Abstract
Background
Although tobacco smoking is the leading cause of lung cancer, interest in the relationship of diet quality on risk has been growing.
Methods
We examined the association between Healthy Eating Index-2010 (HEI-10) at enrollment and lung cancer incidence among 70,802 participants in a predominantly African American and low-income prospective cohort in the southern United States. Outcomes were ascertained through linkages with state cancer registries and the National Death Index (NDI). Hazard ratios by HEI-10 quartiles were assessed using Cox proportional hazard models adjusted for potential confounders.
Results
During ≤16 years of follow-up, 1454 incident lung cancers were identified. The lowest HEI-10 quartile compared to the highest was adversely associated with lung cancer risk (HR: 1.89, 95% CI 1.16–3.07) among male former smokers and female never smokers (HR: 2.58, 95% CI 1.06–6.28).
Conclusions
Low-quality diet was associated with increased lung cancer risk among male former smokers and female never smokers but cautious interpretation of the findings should be taken due to the small number of lung cancers among never smokers and the possibility of residual confounding by smoking in ever smokers.
Subject terms: Lung cancer, Risk factors, Epidemiology
Introduction
Lung cancer accounts for about 23% of cancer deaths in the United States and ranks second among the most common types of cancer diagnosed in males and females [1, 2]. While smoking shows one of the strongest associations with lung cancer, there is some evidence that diet may also contribute to lung cancer risk [3–6]. There is limited evidence suggesting that red meat, processed meat, and alcohol may increase the risk of lung cancer and limited evidence suggesting fruits, vegetables and foods containing beta-carotene, carotenoids, vitamin C and isoflavones might decrease the risk of lung cancer [6]. In addition, there is growing recognition that multiple components of diet may contribute simultaneously to disease risk and prevention. Thus, several dietary pattern scores have been created to assess overall diet quality using foods, food groups, and nutrient intake information [7, 8], such as the Healthy Eating Index (HEI) [9–11].
Although there is substantial interest in dietary patterns and their role in cancer, there are very limited data within African American individuals or individuals with low socioeconomic status (SES), who are at elevated risk of lung cancer [12] but often underrepresented and underserved and whose diets may substantially vary from the general US population. The Southern Community Cohort Study (SCCS) is a large predominantly African American prospective cohort of mostly low SES participants living in the southeastern United States. Low SES, residing in the US South and being a member of a Black racial group have been associated with lower diet quality and higher cancer incidence [13–16]. We previously found that HEI was inversely associated with all-cause mortality, cardiovascular disease mortality, and overall cancer mortality in the SCCS [17]. In the analyses herein, we examine associations between HEI-2010 and lung cancer incidence, as well as the relationship of the HEI-10 with biomarkers related to cancer risk that we hypothesized were related to dietary quality.
Methods
The SCCS is a prospective cohort study designed to investigate determinants for health disparities between African Americans and Whites in underserved populations. A total of 84,508 adults between the ages of 40 and 79 were enrolled during 2002–2009 from the following 12 Southeastern states: Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, Virginia, and West Virginia. Participants were enrolled either in person at one of 71 community health centers (CHC, 85%) or by mailings to stratified random samples of the general populations (GP) of these states [18, 19]. Structured in-person interviews were conducted by trained staff at CHCs to obtain detailed information on the participants’ demographic, socioeconomic, and anthropometric characteristics, personal and family medical history, and lifestyle choices such as alcohol use and diet. GP participants provided the same information by completing a self-administered questionnaire. Periodic direct contact with participants and linkages with the National Death Index (NDI) and the Social Security Administration’s Service for Epidemiologic Research were used to determine vital status. Cancer incidence was ascertained through linkages with cancer registries from the 12 Southeastern states. The study was approved by the institutional review boards of Vanderbilt University and the Meharry Medical College, and participants gave written informed consent at study enrollment.
Participants completed a food frequency questionnaire (FFQ) containing 89 food and 5 alcohol questions, which asked about the frequency of consumption of certain types of foods and alcohol over the last year [20, 21]. Data for participants ages 30–84 living in the South census region from the National Health and Nutrition Examination Survey (NHANES) and the USDA Continuing Survey of Food Intakes by Individuals (CSFII) were used to estimate portion size for each food item after a pilot study determined that collecting individual portion size data was not necessary [22]. The FFQ was validated by comparing the amounts of select nutrients measured from biosamples among a subset of the cohort to those nutrient amounts estimated from the scored FFQ [23].
The HEI-10 was calculated for participants who completed at least 79 of the 89 FFQ questions and had energy intake between 600 and 8000 kcal/day (N = 77,822) [11, 17]. The HEI-10 was calculated by linking the FFQ data with the MyPyramid Equivalents Database (MPED, version 2.0) [24] to determine equivalent intake in cups or ounces per 1000 kcal for food groups in the USDA Dietary Guidelines for Americans (DGA) [25]. The 12 components of the HEI-10 were calculated using reference SAS code provided by the USDA [26] and HEI-2010 standards, which recommended increasing consumption of total fruit, whole fruit, total vegetables, greens and beans, whole grains, dairy, total protein foods, seafood and plant proteins, and the ratio of unsaturated to saturated fatty acids and decreasing consumption of refined grains, sodium, and calories from solid fats, excessive alcohol, and added sugars. The HEI-10 total score ranges from 0 to 100.
After excluding those who reported having had cancer other than non-melanoma skin cancer at baseline (N = 6223), those who died less than a month after enrollment (N = 16), those who were missing information on smoking status or intensity (N = 781), and those who were diagnosed with lung cancer less than a month after enrollment (N = 7), 70,795 participants were available for the analyses. The HEI-10 score was analyzed using quartiles derived from the cohort with males and females combined, similar to previous studies [27–29], and linear trends in the scores were assessed by treating the quartiles as a linear variable using the median value for each quartile.
To inform the possible mechanisms by which the HEI-10 may affect lung cancer risk, we evaluated the relation of the HEI-10 with several biomarkers measured from samples collected at enrollment in a subset of the cohort. Biomarkers included c-reactive protein (CRP), urinary prostaglandin E2 metabolite (PGE-M), interleukins 1β and 6 (IL-1β, IL-6), tumor necrosis factor alpha (TNF-α), and hemoglobin A1c (HbA1c). We calculated partial spearman correlation coefficients adjusted for age, sex, BMI (kg/m2) and smoking status among cohort participants who had at least one measure of biomarkers related to cancer risk that we hypothesized to be potentially related to diet quality (n = 6090). Plasma high sensitivity CRP levels were measured by using a Millipore Human CRP enzyme-linked immunosorbent assay kit as described previously [30, 31]. Urinary PGE-M (11 alpha-hydroxy-9, 15-dioxo-2, 3, 4, 5-tetranor-prostane-1,20-dioic acid) level was measured using a liquid chromatography/tandem mass spectrometric method described previously [32]. Plasma levels of IL-1β, IL-6, and TNFα were measured by using MILLIPLEX MAP Human High Sensitivity T Cell Panel Premixed 21-plex - Immunology Multiplex Assay kit on Luminex 200TM Analyzer following the manufacturer’s protocols. HbA1c level was measured using the Bio-Rad Variant II Hemoglobin Testing System (HPLC) with the 270–2101 NU kit in the Clinical Chemistry laboratories at the Vanderbilt University Medical Center following the manufacturer’s protocol.
Chi-squared tests and ANOVA were used to test the univariate associations between HEI-10 and baseline characteristics. Cox proportional hazards models were used to test the associations between HEI-10 and incident lung cancer using a cohort study design following participants from age (in months) at enrollment through age (in months) at lung cancer diagnosis, death, loss to follow-up (n = 41), or date through which cancer registry data is complete (12/31/2016). Models were adjusted for sex (male, female), self-reported race (White, African American, other race), enrollment site (CHC or GP), education (less than high school, high school graduate, some college or technical training, and college graduate or higher education), annual household income (<$15,000, $15,000–$24,999, $25,000–$49,999, and $50,000 or more), marital status (married, not married), health insurance coverage (yes, no), BMI (<18.5, 18.5–24.9, 25–29.9, 30+ kg/m2), smoking status and intensity (current smoker of 20 or more cigarettes per day, current smoker of 10–19 cigarettes per day, current smoker of less than 10 cigarettes per day, former smoker of 20 or more cigarettes per day, former smoker of 10–19 cigarettes per day, former smoker of less than 10 cigarettes per day, never smoker), history of diabetes (yes, no), heart attack (yes, no), stroke (yes, no), hypertension (yes, no), hypercholesterolemia (yes, no), COPD (yes, no) and HIV/AIDS (yes, no), total physical activity MET-hours per day (none, tertiles among those reporting activity), total hours spent sitting, total energy intake (kcal/day), and menopause status (postmenopausal, premenopausal) and having ever used hormone replacement therapy (yes, no) among females. Sex-stratified analyses were conducted to account for differences in dietary patterns between males and females. Additional analyses were conducted stratified by sex and race (African Americans and Whites; there were too few in the other race category for separate analysis) and by sex and smoking status (current, former, and never smokers and never smokers combined with former smokers who quit more than 15 years before enrollment; there were only 27 incident lung cancers in male never smokers resulting in unstable estimates). Sensitivity analyses excluding the first 2 years of follow-up were conducted to assess the potential for reverse causation. Analyses examining the association of each individual component of the HEI-10 with lung cancer incidence were also conducted by sex. Missing covariate data were imputed using multiple imputation with five imputations. Sensitivity analyses using participants without missing data for the covariates included in the models were performed producing very similar results. Likelihood ratio tests comparing a model with a linear term for the HEI-10 and a model with splines with four knots for the HEI-10 were used to test for non-linearity. There was no evidence for non-linearity of the HEI-10 in the overall or stratified models. Likelihood ratio tests comparing models with and without interaction terms were used to test for interactions between the HEI-10 and sex, race, and smoking status and intensity. The proportional hazards assumption was tested by including an interaction between the HEI-10 quartiles and age. The assumption held for all models among males, former smokers and never smokers. Additional models among female current smokers were stratified by age at enrollment to account for the change in HEI-10 estimates by age. All analyses use two-sided tests and were performed using SAS software, version 9.4 (SAS Institute, Inc, Cary, NC).
Results
Participants 40–79 years old (mean: 51.9, SD: 8.6) at enrollment were followed on average for 10.6 years (range: 0.1–14.8). There were 1454 incident lung cancers (N = 757 males and N = 697 females). Average HEI-10 scores were lower for participants who developed lung cancer (mean: 55.1, SD: 11.5) compared to participants who did not develop lung cancer (mean: 57.7, SD: 12.0). In univariate analyses, the HEI-10 distribution was significantly different by sex and all covariates considered were associated with HEI-10 quartiles among both males and females except for total hours spent sitting and stroke which were not associated with HEI-10 in males (Table 1). Higher educational attainment, greater household income, being married, having health insurance, having a higher BMI, more time spent participating in physical activity, being postmenopausal, ever having hormone replacement therapy, never or former smoking, and having diabetes, a heart attack, hypertension, or high cholesterol were associated with higher quality diets while being enrolled at a CHC, having a higher caloric intake, or having COPD or HIV/AIDS were associated with lower-quality diets.
Table 1.
Baseline characteristics by sex and quartiles of HEI-10 scores in the Southern Community Cohort Study.
| Males (N = 28,951) | Females (N = 41,844) | |||||||
|---|---|---|---|---|---|---|---|---|
| Characteristic | Quartile 1 (low; N = 9133) | Quartile 2 (N = 8073) | Quartile 3 (N = 6789) | Quartile 4 (high; N = 4956) | Quartile 1 (low; N = 8565) | Quartile 2 (N = 9627) | Quartile 3 (N = 10,909) | Quartile 4 (high, N = 12,743) |
| HEI-10 score | ||||||||
| Median | 43.6 | 53.2 | 61.2 | 71.4 | 43.9 | 53.5 | 61.4 | 72.5 |
| Range | 13.7–49.0 | 49.0–57.3 | 57.3–65.9 | 65.9–95.2 | 16.9–49.0 | 49.0–57.3 | 57.3–65.9 | 65.9–96.7 |
| Age at enrollment (years), mean (SD) | 50.0 (7.6) | 50.7 (7.9) | 52.1 (8.3) | 54.7 (9.0) | 49.3 (7.6) | 51.0 (8.3) | 52.3 (8.7) | 55.0 (9.2) |
| Race, N (%) | ||||||||
| Non-Hispanic White | 2760 (30.2) | 2059 (25.5) | 1701 (25.1) | 1531 (30.9) | 2911 (34.0) | 2726 (28.3) | 2935 (26.9) | 3621 (28.4) |
| Non-Hispanic African American | 6090 (66.7) | 5709 (70.7) | 4800 (70.7) | 3123 (63.0) | 5342 (62.4) | 6531 (67.8) | 7495 (68.7) | 8456 (66.4) |
| All other | 283 (3.1) | 305 (3.8) | 288 (4.2) | 302 (6.1) | 312 (3.6) | 370 (3.8) | 479 (4.4) | 666 (5.2) |
| Education, N (%) | ||||||||
| <High school | 3183 (35.0) | 2572 (32.0) | 1846 (27.3) | 1041 (21.2) | 2861 (33.5) | 3012 (31.4) | 2975 (27.3) | 2641 (20.8) |
| High school | 3420 (37.6) | 2912 (36.2) | 2226 (32.9) | 1228 (25.0) | 3163 (37.0) | 3260 (33.9) | 3527 (32.4) | 3666 (28.9) |
| Some college or training | 1874 (20.6) | 1778 (22.1) | 1723 (25.5) | 1327 (27.0) | 1960 (22.9) | 2426 (25.3) | 2997 (27.5) | 3879 (30.5) |
| College graduate or more | 629 (6.9) | 776 (9.7) | 962 (14.2) | 1315 (26.8) | 562 (6.6) | 905 (9.4) | 1382 (12.7) | 2512 (19.8) |
| Missing, N | 27 | 35 | 32 | 45 | 19 | 24 | 28 | 45 |
| Income, N (%) | ||||||||
| <$15,000 | 5627 (62.1) | 4623 (57.8) | 3535 (52.7) | 1880 (38.5) | 5338 (63.0) | 5686 (59.8) | 5998 (55.7) | 5924 (47.2) |
| $15,000–$24,999 | 1846 (20.4) | 1718 (21.5) | 1326 (19.8) | 925 (19.0) | 1882 (22.2) | 2101 (22.1) | 2383 (22.1) | 2810 (22.4) |
| $25,000–$49,999 | 1071 (11.8) | 1016 (12.7) | 1012 (15.1) | 906 (18.6) | 872 (10.3) | 1180 (12.4) | 1560 (14.5) | 2227 (17.8) |
| $50,000 or more | 515 (5.7) | 636 (8.0) | 829 (12.4) | 1166 (23.9) | 376 (4.4) | 548 (5.8) | 822 (7.6) | 1578 (12.6) |
| Missing, N | 74 | 80 | 87 | 79 | 97 | 112 | 146 | 204 |
| Currently married, N (%) | 2977 (32.7) | 2774 (34.5) | 2694 (40.0) | 2444 (50.1) | 2755 (32.3) | 3079 (32.1) | 3631 (33.5) | 4353 (34.4) |
| Missing, N | 33 | 44 | 52 | 73 | 31 | 35 | 54 | 80 |
| Health insurance, N (%) | 4479 (49.1) | 4182 (51.8) | 4049 (59.7) | 3438 (69.5) | 4762 (55.7) | 5726 (59.6) | 6844 (62.8) | 8732 (68.6) |
| Missing, N | 11 | 6 | 8 | 9 | 9 | 13 | 16 | 13 |
| CHC enrollment, N (%) | 8351 (91.4) | 7224 (89.5) | 5736 (84.5) | 3674 (74.1) | 7896 (92.2) | 8773 (91.1) | 9802 (89.9) | 10,916 (85.7) |
| Body mass index (BMI, kg/m2), N (%) | ||||||||
| <18.5 | 153 (1.7) | 114 (1.4) | 45 (0.7) | 25 (0.5) | 151 (1.8) | 148 (1.6) | 133 (1.2) | 80 (0.6) |
| 18.5–24.9 | 3280 (36.1) | 2768 (34.5) | 2036 (30.2) | 1212 (24.7) | 1783 (21.1) | 1790 (18.9) | 1860 (17.3) | 2183 (17.4) |
| 25.0–29.9 | 3118 (34.4) | 2792 (34.8) | 2421 (35.9) | 1931 (39.3) | 2072 (24.5) | 2394 (25.3) | 2785 (25.9) | 3375 (26.8) |
| 30 or more | 2524 (27.8) | 2346 (29.3) | 2239 (33.2) | 1747 (35.5) | 4437 (52.6) | 5128 (54.2) | 5982 (55.6) | 6943 (55.2) |
| Missing, N | 58 | 53 | 48 | 41 | 122 | 167 | 149 | 162 |
| Physical activity (MET-hours/day), N (%) | ||||||||
| None | 615 (6.8) | 439 (5.5) | 376 (5.6) | 181 (3.7) | 179 (2.1) | 196 (2.1) | 173 (1.6) | 178 (1.4) |
| Tertile 1 (>0–12.6) | 2915 (32.3) | 2502 (31.4) | 2146 (32.2) | 1582 (32.7) | 2959 (35.0) | 3170 (33.4) | 3574 (33.3) | 4158 (33.2) |
| Tertile 2 (12.7–26.4) | 2047 (22.7) | 1958 (24.6) | 1664 (24.9) | 1477 (30.5) | 2929 (34.6) | 3380 (35.6) | 3965 (36.9) | 4850 (38.7) |
| Tertile 3 ( > 26.4) | 3449 (38.2) | 3061 (38.5) | 2486 (37.3) | 1605 (33.1) | 2387 (28.2) | 2750 (29.0) | 3032 (28.2) | 3342 (26.7) |
| Missing, N | 107 | 113 | 117 | 111 | 111 | 131 | 165 | 215 |
| Total sitting time (hours/day), mean (SD) | 9.2 (5.3) | 9.2 (5.1) | 9.3 (5.1) | 9.2 (4.9) | 9.7 (5.2) | 9.5 (5.1) | 9.4 (5.0) | 8.9 (4.7) |
| Missing, N | 79 | 43 | 39 | 30 | 80 | 92 | 122 | 116 |
| Smoking status, cigarettes per day, N (%) | ||||||||
| Never | 1721 (18.8) | 1630 (20.2) | 1760 (25.9) | 1701 (34.3) | 3184 (37.2) | 3947 (41.0) | 5109 (46.8) | 6808 (53.4) |
| Former, <10 | 332 (3.6) | 357 (4.4) | 427 (6.3) | 470 (9.5) | 405 (4.7) | 577 (6.0) | 793 (7.3) | 1317 (10.3) |
| Former, 10–19 | 360 (3.9) | 411 (5.1) | 424 (6.2) | 454 (9.2) | 280 (3.3) | 452 (4.7) | 555 (5.1) | 835 (6.6) |
| Former, 20+ | 935 (10.2) | 970 (12.0) | 929 (13.7) | 903 (18.2) | 578 (6.7) | 784 (8.1) | 1028 (9.4) | 1248 (9.8) |
| Current, <10 | 1413 (15.5) | 1373 (17.0) | 1171 (17.2) | 591 (11.9) | 1048 (12.2) | 1255 (13.0) | 1315 (12.1) | 1078 (8.5) |
| Current, 10–19 | 1875 (20.5) | 1625 (20.1) | 1159 (17.1) | 429 (8.7) | 1323 (15.4) | 1271 (13.2) | 1133 (10.4) | 844 (6.6) |
| Current, 20+ | 2497 (27.3) | 1707 (21.1) | 919 (13.5) | 408 (8.2) | 1747 (20.4) | 1341 (13.9) | 976 (8.9) | 613 (4.8) |
| Energy intake (Kcal/day), mean (SD) | 3197 (1555) | 3278 (1627) | 3077 (1614) | 2588 (1340) | 2411 (1344) | 2400 (1353) | 2273 (1309) | 1915 (976) |
| Health history, N (%) | ||||||||
| Diabetes | 1166 (12.8) | 1339 (16.6) | 1469 (21.7) | 1338 (27.0) | 1351 (15.8) | 1932 (20.1) | 2683 (24.6) | 3736 (29.3) |
| Missing, N | 4 | 3 | 5 | 4 | 3 | 3 | 2 | 2 |
| Heart attack | 691 (7.6) | 638 (7.9) | 609 (9.0) | 529 (10.7) | 391 (4.6) | 524 (5.4) | 619 (5.7) | 772 (6.1) |
| Missing, N | 9 | 3 | 5 | 4 | 7 | 6 | 7 | 9 |
| Stroke | 532 (5.8) | 461 (5.7) | 419 (6.2) | 318 (6.4) | 471 (5.5) | 593 (6.2) | 731 (6.7) | 892 (7.0) |
| Missing, N | 10 | 9 | 7 | 4 | 8 | 9 | 6 | 9 |
| Hypertension | 4220 (46.2) | 3837 (47.5) | 3562 (52.5) | 2710 (54.7) | 4449 (52.0) | 5538 (57.5) | 6463 (59.3) | 7795 (61.2) |
| Missing, N | 5 | 3 | 2 | 2 | 1 | 3 | 4 | 4 |
| Hypercholesterolemia | 2112 (23.2) | 2088 (25.9) | 2160 (31.9) | 2024 (40.9) | 2509 (29.4) | 3139 (32.7) | 3924 (36.0) | 5430 (42.7) |
| Missing, N | 36 | 24 | 9 | 13 | 17 | 21 | 23 | 16 |
| COPD | 712 (7.8) | 535 (6.6) | 402 (5.9) | 238 (4.8) | 987 (11.5) | 1094 (11.4) | 1057 (9.7) | 1047 (8.2) |
| Missing, N | 6 | 8 | 8 | 3 | 9 | 7 | 9 | 11 |
| HIV/AIDS | 231 (2.5) | 217 (2.7) | 152 (2.2) | 90 (1.8) | 106 (1.2) | 126 (1.3) | 95 (0.9) | 69 (0.5) |
| Missing, N | 4 | 4 | 0 | 1 | 3 | 2 | 1 | 4 |
| Postmenopause, N (%) | 5035 (58.8) | 6076 (63.2) | 7382 (67.8) | 9631 (75.7) | ||||
| Missing, N | 9 | 13 | 20 | 18 | ||||
| Hormone therapy, N (%) | 1917 (22.4) | 2347 (24.5) | 3074 (28.3) | 4503 (35.4) | ||||
| Missing, N | 18 | 33 | 31 | 40 | ||||
P values were computed using Chi-square tests for categorical variables and ANOVA F-tests for continuous variables. All P values were <0.0001 except for total sitting time (P = 0.15), stroke (P = 0.32) and HIV/AIDS (P = 0.009) among males and currently married (P = 0.0008) among females.
The lowest HEI-10 quartile compared to the highest was adversely related to lung cancer incidence among men but not women (Table 2), although the HEI-10 by sex interaction was not significant. Among males, there was a 35% increase in lung cancer risk (95% CI: 1.05–1.75, P = 0.02) for those with the lowest quality diet compared with the highest quality diet, whereas the corresponding HR among females was 1.06 (0.85–1.33). Associations between HEI-10 and lung cancer were observed for the whole cohort and for men and women separately in models without adjustment for smoking (Supplemental Table 1) but the strength of the associations was attenuated when confounding by smoking status and intensity was adequately controlled. In Table 3, the patterns were generally similar between African Americans and Whites (though somewhat stronger for Whites). Among males the association appeared stronger for former than current smokers (Table 4). Among females alone and males and females combined the association was only seen among never smokers, however the number of lung cancers among never smokers was small and the number of male never smokers with lung cancer was too small to produce reliable risk estimates. When combining never smokers with former smokers who had quit smoking more than 15 years before enrollment (Supplemental Table 2), significant adverse trends remained for both sexes combined and females alone. Hazard ratios remained higher than 1.0 for the 3 lower-quality diet quartiles among males, however, the number of lung cancers remained small and the associations were not statistically significant.
Table 2.
Associations between HEI-10 score and lung cancer incidence by sex, the Southern Community Cohort Study.
| Overall (N = 70,795) | Male (N = 28,951) | Female (N = 41,844) | ||||
|---|---|---|---|---|---|---|
| Cases, N | HR (95% CI) | Cases, N | HR (95% CI) | Cases, N | HR (95% CI) | |
| Diet quality | ||||||
| Highest quality diet (Q4) | 257 | 1.0 | 84 | 1.0 | 173 | 1.0 |
| Higher quality diet | 341 | 1.09 (0.93–1.29) | 158 | 1.16 (0.89–1.53) | 183 | 1.07 (0.86–1.32) |
| Lower-quality diet | 390 | 1.06 (0.90–1.25) | 226 | 1.23 (0.95–1.60) | 164 | 0.95 (0.76–1.18) |
| Lowest quality diet (Q1) | 466 | 1.18 (1.00–1.39) | 289 | 1.35 (1.05–1.75) | 177 | 1.06 (0.85–1.33) |
| P trend | 0.07 | 0.02 | 0.83 | |||
| P interaction for sexa | 0.55–0.57 | |||||
aRange of interaction P values for the HEI-10 and sex using likelihood ratio tests from overall models with and without the interaction terms across the five imputations.
HEI-10 scores were split into quartiles: lowest quality diet (13.72–49.04), lower-quality diet (49.04–57.32), higher quality diet (57.32–65.91), highest quality diet (reference, 65.91–96.72).
Models were adjusted for sex (male vs female in analyses containing both sexes), race (Black, other races, vs White), enrollment source (GP vs CHC), education (less than high school, high school, some college or training, vs college graduate or higher), income (<$15,000, $15,000–$24,999, $25,000–$49,999, vs $50,000 or more), marital status (married vs not married), health insurance coverage (yes vs no), BMI (<18.5, 25–29.9, 30+ vs 18.5–24.9 kg/m2), smoking status and intensity (current smoker of 20 or more cigarettes per day, current smoker of 10–19 cigarettes per day, current smoker of less than 10 cigarettes per day, former smoker of 20 or more cigarettes per day, former smoker of 10–19 cigarettes per day, former smoker of less than 10 cigarettes per day, vs never smoker), diabetes (yes vs no), history of heart attack (yes vs no), history of stroke (yes vs no), hypertension (yes vs no), hypercholesterolemia (yes vs no), COPD (yes vs no), HIV/AIDS (yes vs no), total physical activity MET-hours per day (none, lowest tertile among those reporting some physical activity, middle tertile, vs highest tertile), total hours spent sitting per day, energy intake (kcal/day), and menopausal status (postmenopausal vs premenopausal) and ever use of hormone replacement therapy (yes vs no) among females.
Table 3.
Association between HEI-10 score and lung cancer incidence by sex and race.
| Males | Females | |||||||
|---|---|---|---|---|---|---|---|---|
| African American (N = 19,722) | White (N = 8051) | African American (N = 27,824) | White (N = 12,193) | |||||
| Cases, N | HR (95% CI) | Cases, N | HR (95% CI) | Cases, N | HR (95% CI) | Cases, N | HR (95% CI) | |
| Diet quality | ||||||||
| Highest quality diet | 57 | 1.0 | 22 | 1.0 | 101 | 1.0 | 64 | 1.0 |
| Higher quality diet | 114 | 1.11 (0.80–1.53) | 38 | 1.26 (0.74–2.16) | 107 | 1.02 (0.77–1.34) | 68 | 1.10 (0.78–1.56) |
| Lower-quality diet | 162 | 1.19 (0.87–1.62) | 57 | 1.36 (0.81–2.28) | 96 | 0.93 (0.69–1.25) | 59 | 0.86 (0.59–1.25) |
| Lowest quality diet | 195 | 1.29 (0.95–1.75) | 89 | 1.60 (0.96–2.65) | 98 | 1.10 (0.82–1.49) | 72 | 0.91 (0.63–1.32) |
| P trend | 0.07 | 0.05 | 0.66 | 0.42 | ||||
| P interaction for racea | 0.87 | |||||||
aInteraction P values were the same across the five imputations for the HEI-10 and race using likelihood ratio tests from overall models with and without the interaction terms.
HEI-10 scores were split into quartiles: lowest quality diet (13.72–49.04), lower-quality diet (49.04–57.32), higher quality diet (57.32–65.91), highest quality diet (reference, 65.91–96.72).
Models were adjusted for enrollment source (GP vs CHC), education (less than high school, high school, some college or training, vs college graduate or higher), income (<$15,000, $15,000–$24,999, $25,000–$49,999, vs $50,000 or more), marital status (married vs not married), health insurance coverage (yes vs no), BMI ( < 18.5, 25–29.9, 30+ vs 18.5–24.9 kg/m2), smoking status and intensity (current smoker of 20 or more cigarettes per day, current smoker of 10–19 cigarettes per day, current smoker of less than 10 cigarettes per day, former smoker of 20 or more cigarettes per day, former smoker of 10–19 cigarettes per day, former smoker of less than 10 cigarettes per day, vs never smoker), diabetes (yes vs no), history of heart attack (yes vs no), history of stroke (yes vs no), hypertension (yes vs no), hypercholesterolemia (yes vs no), COPD (yes vs no), HIV/AIDS (yes vs no), total physical activity MET-hours per day (none, lowest tertile among those reporting some physical activity, middle tertile, vs highest tertile), total hours spent sitting per day, energy intake (kcal/day), and menopausal status (postmenopausal vs premenopausal) and ever use of hormone replacement therapy (yes vs no) for models among females.
Table 4.
Association between HEI-10 score and lung cancer incidence by sex and smoking status.
| All current smokers (N = 29,111) | Male current smokers (N = 15,167) | Female current smokers (N = 13,944) | ||||
|---|---|---|---|---|---|---|
| Cases, N | HR (95% CI) | Cases, N | HR (95% CI) | Cases, N | HR (95% CI) | |
| Diet quality | ||||||
| Highest quality diet | 158 | 1.0 | 53 | 1.0 | 105 | 1.0 |
| Higher quality diet | 238 | 0.94 (0.77–1.15) | 109 | 0.92 (0.66–1.29) | 129 | 0.98 (0.75–1.27) |
| Lower-quality diet | 295 | 0.89 (0.73–1.09) | 177 | 1.00 (0.73–1.37) | 118 | 0.80 (0.61–1.04) |
| Lowest quality diet | 393 | 1.03 (0.85–1.25) | 235 | 1.08 (0.79–1.47) | 158 | 1.03 (0.79–1.33) |
| P trend | 0.54 | 0.29 | 0.96 | |||
| All former smokers (N = 15,824) | Male former smokers (N = 6972) | Female former smokers (N = 8852) | ||||
| Cases, N | HR (95% CI) | Cases, N | HR (95% CI) | Cases, N | HR (95% CI) | |
| Diet quality | ||||||
| Highest quality diet | 87 | 1.0 | 30 | 1.0 | 57 | 1.0 |
| Higher quality diet | 74 | 1.09 (0.80–1.50) | 40 | 1.39 (0.86–2.24) | 34 | 0.95 (0.62–1.47) |
| Lower-quality diet | 64 | 1.09 (0.78–1.52) | 39 | 1.39 (0.85–2.26) | 25 | 0.92 (0.57–1.50) |
| Lowest quality diet | 56 | 1.19 (0.83–1.71) | 47 | 1.89 (1.16–3.07) | 9 | 0.52 (0.25–1.08) |
| P trend | 0.36 | 0.01 | 0.15 | |||
| All never smokers (N = 25,860) | Male never smokers (N = 6812) | Female never smokers (N = 19,048) | ||||
| Cases, N | HR (95% CI) | Cases, N | HR (95% CI) | Cases, N | HR (95% CI) | |
| Diet quality | ||||||
| Highest quality diet | 12 | 1.0 | 1 | 1.0 | 11 | 1.0 |
| Higher quality diet | 29 | 3.15 (1.59–6.24) | 9 | – | 20 | 2.77 (1.32–5.85) |
| Lower-quality diet | 31 | 4.14 (2.08–8.21) | 10 | – | 21 | 3.86 (1.83–8.18) |
| Lowest quality diet | 17 | 2.70 (1.25–5.83) | 7 | – | 10 | 2.58 (1.06–6.28) |
| P trend | 0.004 | – | 0.006 | |||
| P interaction HEI-10 x smoking status | <0.001 | 0.03 | <0.001 | |||
P values for the interaction between the HEI-10 and smoking status were computed using likelihood ratio tests comparing models with and without interaction terms.
HEI-10 scores were split into quartiles: lowest quality diet (13.72–49.04), lower-quality diet (49.04–57.32), higher quality diet (57.32–65.91), highest quality diet (reference, 65.91–96.72).
Models were adjusted for sex (male vs female in analyses including both sexes), race (Black, other races, vs White), enrollment source (GP vs CHC), education (less than high school, high school, some college or training, vs college graduate or higher), income (<$15,000, $15,000–$24,999, $25,000–$49,999, vs $50,000 or more), marital status (married vs not married), health insurance coverage (yes vs no), BMI (<18.5, 25–29.9, 30+ vs 18.5–24.9 kg/m2), smoking intensity for models among current or former smokers (20 or more cigarettes per day, 10–19 cigarettes per day, vs less than 10 cigarettes per day), diabetes (yes vs no), history of heart attack (yes vs no), history of stroke (yes vs no), hypertension (yes vs no), hypercholesterolemia (yes vs no), COPD (yes vs no), HIV/AIDS (yes vs no), total physical activity MET-hours per day (none, lowest tertile among those reporting some physical activity, middle tertile, vs highest tertile), total hours spent sitting per day, energy intake (kcal/day), and menopausal status (postmenopausal vs premenopausal) and ever use of hormone replacement therapy (yes vs no) for models among females.
Sensitivity analyses excluding the first 2 years of follow-up showed similar patterns to analyses using the entire follow-up time suggesting reverse causation is not an issue. A significant adverse trend between lower HEI-10 and lung cancer incidence was observed among all never smokers but not among all current or all former smokers (Supplemental Table 3). Among male former smokers there was a more significant trend and a stronger association for the lowest quality diet quartile compared to the highest (HR = 2.47, 95% CI 1.41–4.33, P = 0.002, P trend=0.002). Analyses among female current smokers stratified by age at enrollment (<50 vs 50+ and <55 vs 55 + ) showed an adverse association between low diet quality and lung cancer risk among participants who were younger at enrollment, however, the trend reversed for participants who enrolled at age 55 or later (Supplemental Table 4).
No clearer patterns emerged when lung cancer histological types (squamous cell carcinoma, adenocarcinoma, large cell carcinoma, or small cell lung cancer) were examined separately, with the statistical significance of the HEI-10 association among men disappearing in these sub-type analyses (data not shown). Analyses were also conducted to evaluate individual components of the HEI-10 among males and females (Supplemental Tables 5 and 6, respectively). In general, there were no associations between individual components and lung cancer risk.
Overall, there were no strong correlations between biomarker levels and HEI-10 (Table 5). The HEI-10 was negatively correlated with CRP overall and among males, females, current smokers, former smokers, and the participants who did not develop lung cancer, however all correlations were weak (<10%).
Table 5.
Cross-sectional partial correlations between HEI-10 score and baseline markers of inflammation, immune response, and insulin resistance among 6090 participants with at least one biomarker measured.
| C-reactive protein (CRP) | Urinary prostaglandin E2 metabolite (PGE-M) | Tumor necrosis factor alpha (TNF-α) | Interleukin 1β (IL-1β) | Interleukin 6 (IL-6) | Hemoglobin A1c (HbA1c) | |
|---|---|---|---|---|---|---|
| All participants | ||||||
| N | 5922 | 296 | 1272 | 1272 | 1272 | 2129 |
| Spearman correlation | −0.05 | 0.02 | 0.01 | 0.003 | −0.03 | 0.03 |
| P value | <0.0001 | 0.68 | 0.63 | 0.92 | 0.26 | 0.22 |
| Males | ||||||
| N | 2282 | 168 | 699 | 699 | 699 | 348 |
| Spearman correlation | −0.04 | 0.12 | 0.04 | 0.01 | −0.03 | 0.03 |
| P value | 0.04 | 0.12 | 0.27 | 0.82 | 0.46 | 0.61 |
| Females | ||||||
| N | 3640 | 128 | 573 | 573 | 573 | 1781 |
| Spearman correlation | −0.05 | −0.08 | −0.03 | −0.005 | −0.03 | 0.03 |
| P value | 0.001 | 0.35 | 0.48 | 0.91 | 0.48 | 0.20 |
| Current smokers | ||||||
| N | 2590 | 163 | 662 | 662 | 662 | 832 |
| Spearman correlation | −0.05 | 0.10 | 0.01 | 0.03 | −0.02 | 0.03 |
| P value | 0.01 | 0.21 | 0.76 | 0.51 | 0.62 | 0.44 |
| Former smokers | ||||||
| N | 1388 | 72 | 296 | 296 | 296 | 484 |
| Spearman correlation | −0.08 | −0.06 | −0.03 | −0.08 | −0.04 | −0.02 |
| P value | 0.003 | 0.60 | 0.57 | 0.19 | 0.49 | 0.69 |
| Never smokers | ||||||
| N | 1944 | 61 | 314 | 314 | 314 | 813 |
| Spearman correlation | −0.03 | −0.11 | 0.06 | 0.05 | −0.02 | 0.05 |
| P value | 0.13 | 0.42 | 0.27 | 0.35 | 0.76 | 0.12 |
| Participants who did not develop lung cancer | ||||||
| N | 5328 | 195 | 898 | 898 | 898 | 2072 |
| Spearman correlation | −0.05 | 0.01 | 0.02 | 0.003 | −0.05 | 0.02 |
| P value | 0.0002 | 0.87 | 0.51 | 0.93 | 0.15 | 0.27 |
| Participants who developed lung cancer | ||||||
| N | 565 | 101 | 367 | 367 | 367 | 49 |
| Spearman correlation | −0.01 | 0.05 | −0.002 | 0.03 | 0.03 | 0.06 |
| P value | 0.81 | 0.61 | 0.96 | 0.53 | 0.63 | 0.70 |
P value for partial Spearman’s rank correlations controlling for enrollment age, BMI (kg/m2), sex (in analyses including both sexes), and smoking status (current, former, or never in analyses including all smoking statuses).
Discussion
In this large study of low-income US adults, we observed some evidence of an increased risk of lung cancer incidence associated with a lower-quality diet among male former smokers and female never smokers and long-term former smokers. The strength of the associations with about an 89% difference in risk between highest and lowest quartile diet quality in male former smokers and an over twofold greater risk in never smokers with lower-quality diets, was much less than associated with smoking (where differences in risk of lung cancer mortality exceed 2000% in this population with hazard ratios exceeding 20.0 among current moderate and heavy smokers compared to never smokers [33]) and may be an over estimate of the true difference in risk due to the inability to completely eliminate all confounding by smoking, but nevertheless warrants further study because lung cancer is still the most common cause of cancer death among Americans [12]. The finding of an adverse association with lowest diet quality among male former smokers, female never smokers combined with long-term former smokers, and younger female current smokers suggests that diet quality may have a small effect on risk of lung cancer, however, the reverse in the association for older female current smokers raises caution about a causal interpretation. Aside from menopausal status and hormone replacement therapy, models among males were adjusted for the same covariates as models among females so that confounding factors should not have made a major contribution to sex differences, although sex differences in lung cancer have in the past led to speculation about hormonal and other exposure and/or response differences between men and women [34]. Interactions between sex and the other covariates included in the models were assessed and the only significant interaction was for sex by BMI, however, adding this interaction to the model did not change the HEI-10 quartile estimates. Although risk was examined across the same ranges of diet exposure, the distribution of the HEI-10 scores was significantly different between males and females with 30% of females consuming the highest quality diet while only 17% of males had HEI-10 scores in the highest quartile which may have contributed to the sex differences. However, when we calculated sex-specific quartiles and re-ran the analyses, the results were similar and the conclusions remained the same.
The HEI has been associated with lung cancer in some recent studies, although results are not consistent. In a large American cohort that was predominantly White and of higher socioeconomic status, an inverse association was found among both former and current smokers [27]. The US Multiethnic Cohort Study (MEC) and Women’s Health Initiative (WHI) also have both reported that a higher quality diet, as measured by HEIs, was inversely associated with risk of squamous cell cancers [28, 29]. Our findings were evident for lung cancer overall and not specific for squamous cell carcinoma, possibly due to sample size. One important factor that may explain some of the differences between the studies is that the HEI-10 levels in the MEC and WHI are higher on average than in the SCCS. However, similar to our study, the MEC reported an inverse association with lung cancer incidence and the WHI reported an inverse association with lung cancer mortality. Sex differences were not reported in the other studies.
High diet quality has been hypothesized to be related to cancer risk through individual and combined intakes of potentially beneficial nutrients (e.g., vitamins or fiber) and non-nutrients (e.g., polyphenols or probiotics) as well as the relatively lower intake of potentially adverse food exposures (e.g., nitrates or total and saturated fats) [5, 35–40]. These, in turn, are hypothesized to impact multiple physiological mechanisms, including inflammation and insulin resistance. In this study, we did not observe a strong relationship between the HEI-10 and multiple biomarkers previously hypothesized or observed to be associated with cancer, including lung cancer risk [41–48], which is consistent with a previous study [49]. This suggests that, for SCCS participants, the observed relationship of the HEI-10 with risks of lung cancer incidence cannot be primarily explained via these pathways. Future studies should continue to evaluate these and other relationships to better understand potential mechanisms.
The SCCS is a large cohort study, predominantly comprised of African Americans, females, and people of low socioeconomic status, funded to investigate the higher burden of disease in these groups who are often underrepresented in research, have a higher burden of disease, and have less access to healthy foods and medical treatment. Results from this study may not be generalizable to other populations. The SCCS data is primarily self-reported; therefore, misclassification error is possible. However, the FFQ and adjustment covariates such as physical activity, have been validated [18, 20, 50]. The large sample size allowed us to adjust for numerous factors related to lung cancer risk and healthy eating, however residual confounding by factors that were not measured or not included in the models cannot be ruled out.
Since smoking is a very strong risk factor for lung cancer, we attempted to control for the effects of smoking by adjusting for smoking status and intensity. However, the decreases in strength of the HEI-10 estimates observed between models without adjustment for smoking (Supplemental Table 1) and models adjusted for smoking status and intensity (Table 2) suggest some residual confounding by smoking is still likely. Effect estimates for HEI-10, a modest risk factor, could be biased if adjustment for smoking in the models was inadequate. In sensitivity analyses, we attempted to control for the residual confounding of smoking in a similar manner to previous studies among other cohorts [27–29] by additionally adjusting for packyears in analyses containing current or former smokers and the number of years since quitting smoking in analyses restricted to former smokers. After adding adjustment for packyears and for years of cessation among former smokers, differences in the results were minimal. We also analyzed never smokers alone and never smokers combined with former smokers who had quit smoking more than 15 years before enrollment. We saw significant adverse trends between low diet quality and lung cancer risk for all never smokers and all never and long-term former smokers combined and for female never smokers separately and female never and long-term former smokers, however the number of never smokers who developed lung cancer were small so the results would need to be replicated in studies with larger numbers of never smokers who developed lung cancer to determine whether HEI-10 has an effect on lung cancer risk.
In a predominantly African American cohort with low socioeconomic status, decreased risk of lung cancer incidence was observed among male former smokers and female never and long-term former smokers with higher quality diets. It is possible that non-smokers may be able to reduce their lung cancer risk by following a healthy diet, however future studies are needed to investigate the lack of consistent results by sex and smoking status and potential biological pathways underlying diet quality and risk of lung cancer. Studies with larger numbers of never smokers who develop lung cancer are needed to adequately assess the association between diet and lung cancer and remove the potential for residual confounding by smoking status. The components of the HEI-10 did not strongly influence the results, suggesting that the quality of the diet overall played a more important role than the individual food components and that future studies should focus on overall diet quality.
Supplementary information
Acknowledgements
The authors wish to thank the Southern Community Cohort Study (SCCS) team members who have contributed to the SCCS.
Author contributions
HMM and MJS conceived the work that led to the submission. DY, WZ, WJ, and QC acquired data. All authors played an important role in interpreting the results, drafted or revised the manuscript, approved the final version and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Funding
Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Numbers U01CA202979 and R01CA092447. Biomarker assays were partially supported by NIH grant P50CA090949. Biospecimens and data collection and use as well as cytokine assays were conducted by the Survey and Biospecimen Shared Resource, which is supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA68485).
Data availability
Requests for data are to be made at www.southerncommunitystudy.org.
Competing interests
WZ and MJS receive research support from Pfizer, Inc which is unrelated to the contents of this manuscript. HMM, DY, WJB, and QC declare no competing interests.
Ethics approval and consent to participate
All study participants provided written informed consent. The study was approved by the Institutional Review Board at Vanderbilt University and Meharry Medical College. The study was performed in accordance with the Declaration of Helsinki.
Consent for publication
The manuscript does not contain any individual person’s data.
Footnotes
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
The online version contains supplementary material available at 10.1038/s41416-023-02342-7.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Requests for data are to be made at www.southerncommunitystudy.org.