likely to smoke (except AHEI-2010 for women) (Table 2). Men and women in the highest quintile of the aMED and DASH scores, and women in the highest quintile of AHEI-2010, had higher energy intake than those in the lowest quintile. Pearson’s correlation coefficients between scores ranged from 0.43 (for aMED and HEI-2010) to 0.63 (for HEI-2010 and DASH). All correlations were statistically significant (P<0.0001).

Table 2 Baseline characteristics of men (N=277 174) and women (N=183 596)

All diet scores were inversely associated with risk of lung cancer in multivariable models of men and women combined (comparing highest versus lowest quintile, HEI-2010: HR=0.83, 95% CI=0.77, 0.89; AHEI-2010: HR=0.86, 95% CI=0.80, 0.92; aMED: HR=0.85, 95% CI=0.79, 0.91; DASH: HR=0.84, 95% CI=0.78, 0.90) (Table 3). Statistically significant inverse associations remained for all scores when stratifying by sex (data not shown). Similar inverse associations were observed for each diet index score when analyses were restricted to former smokers; however, HEI-2010 was the only diet index score significantly associated with a lower risk of lung cancer for current smokers. Among the 164 219 never smokers (including 495 lung cancer cases), there was suggestion of an inverse association between higher diet quality score and lung cancer risk; however, none of the estimates were statistically significant. It should be noted that the number of lung cancer cases was highest in the former smoker group. Therefore, the greater statistical power in this group may account for the stronger associations observed in former smokers.

Table 3 HRs for lung cancer by quintile of diet quality indices, overall and by smoking status, NIH–AARP Diet and Health Study, 1995–2006

When stratifying by histology type, statistically significant inverse associations were observed for adenocarcinomas and squamous cell carcinomas for all diet indices, but inverse associations did not remain statistically significant for small cell carcinomas (data not shown). Body mass index did not modify the associations with any diet score (data not shown). Age at enrollment did not modify associations with AHEI-2010, aMED or DASH (data not shown); however, it did modify the association with the HEI-2010 score (P for interaction=0.009), with a stronger inverse association observed for subjects younger than the median age of 62 years (highest versus lowest quintile: HR=0.77, 95% CI=0.67, 0.88) than for subjects aged 62 years and older (highest versus lowest quintile: HR=0.86, 95% CI=0.79, 0.94). Results were also unchanged after excluding lung cancer cases diagnosed during the first 3 years of follow-up (data not shown).

Tables 4 and 5 present risk associations for individual components of each diet score. For HEI-2010, lung cancer risk was lower among men with a higher score for sodium (indicating lower consumption), but none of the components were significantly associated with lung cancer risk for women. None of the AHEI-2010 components were associated with lung cancer risk in men; however, a higher score for whole grains was linked with reduced risk in women. For aMED, higher scores of whole grains and fruits were associated with lower risk of lung cancer in men and women, and a higher score for alcohol (indicating moderate consumption) was inversely associated with risk in men. Within DASH, the fruit component was associated with a lower risk of lung cancer in men, and the whole grain and nuts, soy and legumes components were associated with a reduced risk in women.

Table 4 HRs for lung cancer by individual components of four diet quality indices among 277 174 men in the NIH–AARP Diet and Health Study
Table 5 HRs for lung cancer by individual components of four diet quality indices among 183 596 women in the NIH-AARP Diet and Health Study

Discussion

We observed that higher diet quality, as measured by the HEI-2010, AHEI-2010, aMED and DASH scores, was associated with a statistically significant lower risk of lung cancer across all four diet quality indices, in particular among former smokers. With the exception of one study that looked at the aMED score,12 to our knowledge, no previous studies have examined these four index-based diet scores in relation with lung cancer risk.

In an Italian cohort of heavy smokers, an aMED score of 8 compared with 1 was associated with a significantly lower risk of lung cancer, although this analysis did not adjust for smoking patterns.12 All other studies of dietary patterns and lung cancer risk used data-driven methods. When principal components analysis was used to identify a ‘prudent’ or healthy diet pattern (characterized by high intake of fruits, vegetables, lean meats, whole grains and antioxidants), a reduced risk of lung cancer was observed for heavy smokers in an Italian cohort,13 men in the Netherlands Cohort Study,18 a US case–control study of never smokers14 and several case–control analyses from Uruguay.15, 17 A ‘high-meat’ or ‘Western’ dietary pattern characterized by high intake of red and processed meat was associated with increased lung cancer risk in case–control studies from Uruguay15, 16, 17 and a Netherlands cohort,18 but was not associated with lung cancer risk in an Italian cohort.13 A ‘drinker’ pattern, characterized by high intake of alcoholic beverages, was associated with a higher risk of lung cancer among men in one case–control study,16 although the association just missed statistical significance. Unexpectedly, a ‘sweet foods’ pattern, characterized by high intake of cakes, cookies, candies and berries, was significantly inversely associated with lung cancer risk in the Netherlands cohort.18 Finally, in a US case–control study that used cluster analysis to identify ‘healthy’ and ‘unhealthy’ diet patterns,19 neither pattern was associated with lung cancer risk after adjustment for smoking.

In individual components analyses, higher intake of whole grains and fruits was significantly inversely associated with lung cancer risk for AHEI-2010, aMED and DASH. In line with our results, a pooled analysis of eight cohort studies reported a 23% reduction in lung cancer risk, comparing the highest with the lowest quintile of total fruit consumption, controlling for smoking and other lung cancer risk factors.6 A potential mechanism for the protective effect of fruit consumption is the presence of carotenoids and quercetin in fruit, which have been associated with a lower risk for lung cancer28, 29 and may have antitumorigenic and antiproliferative properties.30, 31 Although previous studies have not assessed the association between whole grain consumption and risk of lung cancer, an inverse association is plausible, given that some whole grains are a good source of selenium, which may protect against lung cancer.32, 33 Although we observed that moderate alcohol consumption, as measured by the aMED score, was associated with a lower lung cancer risk in men, a pooled analysis of seven cohort studies found that compared with no alcohol consumption, moderate alcohol consumption (15 to <30 g/d) was not associated with lung cancer risk.34

Strengths of our study include the prospective study design, a large number of incident lung cancer cases and comprehensive assessment of potential confounders. The use of four established diet indices defined a priori allow our results to be compared with findings from other studies that use these same diet index scores, unlike data-driven approaches for identifying dietary patterns that cannot be compared across studies. The results do not provide evidence that one measure of diet quality is superior over another. All four diet index scores had similar inverse associations with the risk of lung cancer. Although each index captured a slightly different dietary pattern and measured individual components slightly differently, all indices emphasized a diet high in vegetables, fruits, whole grains and plant proteins, and minimal in refined grains, empty calories, and red and processed meat.

Despite controlling for cigarette use, it is possible that the significant findings observed among smokers are due to residual confounding by smoking, given that cigarette use is associated with nutrient intake.35 Another limitation is that a single measurement of diet at baseline does not capture dietary changes over follow-up. Similarly, smoking and other potential confounding factors were only assessed at baseline. In addition, dietary intake was assessed using an FFQ, an instrument known to have inherent nondifferential measurement error,36, 37 which could underestimate the associations between diet quality and lung cancer risk.

In summary, we observed that higher diet quality was associated with a modest reduction in risk of lung cancer; however, it cannot be ruled out that the results are influenced by residual confounding by smoking. The inverse association between diet quality and lung cancer risk was most apparent among former smokers, suggesting diet may lower risk of lung cancer among people who quit smoking. Although smoking cessation is the single biggest factor associated with lung cancer risk reduction, this study adds to a growing body of evidence that diet may have a role in modestly reducing lung cancer risk.

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Acknowledgements

This work was supported by the Intramural Research Program of the National Cancer Institute, National Institutes of Health.

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Correspondence to G M Anic.

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Anic, G., Park, Y., Subar, A. et al. Index-based dietary patterns and risk of lung cancer in the NIH–AARP diet and health study. Eur J Clin Nutr 70, 123–129 (2016). https://doi.org/10.1038/ejcn.2015.122

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