Abstract
Background
A high-quality diet is an important strategy for preventing chronic diseases, including cancer. The Nutrient Rich Food Score (NRFS) is a very useful index that can compare the value of key micronutrients and macronutrients per calorie. The purpose of this study is to investigate the relationship of this index with the risk of lung cancer based on gender for the first time.
Method
This paper is a hospital-based case-control study that includes 135 newly diagnosed lung cancer patient and 237 sex- and age-matched individuals in Iran. A 147-item food frequency questionnaire (147-item-FFQ) was used to assess participants’ dietary intake. Multivariate Logistic regression was used to assess the odds ratio (OR) with 95% confidence interval (CI) of lung cancer by the Nutrient Rich Food Score tertiles.
Results
After adjustment for potential confounders, a high Nutrient-Rich Food Score was associated with a reduced risk of lung cancer (OR = 0.37, 95% CI: 0.19–0.74). Consistent with the overall result, the protective association remained for men (OR = 0.22, 95% CI: 0.08–0.61), while this relationship failed to reach significant level for women (OR = 0.46, 95% CI: 0.16–1.32).
Conclusion
The results showed that a high NRFS is associated with a decrease in lung cancer risk. After stratifying by sex, the association was the same for men, but null among women.
Keywords: Diet, Diet quality, Nutrient rich food, Lung cancer
Background
In the year 2020, lung cancer, with its 2.2 million new cases and 1.8 million fatalities globally, was established as the second most widespread cancer worldwide [1]. Furthermore, it was recognized as the most common form of cancer among males on a global scale. In the female population, it was ranked as the third most prevalent, following breast and colorectal cancers [1]. Also, recent studies have indicated a significant rise in the incidence of lung cancer in Iran [2]. In addition to genetic predispositions, there exist several environmental and lifestyle determinants that can significantly augment the risk of lung cancer. These include tobacco use [3], exposure to air pollutants [4], and interactions with carcinogens such as asbestos and certain chemicals [5]. Moreover, some factors, including physical activity, alcohol consumption [6], and dietary habits [7], may be potentially associated with lung cancer risk. The literature suggests that approximately one-third of tumor occurrences could potentially be associated with dietary influences [8, 9]. It has also been shown that food quality and patterns can affect the risk of lung cancer [7, 9].
Indices such as the Nutrient Rich Foods Score (NRFS) have been formulated to quantify the nutrient density of foods, meals, and overall dietary intake based on their nutrient composition [10, 11]. The calculation of the Nutrient-Rich Foods (NRF) score involves two key components: the Nutrient-Rich (NR) score, which are derived from a variety of beneficial nutrients such as macronutrients, vitamins, and minerals, and the Limited Nutrients (LIM) index score, which is calculated based on the content of saturated fatty acids, sodium, and added sugars [10, 11]. The total NRFS is determined by subtracting the LIM score from the NR scores and provides a pure measure of dietary nutrient density [10, 11]. The NRFS indicates the importance of nutrient density, which is quantified as the amount of nutrients per calorie consumed, and posits this metric as a fundamental element of dietary guidelines. This approach recommends for the selection of foods that provide a higher concentration of essential nutrients relative to their caloric content, thereby promoting optimal health and nutrition [12, 13].
Although research on NRFS and health outcomes has progressed [14, 15], studies examining its association with different types of cancer are scarce [16, 17]. Epidemiological research has suggested that several benefit components of NRFS were associated to decreased lung cancer risk [18, 19]. To the best of our knowledge, this study is the first to investigate the association of NRFS with lung cancer risk.
Method
Subjects
This hospital-based case-control study was conducted at two prominent general hospitals, Masih Daneshvari and Ayatollah Taleghani, in Tehran Province. The case group included individuals aged 30 to 79 years diagnosed with lung cancer, confirmed pathologically and through computed tomography (CT) scans within three months prior to the interview. Exclusion criteria included a history of malignancy elsewhere or adherence to a special diet due to other conditions prior to diagnosis. The control group consisted of randomly selected patients from the same hospitals during the same period, with non-neoplastic conditions (from other hospital departments that were generally related to orthopedics, appendicitis, kidney stones, disk disorders, back pain, acute eye, nose, skin, throat disorders) and free from chronic diseases (such as heart failure, chronic kidney disease, lupus, end-stage renal disease, and end-stage liver disease), within the same age range. Controls were frequency-matched for age (within ± 10 years) and sex. From an initial pool of 400 patients (150 cases and 250 controls), those with incomplete food frequency questionnaires (FFQ) and total energy intake below 500 Kcal or above 4500 Kcal were excluded, resulting in the exclusion of 15 cases and 13 controls. The study adhered to the guidelines of the Declaration of Helsinki, and all procedures were approved by the Ethics Committee of Shahid Beheshti University of Medical Sciences (approval number: IR.SBMU.NNFTRI.REC.1402.088). Written informed consent was obtained from all participants.
Assessment of dietary intake
Dietary data were collected using a validated semi-quantitative FFQ consisting of 147 foods and beverages reflecting participants’ usual diet one year prior to diagnosis for the case group (due to the possibility of changes in dietary habits after diagnosis) or interview (control) [20]. For each item, participants were asked to indicate how many times per week or per day, based on standard portion sizes, they had eaten on average over the past year. The frequency consumption of each food item was asked daily (e.g., bread), weekly (e.g., meat) or monthly (e.g., fish) and data were converted to average daily consumption assuming one month equals 30.5 days. Reported intake was then converted to equivalent weight (e.g., grams, milligrams) per day using a household scale [21]. Then the amount of food consumption in grams was calculated by multiplying the portion size by the number of daily consumptions. Nutritionist IV software was used to calculate the daily intake of energy, macronutrients and micronutrients for the participants. Also, data from the USDA Food Composition Department were used to estimate energy and nutrient intakes for each participant. For traditional Iranian food items that are not included in the USDA Food Composition Database, we used the Iranian Food Composition Table [22].
Assessment of other variables
Additional participant information, including sociodemographic characteristics, family history of cancer, physical activity, smoking habits, alcohol consumption, opium addiction, medical history (comorbidities, medication and supplement use), lung cancer histological types, and cooking techniques, was collected through face-to-face interviews. Weight was measured with minimal clothing and a sensitivity of 100 g, while height without shoes was measured with a sensitivity of 0.1 cm. Physical activity was assessed using a valid questionnaire [23], where participants rated their daily activities such as walking, exercising, sleeping, hours spent watching television, housework, and bathing, along with reported activity intensity. Total activity was reported for 24 h, and the metabolic equivalent of tasks was calculated based on these self-reports.
NRFS calculation
The Nutrient Rich Foods (NRF) Score is a reliable tool for assessing the nutrient quality of an individual’s diet [24, 25]. It comprises two components: the Nutrient-Rich (NR) section, which accounts for a modified array of essential nutrients, and the Limiting Nutrients (LIM) section. The NRF9.3 rating calculates the aggregate of the percentage daily values (DVs) for nine key nutrients: protein, dietary fiber, vitamins A, C, E, and minerals calcium, magnesium, iron, and potassium and three nutrient to be limited: saturated fatty acids, sodium and added sugar [25]. These daily values, detailed in Table 1, adhere to FDA guidelines [26, 27], selecting nutrients that align with the FDA’s definition of nutritious foods [10], subtracting the total percentage of the recommended maximum values for three limited nutrients [25]. The NRF9.3 Score is determined using the following procedure: initially, the NRF 9.3 algorithm, derived from the Drewnowski approach, evaluates all consumed food items for each participant [28], yielding an NRF9.3 value (per 100 kcal) for each food product, as indicated by the food’s NRF9.3 score [10, 29]. Consequently, individuals with elevated NRFS exhibit a more nutritious dietary pattern compared to those with lower scores.
Table 1.
Daily reference values and maximum recommended nutrient values based on the 2000-kcal diet
| Nutrient | RDV | MRV |
|---|---|---|
| Fiber (g) | 25 | - |
| Protein (g) | 50 | - |
| Vitamin A (IU) | 5000 | - |
| Vitamin C (mg) | 60 | - |
| Vitamin E [IU (mg)] | 30 (20) | - |
| Iron (mg) | 18 | - |
| Calcium (mg) | 1000 | - |
| Potassium (mg) | 3500 | - |
| Magnesium (mg) | 400 | - |
| Saturated fat (g) | - | 20 |
| Sodium (mg) | - | 2400 |
| Sugars, added (g) | - | 50 |
RDV: Reference daily value, MRV: Maximum recommended value
Statistical analysis
The analysis of the data was conducted using the Statistical Package for the Social Sciences, version 26. To assess the normality of the data, the Kolmogorov-Smirnov test was utilized. The baseline characteristics of the participants were displayed as median (IQR) or mean ± SD for quantitative variables and frequency and percentage for qualitative variables. The basic characteristics of case and control groups were compared using the chi-square test for categorical data, and the independent t-test or Mann-Whitney U test for continuous data, accordingly. The assessment of dietary intakes among the tertiles of the NRFS utilized One-way ANOVA for parametric variables, displayed as mean ± SD, and the Kruskal-Wallis test for non-parametric variables, presented as median (IQR). Nutrient Rich Food score was classified into 3 tertiles based on the distribution between the control groups. Factors such as age, body mass index (BMI), gender, smoking habits, alcohol use, opium addiction, family history of cancer, existing comorbidities, physical activity, total energy consumption, vitamin supplement intake (yes/no) and prevalent cooking methods were acknowledged as possible confounding variables and were incorporated into the analytical models. A multivariate logistic regression model was used, in which all potential confounders were simultaneously entered based on clinical relevance and prior literature. The outcomes were expressed as odds ratios (OR) with 95% confidence intervals (CI), and a P-value of less than 0.05 was deemed to indicate statistical significance.
Results
Baseline characteristics of participants have been previously reported, and are presented here for completeness [30]. The socio-demographic and life style characteristics of 135 lung cancers and 237 controls were presented in Table 2. In the frequency-matched study design, both cases and controls had the same distribution in terms of age and gender. There was no statistically significant difference between the cases and controls in terms of education level, marital status and energy intake. However, cancer cases were more likely when the patients lived in rural areas, had smoking habits or opium addiction, and had family history of cancer in first degree relatives. Conversely, the data presented in the table indicates that the control group not only exhibited a higher Body Mass Index (BMI) in comparison to the cancer group, but was also engaged in elevated levels of physical activity. Among the 135 lung cancer cases, cancer subtype information was available for 128 patients: 71 had adenocarcinoma, 34 had squamous cell carcinoma, and 23 had small cell carcinoma.
Table 2.
General characteristics of participants (n = 372)
| Variables | Cases (n = 135) | Controls (n = 237) | P-value, ‡ |
|---|---|---|---|
| Age (Mean ± SD) | 56.38 ± 11.11 | 55.43 ± 9.47 | 0.298 |
| Gender (male) n (%) | 83 (61.5) | 137 (57.8) | 0.488 |
| BMI (Mean ± SD) | 25.41 ± 4.68 | 26.81 ± 3.97 | < 0.0001‡ |
|
Residence n (%) Urban Rural |
109 (80.7) 26 (19.3) |
213 (90.3) 20 (8.5) |
0.014‡ |
|
Educational level n (%) Illiterate Low education High education |
23 (17) 98 (72.6) 14 (10.4) |
30 (12.7) 170 (72) 34 (14.14) |
0.340 |
| Smoking (yes) n (%) | 59 (43.7) | 43 (18.1) | < 0.0001‡ |
| Opium Addiction (yes) n (%) | 27 (20) | 14 (5.9) | < 0.0001‡ |
| Comorbidity (yes) n (%) | 63 (46.7) | 38 (16) | < 0.0001‡ |
| Family history of cancer in first degree (yes) n (%) | 65 (48.1) | 77 (32.5) | 0.003‡ |
|
Common ways of cooking food n (%) Fried Boiled Grilled Steam cook Combined |
28 (20.7) 13 (9.6) 1 (0.7) 1 (0.7) 92 (68.1) |
51 (21.5) 80 (33.8) 5 (2.1) 3 (1.3) 98 (41.4) |
< 0.0001‡ |
| Physical activity (Mean ± SD) (met/h/day) | 37.29 ± 10.91 | 39.30 ± 5.90 | 0.008‡ |
| Energy intake (Mean ± SD) | 2482.81 ± 471.43 | 2345.52 ± 493.34 | 0.960 |
|
Marital Status Single n (%) Married n (%) Divorced n (%) Widowed n (%) |
7 (5.2) 123 (91.1) 2 (1.5) 3 (2.2) |
9 (3.8) 218 (92) 1 (0.4) 6 (2.5) |
0.504 |
| Supplement use (yes) n (%) | 17 (12.6) | 55 (23.2) | 0.013‡ |
|
Cancer subtype Adenocarcinoma (n) Squamous cell carcinoma (n) Small cell carcinoma (n) |
71 34 23 |
- - - |
- - - |
Continuous values are shown as mean ± standard deviation. Categorical values are shown as number (%); MET, metabolic equivalent; BMI, body mass index; Independent t-test or Mann-Whitney was used for continuous variables; χ2 test was used for categorical variables; ‡p-values are statistically significant.
Table 3 presents the dietary intakes of study participants according to tertiles of the NRFS. Based on this table, participants with the highest third of the NRFS have a higher intake of MUFA, fish, fruits, vegetables, legumes, total fiber, Vitamin A, Vitamin K, Vitamin E, Vitamin C, calcium, iron, potassium, magnesium, copper, manganese, riboflavin, niacin, Pantothenic Acid, Vitamin B6, Vitamin B9 and biotin and lower intake of red meat, PUFA, SAFA, sodium and total fat.
Table 3.
Dietary intakes of study participants across tertiles of the NRFS
| Dietary intake | T1 (n = 124) | T2 (n = 124) | T3 (n = 124) | P-value |
|---|---|---|---|---|
| Protein (g/day) | 76.02 (29.86) | 77.62 (25.30) | 80.16 (21.28) | 0.103 |
| Carbohydrate (g/day) | 296.12 (99.96) | 288.04 (105.13) | 276.64 (78.96) | 0.277 |
| Total fat (g/day) | 116.20 (43.54) | 99.65 (30.74) | 94.10 (32.71) | < 0.0001 |
| Cholesterol (mg/day) | 236.85 (140.75) | 246.13 (123.72) | 223.01 (139.97) | 0.439 |
| SAFA (g/day) | 30.80 (12.46) | 25.36 (12.08) | 22.26 (8.75) | < 0.0001 |
| MUFA (g/day) | 46.15 (15.31) | 39.88 (13.43) | 38.43 (14.04) | < 0.0001 |
| PUFA (g/day) | 30.15 (16.17) | 27.03 (8.39) | 26.87 (6.87) | 0.002 |
| Red meat(g/day) | 28.7 (34.63) | 24.26 (27.53) | 18.86 (22.44) | 0.004 |
| Fish (g/day) | 7.54 (13.81) | 7.54 (13.88) | 15.20 (20.13) | 0.002 |
| Poultry (g/day) | 31.71 (41.23) | 40.71 (31.71) | 47.57 (43.07) | 0.357 |
| Fruits (g/day) | 185.83 (102.93) | 226.81 (117.94) | 238.81 (115.94) | < 0.0001 |
| Vegetables (g/day) | 120.51 ± 67.53 | 143.72 ± 63.03 | 177.90 ± 66.38 | < 0.0001 |
| Legumes (g/day) | 37.42 (21.23) | 43.16 (27.71) | 45.35 (24.23) | 0.002 |
| Whole grains (g/day) | 97.09 (86.07) | 99.42 (83.99) | 92.31 (78.23) | 0.723 |
| Refined grains (g/day) | 291.46 ± 129.15 | 300.00 ± 136.12 | 283.40 ± 172.06 | 0.505 |
| Total Fiber (g/day) | 31.39 (13.89) | 35.28 (14.82) | 39.24 (15.73) | < 0.0001 |
| Added sugar (g/day) | 112.10 (43.93) | 109.72 (42.71) | 107.16 (39.46) | 0.091 |
| Vitamin A (IU/day) | 2605.61 (1243.46) | 3086.76 (1501.59) | 3957.11 (2023.46) | < 0.0001 |
| Vitamin K (mg/day) | 196.84 (85.47) | 215.31 (127.71) | 308.48 (149.53) | < 0.0001 |
| Vitamin E (mg/day) | 25.09 (9.59) | 29.16 (10.14) | 30.86 (7.60) | < 0.0001 |
| Vitamin D (µg/day) | 1.08 (1.65) | 1.25 (1.84) | 1.30 (1.87) | 0.386 |
| Vitamin C (mg/day) | 71.43 (28.68) | 90.77 (29.20) | 108.16 (46.25) | < 0.0001 |
| Calcium (mg/day) | 914.98 (341.04) | 1014.49 (395.48) | 1124.60 (341.8) | < 0.0001 |
| Iron (mg/day) | 24.71 (8.38) | 25.95 (12.69) | 32.35 (11.76) | < 0.0001 |
| Potassium (mg/day) | 3096.12 ± 751.20 | 3445.50 ± 806.65 | 3825.40 ± 993.63 | < 0.0001 |
| Magnesium (mg/day) | 355.71 (114.79) | 376.07 (129.98) | 398.66 (126.94) | < 0.0001 |
| Sodium (mg/day) | 5298.45 (1101.63) | 5073.72 (1707.30) | 5028.60 (1978.63) | 0.004 |
| Phosphorus (mg/day) | 1309.74 (437.36) | 1367.47 (494.16) | 1400.14 (407.65) | 0.072 |
| Zinc (mg/day) | 11.55 (3.96) | 11.45 (3.45) | 11.41 (3.31) | 0.666 |
| Selenium (mg/day) | 103.39 (41.60) | 104.32 (39.26) | 102.03 (37.92) | 0.764 |
| Copper (mg/day) | 1.40 (0.40) | 1.54 (0.65) | 1.61 (0.57) | < 0.0001 |
| Manganese (mg/day) | 7.18 (2.33) | 7.62 (2.87) | 8.32 (2.64) | < 0.0001 |
| Chromium (mg/day) | 0.0971 (0.09) | 0.0994 (0.08) | 0.0923 (0.08) | 0.722 |
| Thiamin (mg/day) | 1.72 (0.55) | 1.78 (0.60) | 1.76 (0.49) | 0.296 |
| Riboflavin (mg/day) | 1.56 (0.61) | 1.75 (0.67) | 1.84 (0.64) | 0.001 |
| Niacin (mg/day) | 20.51 (8.70) | 21.60 (7.12) | 22.86 (5.76) | 0.037 |
| Pantothenic Acid (mg/day) | 4.68 (1.61) | 4.89 (1.67) | 4.94 (1.42) | 0.035 |
| Vitamin B6 (mg/day) | 1.72 ± 0.40 | 1.84 ± 0.44 | 1.96 ± 0.41 | < 0.0001 |
| Vitamin B9 (mg/day) | 466.10 (140.93) | 485.90 (173.16) | 515.32 (144.81) | 0.002 |
| Vitamin B12 (mg/day) | 3.01 (1.44) | 3.12 (1.53) | 2.89 (1.20) | 0.522 |
| Biotin (mg/day) | 23.68 (12.49) | 25.54 (11.45) | 26.27 (11.00) | 0.002 |
Data are presented as median (interquartile range) or mean ± standard deviation. Kruskal-Wallis test was used for estimate p-value of non-parametric variables. One-way ANOVA test was used for estimate p-value of parametric variables. SAFA Saturated fatty acid; MUFA Monounsaturated fatty acid; PUFA Polyunsaturated fatty acid
When participants’ NRF scores were divided into tertiles (Table 4), we found that vitamin C, calcium, potassium, and magnesium were associated with a lower risk of lung cancer, whereas other NRF components showed no significant relationship.
Table 4.
Multivariable-adjusted odds ratios (95% CIs) for lung cancer across tertiles categories in each component for NRFS
| T1 OR (95% CI) |
T2 OR (95% CI) |
T3 OR (95% CI) |
P-value | |
|---|---|---|---|---|
| Lung cancer (Control/Case) | 79/45 | 80/44 | 78/46 | |
| Fiber (gr/day) | ||||
| Adjusted Model§ | 1.00 (ref) | 0.68 (0.35–1.30) | 0.82 (0.43–1.56) | 0.075 |
| Lung cancerl (Control-Case) | 71/53 | 71/53 | 95/29 | |
| Vitamin A (IU/day) | ||||
| Adjusted Model§ | 1.00 (ref) | 1.05 (0.57–1.95) | 0.58 (0.29–1.13) | 0.113 |
| Lung cancer (Control/Case) | 58/66 | 86/38 | 93/31 | |
| Vitamin C (mg/day) | ||||
| Adjusted Model§ | 1.00 (ref) | 0.45 (0.24–0.84) | 0.35 (0.18–0.68) | 0.002 |
| Lung cancer (Control/Case) | 76/48 | 67/57 | 94/30 | |
| Vitamin E (mg/day) | ||||
| Adjusted Model§ | 1.00 (ref) | 1.35 (0.72–2.51) | 0.62 (0.29–1.31) | 0.216 |
| Lung cancer (Control/Case) | 61/63 | 84/40 | 92/32 | |
| Calcium (mg/day) | ||||
| Adjusted Model§ | 1.00 (ref) | 0.52 (0.28–0.97) | 0.40 (0.21–0.77) | 0.006 |
| Lung cancer (Control/Case) | 73/51 | 77/47 | 87/37 | |
| Iron (mg/day) | ||||
| Adjusted Model§ | 1.00 (ref) | 0.84 (0.45–1.56) | 0.61 (0.32–1.17) | 0.141 |
| Lung cancer (Control/Case) | 55/68 | 79/48 | 102/22 | |
| Potassium (mg/day) | ||||
| Adjusted Model§ | 1.00 (ref) | 0.54 (0.28–1.02) | 0.22 (0.11–0.43) | < 0.0001 |
| Lung cancer (Control/Case) | 51/73 | 82/42 | 104/20 | |
| Magnesium (mg/day) | ||||
| Adjusted Model§ | 1.00 (ref) | 0.42 (0.22–0.80) | 0.15 (0.07–0.31) | < 0.0001 |
| Lung cancer (Control/Case) | 90/34 | 83/41 | 64/60 | |
| SAFA (gr/day) | ||||
| Adjusted Model§ | 1.00 (ref) | 1.08 (0.56–2.07) | 1.33 (0.69–2.58) | 0.386 |
| Lung cancer (Control/Case) | 61/63 | 87/37 | 89/57 | |
| Added sugar (gr/day) | ||||
| Adjusted Model§ | 1.00 (ref) | 1.87 (0.99–3.51) | 0.89 (0.45–1.75) | 0.754 |
| Lung cancer (Control/Case) | 89/38 | 70/54 | 81/43 | |
| Sodium (mg/day) | ||||
| Adjusted Model§ | 1.00 (ref) | 0.84 (0.41–1.71) | 1.18 (0.60–2.30) | 0.623 |
§Adjusted for age, BMI, sex, smoking status, alcohol consumption, addiction, cancer family history, comorbidity, physical activity, energy intake, vitamin supplementation use (yes/no) and common ways of cooking food.
Odds ratios and 95% confidence intervals for lung cancer risk based on tertile of NRFS and subgroup analysis stratified by gender are presented in Table 5. After adjusting for confounding variables such as age, body mass index (BMI), gender, smoking habits, alcohol use, opium addiction, family history of cancer, comorbidities, physical activity, total energy consumption, vitamin supplement intake (yes/no), prevalent cooking methods, and place of residence, an inverse association has been seen between NRFS and lung cancer risk (OR = 0.37, 95% CI: 0.19–0.74). After stratification by gender, the association between NRFS and lung cancer among women was null (OR = 0.46, 95% CI: 0.16–1.32); On the other hand, adherence to the high score of NRF seems to play a role in reducing lung cancer in men (OR = 0.22, 95% CI: 0.08–0.61).
Table 5.
Multivariable-adjusted odds ratios (95% CIs) for lung cancer across tertiles categories of NRFS, stratified by gender
| T1 OR (95% CI) |
T2 OR (95% CI) |
T3 OR (95% CI) |
P-value | |
|---|---|---|---|---|
| Lung cancer (Control/Case) | 60/64 | 81/43 | 96/28 | |
| Model 1† | 1.00 (ref) | 0.49 (0.29–0.81) | 0.26 (0.15–0.45) | |
| Model 2‡ | 1.00 (ref) | 0.51 (0.29–0.89) | 0.29 (0.16–0.52) | |
| Model 3§ | 1.00 (ref) | 0.56 (0.30–1.05) | 0.37 (0.19–0.74) | 0.005 |
| Female (Control-Case) | 26/19 | 37/18 | 37/15 | |
| Model 1† | 1.00 (ref) | 0.65 (0.28–1.48) | 0.56 (0.24–1.31) | |
| Model 2‡ | 1.00 (ref) | 0.61 (0.26–1.43) | 0.59 (0.25–1.41) | |
| Model 3§ | 1.00 (ref) | 0.59 (0.22–1.57) | 0.46 (0.16–1.32) | 0.152 |
| Male (Control-Case) | 34/45 | 44/25 | 59/13 | |
| Model 1† | 1.00 (ref) | 0.38 (0.19–0.76) | 0.15 (0.07–0.33) | |
| Model 2‡ | 1.00 (ref) | 0.38 (0.17–0.83) | 0.14 (0.06–0.34) | |
| Model 3§ | 1.00 (ref) | 0.49 (0.19–1.22) | 0.22 (0.08–0.61) | 0.004 |
†Model 1: Adjusted for age. ‡ Model 2: Further adjusted for BMI, sex, smoking status, alcohol consumption, addiction. § Model 3: Further adjusted for cancer family history, comorbidity, physical activity, energy intake, vitamin supplementation use (yes/no) and common ways of cooking food
Discussion
Based on current knowledge, this study attempts to be the first exploration of the link between NRFS and susceptibility to lung cancer. Findings show that a high NRFS is inversely related with lung cancer risk, a relationship that remains statistically significant even after adjusting for potential confounders. After further analysis by gender, the results remained the same for the male group. However, the relationship between the NRFS and the risk of lung cancer in the female group is not statistically significant. Our findings are consistent with previous evidence that diet quality plays an important role in lung cancer risk. In our previous study, a higher glycemic index was associated with an increased risk of lung cancer, while better carbohydrate quality showed a protective effect [30]. Similarly, recent meta-analysis data confirm that healthy dietary patterns such as the Mediterranean and DASH diets and healthy eating index (HEI) are consistently associated with a reduced risk of lung cancer, while Western and inflammatory diets are associated with a higher risk [7]. These converging results reinforce the importance of nutrient-dense dietary patterns, such as those documented by the NRFS, in lung cancer prevention.
Consistent with the findings of the present research, an observational cohort study conducted in China demonstrated that an elevated score of NRF was associated with improved recovery in patients with ovarian cancer [16]. In addition, a case-control study conducted in Iran with a scale similar to the present study showed that a high score of NRF was associated with an 8% reduction in the risk of colorectal cancer [17].
Dietary patterns are related to the tumorigenic process [9]. In addition to regulating caloric intake to reduce obesity- a key factor in tumorigenesis [31, 32]- following a diet rich in vital micronutrients and macronutrients are essential to reduce the risk of tumorigenesis [33]. Various observational studies have investigated the relationship between individual food components of the NRFS and lung cancer risk [34–40].
It has been revealed that dietary fiber intake can reduced the risk of lung cancer [34]. Dietary fiber is indigestible by humans, but it can be fermented by gut microbiota, resulting in the production of short-chain fatty acids [41]. Recent research shows that the positive effects of short-chain fatty acids on the immune system and metabolism go beyond the gut and affect various organs, including the lungs [42]. Experimental research has demonstrated that a diet rich in fiber can enhance the immune environment within the lungs by altering the composition of both gut and lung microbiota [42]. In addition, dietary fiber can lower the risk of lung cancer by reducing inflammation and improving insulin sensitivity [43, 44].
The implications of saturated fatty acids in various forms of cancer have been investigated [45]. Carcinogenic potential may result from activation of nuclear factor kappa B, protein kinase C, and mitogen-activated protein kinases, leading to activation of inflammatory genes in white adipose tissue and immune cells [46]. Added sugar is another limited food item in the NRFS. This causes a high glycemic load, which leads to excessive weight gain, inflammation, and insulin resistance [47]. Studies have shown that insulin resistance can increase the risk of lung cancer [44].
Meta-analysis and review literatures suggest that dietary intake of vitamins E, C, and A may help reduce the risk of lung cancer [38, 39, 48]. The observed inverse association between vitamin E and C intake and lung cancer risk can be explained by a range of underlying mechanisms. Known for their strong antioxidant capabilities [49, 50] and anti-inflammatory properties [51], these vitamins play an important role in protecting cell structures and DNA from oxidative damage. Vitamin C, which acts as a strong antioxidant, can eliminate reactive oxygen species (ROS) and thus prevent DNA damage and the development of oncogenic processes [50]. Vitamin E, also has the potential to decrease nitrite levels and hinder the formation of carcinogenic nitroso amides and nitroso amines [52, 53]. Additionally, vitamin E may play a role in preventing carcinogenesis by downregulating the nuclear factor (NF)-κB signaling pathway, thereby inhibiting cell proliferation and angiogenesis while inducing apoptosis [54, 55].
Also, a meta-analysis and review study found that dietary magnesium intake could be associated with a reduced risk of lung cancer [18]. In addition to DNA replication, magnesium (Mg) has a multifaceted role in physiological processes such as energy metabolism, membrane stabilization, protein synthesis, cytoskeleton activation, and antioxidant defense [56]. In the field of oncology, sufficient physiological concentration of magnesium is effective in facilitating DNA repair and maintaining genomic integrity [56, 57]. Regarding dietary calcium, however, the latest pooled analysis found no association between dietary calcium and lung cancer risk [58], but some mechanisms are able to explain the current findings. Calcium mediated reactive oxygen species, and heighten cytoplasmic Ca2 + levels lead to mitochondrial and nuclear invasion, which can affect DNA stability [59].
The results of gender subgroup analysis showed that adherence to NRFS in the female group was not associated with a reduction in the risk of lung cancer. A meta-analysis study found that although heme iron was not associated with the risk of lung cancer in men, it could increase the risk of lung cancer by 14% in women [35]. While iron is an essential element, it also acts as a strong oxidizing agent. Its carcinogenic potential is attributed to its ability to generate reactive oxygen species (ROS), which can damage tissues and DNA [60]. It has been hypothesized that the estrogen-iron axis may exacerbate iron overload and its subsequent clinical manifestations, such as cancer, especially in women [61]. The presence of these mechanisms can lead to the hypothesis in our study that the reason for the neutralization of the protective effect of NRFS in women group is related to dietary iron. Further studies are needed to clarify this hypothesis.
As the same way, previous studies have also shown that high potassium intake is associated with a reduced risk of lung cancer and high sodium intake is associated with an increased risk of lung cancer [40]. Potassium can play a role in cancer prevention by improving the function of T cells [62]. However, the biological mechanisms of the relationship between lung cancer risk and sodium intake remain unknown [40].
The results of the present study showed that high score of nutrient-rich food can play a role in reducing the risk of lung cancer (Fig. 1). A meta-analysis and review study found that adherence to a Mediterranean diet, which is rich in vitamins and dietary fiber and low in added sugar, saturated fatty acid and sodium, was associated with a reduced risk of lung cancer [7]. On the other hand, following a Western and inflammatory diet that contains high amounts of refined grains, saturated fatty acids, and sodium has been implicated in increasing the risk of lung cancer [7]. The NRFS, which is derived from the percent Daily Values (DVs) for nine essential nutrients per 2000 kcal of food, serves as a measure of the nutrient density of different foods in food groups. Consequently, NRFS may serve as an indicator of dietary potential to reduce the risk of chronic diseases, including inflammatory diseases and cancer.
Fig. 1.
Mechanistic Pathways of NRF9:3 Components in Lung Cancer. This study founds a high NRFS inversely associated with lung cancer risk. Dietary fiber may lower lung cancer risk by boosting SCFA production, modulating immune responses, and enhancing insulin sensitivity. Vitamins A, E and C act as antioxidants, and vitamin E reduces DNA damage and lung cancer risk by inhibiting nitrite products and NF-kappa B activity, and affects angiogenesis and cell proliferation. Magnesium and calcium use distinct biochemical pathways to stabilize DNA and prevent damage. High iron intake may elevate lung cancer risk via reactive oxygen species (ROS) generation. Saturated fats and added sugars may increase the risk of lung cancer by stimulating inflammation, DNA damage via NF-kappaB, and insulin resistance
This research acknowledges certain limitations, particularly its focus on Iranian demographics, which did not include diverse racial spectrums or genetic variances. In addition, the retrospective nature of this study, relying on participants’ recollections, could lead to overestimation or underestimation of dietary intake. To reduce these biases, a validated food frequency questionnaire (FFQ) was used to assess dietary intake, supplemented by confirmation from first-degree relatives when participant data were incomplete. Additionally, the lack of a validation cohort represents a limitation in terms of reproducibility. While our findings are internally consistent, future research should include independent cohorts to confirm these associations and enhance generalizability. Although cancer subtype data were available for most cases and reported, information on tumor stage and grade was incomplete and therefore not included in the analysis. Future research should incorporate these clinical parameters to better understand phenotype-specific dietary associations. Another limitation of our study is that smoking was measured only as ever versus never, which precludes adjustment for pack-years. As a result, residual confounding from smoking intensity and duration may persist. This drawback also applies to alcohol and drug use. Future studies should collect detailed smoking history (e.g., pack-years) to better control for this key confounding factor. To confirm these findings and formulate appropriate dietary guidelines for people susceptible to lung cancer, it is necessary to extend the research to wider populations and different ethnicities, taking into account genetic factors.
Conclusion
The current results showed that a high NRFS was associated with a reduction in lung cancer. After stratifying by gender, this association remained the same for men, but was ineffective among women.
Acknowledgements
We are thankful to the National Nutrition and Food Technology Research Institute (NNFTRI) of Shahid Beheshti University of Medical Sciences, Tehran, Iran, and all other investigators, staff, and participants of this study. Also, the grammar and sentence fluency of this article were enhanced with the aid of an AI tool.
Abbreviations
- NRFS
Nutrient Rich Food Score
- FFQ
Food Frequency Questionary
Authors’ contributions
M.M, E.H, Me.M and SH. S contributed in study design. M.M, Me.M and A.P had parts in data collection. M.M is involved in data analysis and drafted the manuscript. M.M, F.A, A.B, S.H, V.H and E.H reviewed the paper and revised it to the final format. All authors read and approved the final manuscript.
Funding
This work was supported by the Shahid Beheshti University of Medical Sciences.
Data availability
The datasets generated and/or analyzed during the current study are not publicly available due confidential and private information but are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
The study was approved by the ethics committee for Research at Shahid Beheshti University of Medical Sciences (approval number: IR.SBMU.NNFTRI.REC.1402.088).
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Sharareh Seifi, Email: sh_seifi@yahoo.com.
Ehsan Hejazi, Email: Ehsanhejazi@sbmu.ac.ir.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and/or analyzed during the current study are not publicly available due confidential and private information but are available from the corresponding author on reasonable request.