Abstract
Background
Results from studies investigating the association between ultra-processed foods (UPFs) and breast cancer are scarce and, in some cases, contradictory. Therefore, we aimed to evaluate the association between the intake of processed foods (PFs) and UPFs with the risk of breast cancer in Iranian women.
Methods
The present case (n = 133) - control (n = 266) study was carried out at two general hospitals in Tehran, Iran. A 168-item semi-quantitative food frequency questionnaire was used to assess the participants’ dietary intake. Also, the NOVA classification was used to identify PFs and UPFs. The association between PFs and UPFs with the odds of breast cancer was analyzed using logistic regression models.
Results
According to Model 1 of conditional logistic regression, the odds of breast cancer were higher in the last tertile of UPFs than in the first tertile (odds ratio (OR) = 1.930; 95% confidence interval (CI): 1.080–3.449). In Model 2, no significant association was observed between the second and last tertiles of PFs and UPFs with the odds of breast cancer compared to the reference tertile. Also based on menopause status, the odds of breast cancer increased in the last tertile only among premenopausal women in Model 2 (OR = 3.656; 95% CI: 1.326–10.079).
Conclusions
This study demonstrated that higher consumption of UPFs is associated with higher odds of breast cancer in premenopausal women.
Keywords: Food, Processed, Breast neoplasms, Iran
Introduction
Breast cancer was the most commonly diagnosed cancer, with 2.26 million new cases in 2020 [1]. This cancer is the most common cancer among Iranian women with an age-standardized incidence rate of 35.8 per 100,000 people [2]. Genetic and lifestyle/environmental factors are involved in the development of breast cancer [3]. It is estimated that 90–95% of cancer cases are related to environmental and lifestyle factors [4]. Diet modification and lifestyle changes are suggested to prevent one-third of breast cancer-related morbidity and mortality [5]. Diet-related factors are believed to contribute to approximately 30% of cancer cases in developed countries [6], and healthy/prudent dietary patterns can reduce the risk of breast cancer by 11% [7].
Food processing has advanced significantly due to the industrialization and globalization of food systems [8]. Considering the degree of food processing, the NOVA classification categorizes foods into four groups: minimally processed, processed culinary ingredients, processed foods (PFs), and ultra-processed foods (UPFs) [9]. UPFs are affordable, easy to access, palatable, and microbiologically safe [10] and contribute to 25–50% of people’s energy intake in high- and middle-income countries [11]. However, these foods are usually energy-dense, with high sugar, salt, and saturated fatty acids, and low micronutrients and fiber, so they are considered foods with poor nutritional values [9, 12, 13]. In addition, these foods can contain additives, including sodium nitrites and titanium dioxide, newly formed substances, including heterocyclic amines, aromatic polycyclic hydrocarbons, and acrylamides, and substances from packaging such as bisphenol A [14–17].
Results from studies investigating the association between UPFs and breast cancer are scarce and, in some cases, contradictory (15–18). The French NutriNet-Santé prospective cohort study and a multicentric population-based case-control study (MCC) demonstrated that a higher intake of UPFs is associated with an increased risk of breast cancer [18, 19]. Many studies indicate that the increased consumption of UPFs is a primary contributor to the obesity epidemic [18–20]. Obesity has a complicated relationship with both breast cancer risk and the clinical behavior of the established disease [21]. On the other hand, studies conducted among women from South Africa and Spain did not show any significant association between UPFs and the risk of breast cancer [20, 21]. To address the discrepancies between the studies, we aimed to evaluate the association between the intake of PFs and UPFs with the risk of breast cancer in Iranian women.
Methods
Study participants
The present study was conducted at two general hospitals in Tehran, Iran and randomly selected by convenient sampling method. The sample size was calculated by the study of Ching et al. (odds ratio (OR) = 0.47, α error = 0.05, and β error = 20%) [22]. In the current research, 136 women aged 30 to 65 years, whose breast cancer was recently confirmed by histology, were selected. Also, 272 females in the control group were admitted to the same hospitals for a broad spectrum of non-neoplastic diseases unrelated to alcohol abuse, smoking, and long-term dietary modifications (1 case − 2 controls). The conditions of the participants from the control group included acute surgical conditions (such as appendicitis, inguinal hernia, and kidney stones), trauma and orthopedic conditions, disc disorders, and eye, nose, ear, or skin disorders. For the matching process, the control group participants were age-matched to the cases within a five-year range. Seven participants (5 controls and 2 cases) were excluded from the analysis because their energy intake was outside the range of ± 3 standard deviations (SDs) from the mean energy intake separately in each case and control group, and 2 participants were excluded due to missing data (1 control and 1 case). All protocols and procedures of the current study were approved by the medical research and ethics committee of Shiraz University of Medical Sciences. Also, written informed consent was obtained from all patients. Some details of the present study were published previously [23, 24].
Dietary assessment
A 168-item semi-quantitative food frequency questionnaire (FFQ) was used to assess the participants’ dietary intake. The questionnaires included participants’ dietary intake one year before the interview for the control group and one year before the cancer diagnosis for the case group. The questionnaire used in this study was based on the common foods consumed by Iranians and had high reliability and reproducibility in this population [25, 26]. A validated food album [27] was provided to patients along with a set of household measuring items (e.g., cups, tablespoons, teaspoons, bowls, plates, spatulas, and glasses) to facilitate the estimation of food type and portion size. The portion size of each food item was converted into grams, and then the consumption of each food was determined by the portion size multiplied by the frequency of daily intake. The composition table of Iranian food nutrients [28] and the data of food compositions from the United States Department of Agriculture (USDA) were used to calculate foods’ energy and nutrient content.
The NOVA classification was used to identify PFs and UPFs [29, 30]. Foods and beverages that were identified as PFs and UPFs included [31] baguette bread, toast bread, crackers, cookies, Yazdi cake, homemade cakes, other cakes, biscuits, pastries, cream sweets, gaz, sohan, noghl, chocolate, donuts, caramel cream, candies, pizza, meat products, kielbasa, sausage, hamburger, French fries, puff, chips, industrial beverages, soft drinks, cola, industrial jams, packaged salty snacks, milk sweetened with sugar, cacao milk, yogurt cream, cream cheese, traditional ice cream, non-traditional ice cream, gravies, margarine, sauces, ketchup, mayonnaise, etc. To determine the contribution of each subgroup of UPFs in the total consumption of UPFs, the mean daily consumption was divided by the total daily UPF intake and then multiplied by 100.
Other measurements
All measurements and data collection were carried out by trained nutritionists. Participants were weighed to the nearest 0.1 kg using a digital scale (Seca, Germany) while wearing lightweight clothing and without shoes. In addition, height was measured using a non-elastic measuring tape installed on the wall with an accuracy of 0.5 cm. Body mass index (BMI) was calculated by dividing weight (kilograms) by the square of height (meters).
The socio-demographic, lifestyle, and clinical information of the participants was collected through a checklist. This information included age (years), age at the first pregnancy (years), abortion history (yes, no), breastfeeding history (months), menopausal status (premenopausal, postmenopausal), history of taking oral contraceptive pills (yes, no), family history of breast cancer (yes, no), wearing a bra during the day (yes, no) and at night (yes, no), family history of cancer (yes, no), smoking (yes, no), and history of supplement use (yes, no). Also, physical activity was evaluated using a valid and reliable questionnaire [32], and questions changed to metabolic equivalents of tasks (METs)-hours per day.
Statistical analysis
In this study, all analyses were performed using SPSS software (version 26.0, SPSS Inc. Chicago IL, USA) and STATA (version 17). The Kolmogorov-Smirnov test was used to evaluate the normality of the data. At first, the intake of PFs and UPFs was calculated based on energy percent and then converted to tertile. For the basic characteristics of the subjects (continuous and categorical variables), independent samples T-test or Mann-Whitney test and chi-square test were used, respectively. The association between the intake of PFs and UPFs and breast cancer risk was analyzed using conditional logistic regression models. The role of potential confounding variables (BMI (kg/m2), marriage age (years), age at the first pregnancy (years), breastfeeding time (months), fiber intake (g/day), abortion history (no/yes), family history of cancer (no/yes), family history of breast cancer (no/yes), wearing a bra during the day (less than 12 h/more than 12 h), wearing a bra at night (no/yes), vitamin D supplement (no/yes), omega-3 supplement (no/yes), and herbal drugs (no/yes)) was adjusted (adjusted for variables with p-value < 0.25 based on Table 3, and energy was not added in the adjusted model, because the intake of PFs and UPFs was calculated based on energy percent). The OR and their 95% confidence intervals (CIs) were calculated. P-values less than 0.05 were considered significant.
Table 3.
Association between some baseline variables and the risk of breast cancer
Variables | OR | 95% CI | P-value |
---|---|---|---|
Marriage age (years) | 1.033 | 0.996–1.071 | 0.079 |
Age at the first pregnancy (years) | 1.041 | 1.003–1.079 | 0.034 |
BMI (kg/m2) | 1.035 | 0.997–1.075 | 0.069 |
Breastfeeding time (months) | 0.996 | 0.991–1.002 | 0.158 |
Physical activity (MET-h/day) | 1.007 | 0.968–1.047 | 0.728 |
Fiber intake (g/day) | 0.988 | 0.975–1.001 | 0.070 |
Menopausal status | |||
Pre-menopausal | Ref. | Ref. | Ref. |
Post-menopausal | 1.589 | 1.051–2.430 | 0.028 |
Abortion history | |||
No | Ref. | Ref. | Ref. |
Yes | 1.576 | 1.017–2.441 | 0.042 |
Family history of cancer | |||
No | Ref. | Ref. | Ref. |
Yes | 1.642 | 1.021–2.640 | 0.041 |
Family history of breast cancer | |||
No | Ref. | Ref. | Ref. |
Yes | 1.901 | 0.816–4.431 | 0.137 |
Smoking | |||
No | Ref. | Ref. | Ref. |
Yes | 0.889 | 0.269–2.942 | 0.847 |
Wearing a bra during the day | |||
Less than 12 h | Ref. | Ref. | Ref. |
More than 12 h | 2.287 | 1.171–4.467 | 0.015 |
Wearing a bra at night | |||
No | Ref. | Ref. | Ref. |
Yes | 1.508 | 0.920–2.473 | 0.104 |
OCP use | |||
No | Ref. | Ref. | Ref. |
Yes | 0.803 | 0.529–1.218 | 0.302 |
Multivitamin-mineral supplements | |||
No | Ref. | Ref. | Ref. |
Yes | 0.878 | 0.372–2.076 | 0.767 |
Vitamin D supplement | |||
No | Ref. | Ref. | Ref. |
Yes | 0.556 | 0.320–0.966 | 0.037 |
Omega-3 supplement | |||
No | Ref. | Ref. | Ref. |
Yes | 0.483 | 0.216–1.083 | 0.077 |
Herbal drugs | |||
No | Ref. | Ref. | Ref. |
Yes | 0.620 | 0.372–1.036 | 0.068 |
Obtained from logistic regression
These values are odds ratios (95% CIs)
Significant values are shown in bold
OR Odds ratio, CI Confidence interval, BMI Body mass index, kg kilogram, m meter, MET Metabolic equivalent of task, g gram, Ref Reference, OCP Oral contraceptive pill
Results
Baseline characteristics of the study based on case and control groups are shown in Table 1. According to the tables, age (P = 0.028), menopausal status (P = 0.033), wearing a bra during the day (P = 0.012), family history of cancer (P = 0.046), abortion history (P = 0.046), and taking vitamin D supplements (P = 0.038) were significantly different between the groups of cases and controls.
Table 1.
Basic characteristics of the study based on case and control groups
Variables | Cases (n = 133) | Controls (n = 266) | P-value |
---|---|---|---|
BMI (kg/m2)a | 29.64 (25.96–33.32) | 28.52 (25.39–31.64) | 0.119 |
Age (years)b | 49.51 ± 10.71 | 47.11 ± 10.09 | 0.028 |
Marriage age (years)a | 19.00 (16.00–22.00) | 18.00 (16.00–20.00) | 0.077 |
Age at the first pregnancy (years)a | 20.00 (17.00–25.00) | 20.00 (17.00–22.00) | 0.055 |
Breastfeeding time (months)a | 39.00 (20.00–60.00) | 48.00 (24.00–70.00) | 0.162 |
Physical activity (MET-h/day)a | 32.10 (29.10–35.50) | 31.42 (29.10-34.98) | 0.677 |
Menopausal status, %c | 0.033 | ||
Pre-menopause | 45.90 | 57.50 | |
Post-menopause | 54.10 | 42.50 | |
Wearing a bra during the day, %c | 0.012 | ||
Less than 12 h | 9.00 | 18.50 | |
More than 12 h | 91.0 | 81.50 | |
Wearing a bra at night, %c | 0.116 | ||
Yes | 78.90 | 71.30 | |
No | 21.10 | 28.70 | |
Family history of cancer, %c | 0.046 | ||
Yes | 30.10 | 20.80 | |
No | 69.90 | 79.20 | |
Family history of breast cancer, %c | 0.171 | ||
Yes | 8.30 | 4.50 | |
No | 91.70 | 95.50 | |
Abortion history, %c | 0.046 | ||
Yes | 40.10 | 28.90 | |
No | 59.90 | 71.10 | |
Smoking, yes, %c | 3.00 | 3.40 | 1.000 |
OCP use, no, %c | 49.60 | 44.20 | 0.338 |
Multivitamin-mineral supplements, no, %c | 94.00 | 93.20 | 0.833 |
Vitamin D supplement, no, %c | 85.00 | 75.80 | 0.038 |
Omega-3 supplement, no, %c | 94.00 | 88.30 | 0.076 |
Herbal drugs, no, %c | 81.20 | 72.80 | 0.083 |
Values are percentage for categorical variables and median (25th -75th) or mean ± SD for continuous
BMI Body mass index, kg kilogram, m meter, MET Metabolic equivalent of task, OCP Oral contraceptive pill
aUsing Mann-Whitney for abnormal continuous variables
bUsing independent samples T-test for normal continuous variables
cUsing chi-square test for categorical variables
The dietary intake of the study participants based on case and control groups is reported in Table 2. The median intake of PFs (P = 0.012), monounsaturated fatty acids (MUFAs) (P = 0.006), and polyunsaturated fatty acids (PUFAs) (P = 0.012) were significantly different between the two groups.
Table 2.
Dietary intake of the study participants based on case and control groups
Variables | Cases (n = 133) | Controls (n = 266) | P-value |
---|---|---|---|
Energy (kcal/day)a | 2482.3 (2079.7-2979.6) | 2546.2 (2150.2-3220.6) | 0.079 |
PFs (% energy/day)a | 21.52 (15.29–29.25) | 18.18 (12.63–26.43) | 0.012 |
UPFs (% energy/day)a | 11.29 (6.97–18.11) | 9.70 (6.42–15.60) | 0.088 |
Protein (% energy/day)b | 12.68 ± 2.06 | 13.03 ± 2.13 | 0.117 |
Carbohydrate (% energy/day)b | 53.79 ± 6.68 | 54.23 ± 7.05 | 0.553 |
Fiber (g/day)a | 34.86 (27.43–45.03) | 38.20 (27.01–50.08) | 0.195 |
Fat (% energy/day)a | 32.76 (29.30–38.10) | 32.60 (28.11–38.38) | 0.343 |
SFAs (% energy/day)a | 10.90 (9.97–11.89) | 10.38 (8.97–11.70) | 0.127 |
MUFAs (% energy/day)a | 12.49 (10.75–14.39) | 11.73 (10.04–14.24) | 0.006 |
PUFAs (% energy/day)a | 7.97 (6.66–10.65) | 7.64 (5.80–9.93) | 0.012 |
Values are percentages for categorical variables and median (25th -75th) or mean ± SD for continuous variables
Kcal kilocalorie, PFs Processed foods, UPFs Ultra-processed foods, g gram, SFAs Saturated fatty acids, MUFAs Monounsaturated fatty acids, PUFAs Polyunsaturated fatty acids
aUsing Mann-Whitney for abnormal continuous variables
bUsing independent samples T-test for normal continuous variables
The association between some baseline variables and the risk of breast cancer is shown in Table 3. In the univariate analysis, higher odds of breast cancer were found with each unit change in age at the first pregnancy (OR = 1.041, 95% CI: 1.003–1.079). Also, in categorical variables, higher odds of breast cancer were observed in postmenopausal women (OR = 1.589, 95% CI: 1.051–2.430), those with a positive abortion history (OR = 1.576, 95% CI: 1.017–2.441), those with a positive family history of cancer (OR = 1.642, 95% CI: 1.021–2.640), and those wearing a bra during the day for more than 12 h (OR = 2.287, 95% CI: 1.171–4.467), compared to the reference group. However, lower odds of breast cancer were seen in those taking vitamin D supplements (OR = 0.556, 95% CI: 0.320–0.966), compared to the reference group.
Table 4 represents the association between PF and UPF intake and the risk of breast cancer. According to the crude model of conditional logistic regression, the chance of breast cancer was higher in the last tertile of UPFs than in the first tertile (OR = 1.930; 95% CI: 1.080–3.449). After adjusting for confounders, no significant associations were seen between the second and last tertiles of PFs and UPFs with the odds of breast cancer compared to the reference tertile.
Table 4.
Association between processed and ultra-processed foods intake and the risk of breast cancer
Tertiles of Indices | Case / Control |
Crude model | Adjusted model | ||||
---|---|---|---|---|---|---|---|
OR | 95% CI | P-value | OR | 95% CI | P-value | ||
Processed foods | |||||||
T1 (≤ 15.82) | 37/96 | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. |
T2 (15.83–23.56) | 43/90 | 1.130 | 0.640–1.997 | 0.673 | 1.319 | 0.676–2.573 | 0.415 |
T3 (≥ 23.57) | 53/80 | 1.633 | 0.937–2.847 | 0.083 | 1.234 | 0.650–2.342 | 0.520 |
Ultra-processed foods | |||||||
T1 (≤ 7.49) | 34/95 | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. |
T2 (7.50-13.92) | 44/89 | 1.309 | 0.730–2.348 | 0.365 | 1.337 | 0.688–2.596 | 0.390 |
T3 (≥ 13.93) | 55/82 | 1.930 | 1.080–3.449 | 0.026 | 1.800 | 0.923–3.513 | 0.084 |
Obtained from conditional logistic regression
These values are odds ratios (95% CIs)
Significant values are shown in bold
Adjusted for variables with p-value < 0.25 based on Table 3
Adjusted model: adjusted for BMI (kg/m2), marriage age (years), age at the first pregnancy (years), breastfeeding time (months), fiber intake (g/day), menopausal status (premenopausal/postmenopausal), abortion history (no/yes), family history of cancer (no/yes), family history of breast cancer (no/yes), wearing a bra during the day (less than 12 h/more than 12 h), wearing a bra at night (no/yes), vitamin D supplement (no/yes), omega-3 supplement (no/yes), and herbal drugs (no/yes)
T Tertile, OR Odds ratio, CI Confidence interval
The association between the intake of PFs and UPFs and the risk of breast cancer by menopausal status is presented in Table 5. In the crude model, no significant associations were seen between PFs and UPFs with the odds of breast cancer. After adjusting for potential confounders, the odds of breast cancer increased in the last tertile only among premenopausal women (OR = 3.656; 95% CI: 1.326–10.079).
Table 5.
Association between the intake of processed and ultra-processed foods and the risk of breast cancer by menopausal status
Tertiles of Indices | Case / Control |
Crude model | Adjusted model | ||||
---|---|---|---|---|---|---|---|
OR | 95% CI | P-value | OR | 95% CI | P-value | ||
Pre-menopausal | |||||||
Processed foods | |||||||
T1 (≤ 15.82) | 15/55 | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. |
T2 (15.83–23.56) | 22/53 | 1.557 | 0.717–3.382 | 0.263 | 2.483 | 0.905–6.812 | 0.077 |
T3 (≥ 23.57) | 24/45 | 1.663 | 0.474–3.703 | 0.213 | 2.000 | 0.759–5.285 | 0.161 |
Ultra-processed foods | |||||||
T1 (≤ 7.49) | 12/50 | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. |
T2 (7.50-13.92) | 18/54 | 1.166 | 0.505–2.690 | 0.718 | 2.008 | 0.731–5.515 | 0.176 |
T3 (≥ 13.93) | 31/49 | 2.260 | 0.992–5.150 | 0.052 | 3.656 | 1.326–10.079 | 0.012 |
Post-menopausal | |||||||
Processed foods | |||||||
T1 (≤ 15.82) | 22/41 | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. |
T2 (15.83–23.56) | 21/37 | 0.758 | 0.322–1.785 | 0.527 | 0.982 | 0.311–3.098 | 0.976 |
T3 (≥ 23.57) | 29/35 | 1.422 | 0.644–3.137 | 0.383 | 1.225 | 0.422–3.555 | 0.708 |
Ultra-processed foods | |||||||
T1 (≤ 7.49) | 24/45 | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. |
T2 (7.50-13.92) | 26/35 | 1.418 | 0.621–3.241 | 0.407 | 1.163 | 0.381–3.551 | 0.790 |
T3 (≥ 13.93) | 24/33 | 1.403 | 0.586–3.357 | 0.447 | 1.583 | 0.505–4.955 | 0.430 |
Obtained from conditional logistic regression
These values are odds ratios (95% CIs)
Significant values are shown in bold
Adjusted for variables with p-value < 0.25 based on Table 3
Adjusted model: adjusted for BMI (kg/m2), marriage age (years), age at the first pregnancy (years), breastfeeding time (months), fiber intake (g/day), abortion history (no/yes), family history of cancer (no/yes), family history of breast cancer (no/yes), wearing a bra during the day (less than 12 h/more than 12 h), wearing a bra at night (no/yes), vitamin D supplement (no/yes), omega-3 supplement (no/yes), and herbal drugs (no/yes)
T Tertile, OR Odds ratio, CI Confidence interval
Discussion
In the present case-control study conducted on Iranian women, results demonstrated that higher consumption of PFs and UPFs was not associated with breast cancer. However, subgroup analysis of this association, considering pre-and post-menopausal women, showed a significant association between UPFs and breast cancer risk in premenopausal women.
Our findings are in line with some previous studies. A study conducted in Canada did not show any association between the intake of UPFs and cancer [33]. Also, a study conducted on South African women failed to show any significant association between the intake of UPFs and the risk of breast cancer. In this study, they observed that a higher intake of minimally PFs was inversely associated with the risk of breast cancer [33]. In a MCC study, non-adjusted models showed a significant association between UPFs and a higher risk of breast cancer. They lost their significance after adjusting for energy and alcohol intake. This might suggest, that in this population, energy and alcohol intake, as recognized risk factors [34, 35] of breast cancer, mediated the observed association. In addition, a MCC study showed that the association between UPFs and breast cancer in former and current smokers was significant. Smoking is a risk factor for breast cancer [36] and also might have some synergistic effects with UPFs [37], which need more investigation. However, due to cultural stigmas about smoking and alcohol consumption in Iran, we could not evaluate these factors. Therefore, our findings need to be interpreted with caution. Additionally, a MCC study conducted by Romaguera et al. showed that UPF consumption did not affect the odds of developing breast cancer [19]. However, results from the NutriNet-Santé study on 105,000 individuals in France showed that a 10% higher intake of UPFs was associated with a significantly increased risk of overall cancer (hazard ratio (HR) = 1.12; 95% CI: 1.06–1.18) and breast cancer (HR = 1.11; 95% CI: 1.02–1.22) [18]. Also, a case-control study conducted by Queiroz et al. in Brazil revealed that regular consumption of UPFs more than five times a week increases the risk of breast cancer by 2.35 times [38]. Discrepancies between the findings might be due to different study designs and/or study populations [19].
The results of the present study showed a significant relationship between the consumption of UPFs and the risk of breast cancer in premenopausal women. There is evidence showing that the association between UPF intake and the risk of breast cancer is stronger in younger women [34]. This observation is in line with our findings, showing that the association between UPFs and the risk of breast cancer is significant only in premenopausal women. The association observed in the NutriNet-Santé study was significant in the overall cancer and postmenopausal subgroup but not in the premenopausal subgroup. This discrepancy might be due to the differences in French and Iranian populations, such as smoking habits, alcohol consumption, and lower UPF consumption in Iran (8.5%) [35] (in the present study in the case group: 11.3% and in the control group: 9.6% energy from UPFs) compared with the total consumption of UPFs in France (18.7%) [18]. On the other hand, studies showed that the mean age of patients with breast cancer in Iran is 10–15 years lower than in developed countries [36, 37], and 23% of diagnosed cases are younger than 40 years [39]. Additionally, in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort [34], low-fat and high-fiber intake was associated with a reduction in breast cancer risk in premenopausal women, suggesting that lower fat intake reduces sex hormone concentrations and bioavailability and contributes to a lower risk of breast cancer [40, 41].
Several mechanisms may explain the association between UPFs and breast cancer risk. UPFs have poor nutritional values, such as high energy, sugar, sodium, saturated and trans-fatty acid content, and low micronutrient, protein, and fiber [33]. Higher intake of carbohydrates, glycemic index, and glycemic load has been shown to be associated with a higher risk of breast cancer [42]. Industrial bread, fruit juices, and packaged sweet snacks, as categories of UPFs, have a high glycemic index and glycemic load, which might explain their association with breast cancer [21, 43]. The EPIC study has previously shown that trans-fatty acid blood concentrations are associated with the risk of estrogen receptor (ER)-negative breast cancer [44]. Trans-fatty acids are present in ready-to-eat/fast foods and are part of UPFs [33].
It is documented that UPFs are associated with reduced gut-brain satiety signaling [45]. Additionally, the physical and chemical characteristics of UPFs and their high availability, convenience, and palatability result in their overconsumption [46–49]. Some studies [18], have shown that even after adjustments for nutritional factors, including energy intake, the association between UPFs and adverse health outcomes remains significant. These observations suggest that factors other than the energy, carbohydrate, and fat content of UPFs might affect the association between UPFs and undesirable health outcomes. For instance, additives such as sodium nitrite in processed meat products might produce new compounds, such as nitrosamines, with carcinogenic effects during industrial processes [50, 51]. Additionally, the accumulated effects of food additives are still unknown. Various carcinogenic compounds, such as acrylamides, might be produced during heat treatment [52]. Various compounds, including phthalates, titanium dioxide (TiO2), and bisphenol A, that have been associated with endocrine disruption, might migrate from packages to packaged foods [53, 54]. Some components of UPFs might induce inflammatory responses that change gut microbiota and intestinal permeability [55–57]. These aspects of UPFs need to be studied more. Also, genes that play a role in deoxyribonucleic acid (DNA) repair, cell-cycle regulation, and apoptosis are crucial in the progression of cancer [58]. The consumption of UPFs is associated with more DNA damage, which can contribute to the occurrence of cancer [59]. Additionally, UPFs are high in fat and sugar, which can contribute to obesity, a potential risk factor for breast cancer [60]. However, in the present study, no significant differences were observed between the two groups regarding BMI.
Strengths and limitations
Our study has some strengths and limitations. With the rapid rise of PF and UPF consumption, investigating the association between this type of food and breast cancer seems relevant. Considering the menopausal status of the patients, which is a critical aspect when studying breast cancer, was one of the strengths of this study. In addition, the classification of the foods and drinks from the validated FFQ was done by a panel of nutritionists based on the NOVA system. Intrinsic limitations of case-control retrospective design and self-reporting of dietary intake can result in selection and recall bias. To minimize these limitations, patients and controls were matched based on age, and we tried to use a validated questionnaire with high validity and reproducibility in the Iranian population, and trained nutritionists to gather the data. The FFQ used in this study was not designed to evaluate the consumption of UPFs, which might lead to an underestimation of the association between the consumption of UPFs and breast cancer [61]. This questionnaire only captures the dietary intake one year before the cancer diagnosis. Therefore, there might be a reverse causation, and the results from this study need to be interpreted with caution. Additionally, as it takes decades for cancer to develop and progress [62], long-term prospective cohort studies are needed to confirm the observed association. Lastly, although several confounding factors were considered in this study, the effects of the remaining confounding factors could not be entirely excluded due to the study’s observational design.
Conclusions
In conclusion, this study demonstrated that higher consumption of UPFs is associated with a higher odds of breast cancer in premenopausal women. More studies are warranted to discover the underlying mechanisms of this observed association.
Acknowledgements
We sincerely thank all field investigators, staff, and participants of the present study.
Authors’ contributions
M.N., F.M., F.J, M.R.Z., and Z.S.; Contributed to writing the first draft and revision. S.J and Z.H; Contributed to data collection. M.N., F.M., and B.R.; Contributed to all data and statistical analysis and interpretation of data. M.N. and B.R.; Contributed to the research concept, supervised the work, and revised the manuscript. All authors read and approved the final manuscript.
Funding
Not applicable.
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
This study was conducted in accordance with the ethical standards of the Declaration of Helsinki and was approved by the Research Institute of Nutrition and Food Sciences of Shahid Beheshti University of Medical Sciences. All participants read and signed the informed consent form.
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
Zainab Shateri, Email: zainabshateri@gmail.com.
Bahram Rashidkhani, Email: rashidkhani@yahoo.com.
References
- 1.Ferlay J, Colombet M, Soerjomataram I, Parkin DM, Piñeros M, Znaor A, Bray F. Cancer statistics for the year 2020: an overview. Int J Cancer. 2021;149(4):778–89. [DOI] [PubMed]
- 2.Lei S, Zheng R, Zhang S, Wang S, Chen R, Sun K, Zeng H, Zhou J, Wei W. Global patterns of breast cancer incidence and mortality: a population-based cancer registry data analysis from 2000 to 2020. Cancer Commun (Lond). 2021;41(11):1183–94. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Mavaddat N, Antoniou AC, Easton DF, Garcia-Closas M. Genetic susceptibility to breast cancer. Mol Oncol. 2010;4(3):174–91. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Castelló A, Martín M, Ruiz A, Casas AM, Baena-Cañada JM, Lope V, Antolín S, Sánchez P, Ramos M, Antón A, et al. Lower breast cancer risk among women following the world cancer research fund and american institute for cancer research lifestyle recommendations: EpiGEICAM case-control study. PLoS ONE. 2015;10(5):e0126096. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Clinton SK, Giovannucci EL, Hursting SD. The world cancer research Fund/American Institute for cancer research third expert report on diet, nutrition, physical activity, and cancer: impact and future directions. J Nutr. 2020;150(4):663–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Key TJ, Allen NE, Spencer EA, Travis RC. The effect of diet on risk of cancer. Lancet. 2002;360(9336):861–8. [DOI] [PubMed] [Google Scholar]
- 7.Brennan SF, Cantwell MM, Cardwell CR, Velentzis LS, Woodside JV. Dietary patterns and breast cancer risk: a systematic review and meta-analysis. Am J Clin Nutr. 2010;91(5):1294–302. [DOI] [PubMed] [Google Scholar]
- 8.Moodie R, Stuckler D, Monteiro C, Sheron N, Neal B, Thamarangsi T, Lincoln P, Casswell S. Profits and pandemics: prevention of harmful effects of tobacco, alcohol, and ultra-processed food and drink industries. Lancet (London England). 2013;381(9867):670–9. [DOI] [PubMed] [Google Scholar]
- 9.Monteiro CA, Cannon G, Levy RB, Moubarac JC, Louzada ML, Rauber F, Khandpur N, Cediel G, Neri D, Martinez-Steele E, et al. Ultra-processed foods: what they are and how to identify them. Public Health Nutr. 2019;22(5):936–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Rico-Campà A, Martínez-González MA, Alvarez-Alvarez I, Mendonça RD, de la Fuente-Arrillaga C, Gómez-Donoso C, Bes-Rastrollo M. Association between consumption of ultra-processed foods and all cause mortality: SUN prospective cohort study. BMJ. 2019;365:1–11. [DOI] [PMC free article] [PubMed]
- 11.Monteiro CA, Moubarac JC, Cannon G, Ng SW, Popkin B. Ultra-processed products are becoming dominant in the global food system. Obes Rev: Off J Int Assoc Study Obes. 2013;14(Suppl 2):21–8. [DOI] [PubMed] [Google Scholar]
- 12.Costa Louzada ML, Martins AP, Canella DS, Baraldi LG, Levy RB, Claro RM, Moubarac JC, Cannon G, Monteiro CA. Ultra-processed foods and the nutritional dietary profile in Brazil. Rev Saude Publica. 2015;49:38. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Louzada ML, Martins AP, Canella DS, Baraldi LG, Levy RB, Claro RM, Moubarac JC, Cannon G, Monteiro CA. Impact of ultra-processed foods on micronutrient content in the Brazilian diet. Rev Saude Publica. 2015;49:45. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Kim CB, Moon SY, Gelder SR, Kim W. Phylogenetic relationships of annelids, molluscs, and arthropods evidenced from molecules and morphology. J Mol Evol. 1996;43(3):207–15. [DOI] [PubMed] [Google Scholar]
- 15.Singh L, Varshney JG, Agarwal T. Polycyclic aromatic hydrocarbons’ formation and occurrence in processed food. Food Chem. 2016;199:768–81. [DOI] [PubMed] [Google Scholar]
- 16.Buckley JP, Kim H, Wong E, Rebholz CM. Ultra-processed food consumption and exposure to phthalates and bisphenols in the us national health and nutrition examination Survey, 2013–2014. Environ Int. 2019;131: 105057. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Martínez Steele E, Khandpur N, da Costa Louzada ML, Monteiro CA. Association between dietary contribution of ultra-processed foods and urinary concentrations of phthalates and bisphenol in a nationally representative sample of the US population aged 6 years and older. PLoS ONE. 2020;15(7): e0236738. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Fiolet T, Srour B, Sellem L, Kesse-Guyot E, Allès B, Méjean C, Deschasaux M, Fassier P, Latino-Martel P, Beslay M, et al. Consumption of ultra-processed foods and cancer risk: results from NutriNet-Santé prospective cohort. BMJ. 2018;360:k322. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Romaguera D, Fernández-Barrés S, Gracia-Lavedán E, Vendrell E, Azpiri M, Ruiz-Moreno E, Martín V, Gómez-Acebo I, Obón M, Molinuevo A, et al. Consumption of ultra-processed foods and drinks and colorectal, breast, and prostate cancer. Clin Nutr. 2021;40(4):1537–45. [DOI] [PubMed] [Google Scholar]
- 20.Jacobs I, Taljaard-Krugell C, Wicks M, Cubasch H, Joffe M, Laubscher R, Romieu I, Levy RB, Rauber F, Biessy C, et al. Degree of food processing and breast cancer risk in black urban women from Soweto, South African: the South African breast Cancer study. Br J Nutr. 2022;128(11):2278–89. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Romieu I, Khandpur N, Katsikari A, Biessy C, Torres-Mejía G, Ángeles-Llerenas A, Alvarado-Cabrero I, Sánchez GI, Maldonado ME, Porras C, et al. Consumption of industrial processed foods and risk of premenopausal breast cancer among latin American women: the PRECAMA study. BMJ Nutr Prev Health. 2022;5(1):1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Ching S, Ingram D, Hahnel R, Beilby J, Rossi E. Serum levels of micronutrients, antioxidants and total antioxidant status predict risk of breast cancer in a case control study. J Nutr. 2002;132(2):303–6. [DOI] [PubMed] [Google Scholar]
- 23.Pourhabibi-Zarandi F, Kahrizsangi MA, Eskandarzadeh S, Mansouri F, Vali M, Jalali S, Heidari Z, Shateri Z, Nouri M, Rashidkhani B. Dietary quality index and the risk of breast cancer: a case-control study. BMC Womens Health. 2023;23(1):469. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Hosseini Y, Hadi Sichani P, Moslemi E, Nouri M, Rajabzadeh-dehkordi M, Jalali S, Heidari Z, Shateri Z, Rashidkhani B. Pro-vegetarian dietary pattern and risk of breast cancer: a case–control study. Breast Cancer Res Treat. 2024;205(2):395–402. [DOI] [PubMed] [Google Scholar]
- 25.Esfahani FH, Asghari G, Mirmiran P, Azizi F. Reproducibility and relative validity of food group intake in a food frequency questionnaire developed for the Tehran lipid and glucose study. J Epidemiol. 2010;20(2):150–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Mirmiran P, Esfahani FH, Mehrabi Y, Hedayati M, Azizi F. Reliability and relative validity of an FFQ for nutrients in the Tehran lipid and glucose study. Public Health Nutr. 2010;13(5):654–62. [DOI] [PubMed] [Google Scholar]
- 27.Ghaffarpour M, Houshiar-Rad A, Kianfar H. The manual for household measures, cooking yields factors and edible portion of foods. Tehran: Nashre Olume Keshavarzy. 1999;7(213):42–58. [Google Scholar]
- 28.Azar M, Sarkisian E. Food composition table of Iran. Tehran: Natl Nutr Food Res Inst Shaheed Beheshti Univ. 1980;65.
- 29.Monteiro CA, Cannon G, Moubarac JC, Levy RB, Louzada ML, Jaime PC. The UN decade of nutrition, the NOVA food classification and the trouble with ultra-processing. Public Health Nutr. 2017;21(1):5–17. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Monteiro CA, Levy RB, Claro RM, de Castro IRR, Cannon G. Increasing consumption of ultra-processed foods and likely impact on human health: evidence from Brazil. Public Health Nutr. 2010;14(1):5–13. [DOI] [PubMed] [Google Scholar]
- 31.Jafari F, Yarmand S, Nouri M, Nejad ET, Ramezani A, Sohrabi Z, Rashidkhani B. Ultra-processed food intake and risk of colorectal cancer: a matched case-control study. Nutr Cancer. 2023;75(2):532–41. [DOI] [PubMed] [Google Scholar]
- 32.Aadahl M, Jørgensen T. Validation of a new self-report instrument for measuring physical activity. Med Sci Sports Exerc. 2003;35(7):1196–202. [DOI] [PubMed] [Google Scholar]
- 33.Monteiro CA, Cannon G, Moubarac JC, Levy RB, Louzada MLC, Jaime PC. Ultra-processing. An odd ‘appraisal.’ Public Health Nutr. 2018;21(3):497–501. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Ferrari P, Rinaldi S, Jenab M, Lukanova A, Olsen A, Tjønneland A, Overvad K, Clavel-Chapelon F, Fagherazzi G, Touillaud M, et al. Dietary fiber intake and risk of hormonal receptor-defined breast cancer in the European prospective investigation into cancer and nutrition study. Am J Clin Nutr. 2013;97(2):344–53. [DOI] [PubMed] [Google Scholar]
- 35.Haghighatdoost F, Hajihashemi P, Mohammadifard N, Najafi F, Farshidi H, Lotfizadeh M, Kazemi T, Karimi S, Shirani S, Solati K, Sarrafzadegan N. Association between ultra-processed foods consumption and micronutrient intake and diet quality in Iranian adults: a multicentric study. Public Health Nutr. 2023;26(2):467–5. [DOI] [PubMed]
- 36.Motie MR, Besharat S, Torkjazi R, Shojaa M, Besharat M, Keshtkar A, Roshandel G, Besharat S, Fateme AA. Modifiable risk of breast cancer in Northeast Iran: hope for the future. A case-control study. Breast Care (Basel). 2011;6(6):453–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Tehranian N, Shobeiri F, Pour FH, Hagizadeh E. Risk factors for breast cancer in Iranian women aged less than 40 years. Asian Pac J Cancer Prev: APJCP. 2010;11(6):1723–5. [PubMed] [Google Scholar]
- 38.Queiroz SA, de Sousa IM, de Melo Silva FR, de Oliveira Lyra C, Fayh PT. Nutritional and environmental risk factors for breast cancer: a case-control study. Scientia Med. 2018;28(2):2. [Google Scholar]
- 39.Mousavi SM, Montazeri A, Mohagheghi MA, Jarrahi AM, Harirchi I, Najafi M, Ebrahimi M. Breast cancer in Iran: an epidemiological review. Breast J. 2007;13(4):383–91. [DOI] [PubMed] [Google Scholar]
- 40.Prentice RL, Sheppard L. Dietary fat and cancer: consistency of the epidemiologic data, and disease prevention that may follow from a practical reduction in fat consumption. Cancer Causes Control. 1990;1(1):81–97 discussion 99–109. [DOI] [PubMed] [Google Scholar]
- 41.Berrino F, Bellati C, Secreto G, Camerini E, Pala V, Panico S, Allegro G, Kaaks R. Reducing bioavailable sex hormones through a comprehensive change in diet: the diet and androgens (DIANA) randomized trial. Cancer Epidemiol Biomarkers Prev: Public Am Assoc Cancer Res Cosponsored Am Soc Prev Oncol. 2001;10(1):25–33. [PubMed] [Google Scholar]
- 42.Choi Y, Giovannucci E, Lee JE. Glycaemic index and glycaemic load in relation to risk of diabetes-related cancers: a meta-analysis. Br J Nutr. 2012;108(11):1934–47. [DOI] [PubMed] [Google Scholar]
- 43.Romieu I, Lazcano-Ponce E, Sanchez-Zamorano LM, Willett W, Hernandez-Avila M. Carbohydrates and the risk of breast cancer among Mexican women. Cancer Epidemiol Biomarkers Prev: Public Am Assoc Cancer Res Cosponsored Am Soc Prev Oncol. 2004;13(8):1283–9. [PubMed] [Google Scholar]
- 44.Chajès V, Assi N, Biessy C, Ferrari P, Rinaldi S, Slimani N, Lenoir GM, Baglietto L, His M, Boutron-Ruault MC, et al. A prospective evaluation of plasma phospholipid fatty acids and breast cancer risk in the EPIC study. Ann Oncol. 2017;28(11):2836–42. [DOI] [PubMed] [Google Scholar]
- 45.Fardet A. Minimally processed foods are more satiating and less hyperglycemic than ultra-processed foods: a preliminary study with 98 ready-to-eat foods. Food Funct. 2016;7(5):2338–46. [DOI] [PubMed] [Google Scholar]
- 46.Alexy U, Sichert-Hellert W, Rode T, Kersting M. Convenience food in the diet of children and adolescents: consumption and composition. Br J Nutr. 2008;99(2):345–51. [DOI] [PubMed] [Google Scholar]
- 47.Peltner J, Thiele S. Convenience-based food purchase patterns: identification and associations with dietary quality, sociodemographic factors and attitudes. Public Health Nutr. 2018;21(3):558–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Filgueiras AR, Pires de Almeida VB, Koch Nogueira PC, Alvares Domene SM, Eduardo da Silva C, Sesso R, Sawaya AL. Exploring the consumption of ultra-processed foods and its association with food addiction in overweight children. Appetite. 2019;135:137–45. [DOI] [PubMed] [Google Scholar]
- 49.Hall KD, Ayuketah A, Brychta R, Cai H, Cassimatis T, Chen KY, Chung ST, Costa E, Courville A, Darcey V, et al. Ultra-processed diets cause excess calorie intake and weight gain: an inpatient randomized controlled trial of Ad Libitum food intake. Cell Metab. 2019;30(1):67-e7763. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Bouvard V, Loomis D, Guyton KZ, Grosse Y, Ghissassi FE, Benbrahim-Tallaa L, Guha N, Mattock H, Straif K. Carcinogenicity of consumption of red and processed meat. Lancet Oncol. 2015;16(16):1599–600. [DOI] [PubMed] [Google Scholar]
- 51.Santarelli RL, Vendeuvre JL, Naud N, Taché S, Guéraud F, Viau M, Genot C, Corpet DE, Pierre FH. Meat processing and colon carcinogenesis: cooked, nitrite-treated, and oxidized high-heme cured meat promotes mucin-depleted foci in rats. Cancer Prev Res (Phila). 2010;3(7):852–64. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Virk-Baker MK, Nagy TR, Barnes S, Groopman J. Dietary acrylamide and human cancer: a systematic review of literature. Nutr Cancer. 2014;66(5):774–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Burks H, Pashos N, Martin E, McLachlan J, Bunnell B, Burow M. Endocrine disruptors and the tumor microenvironment: a new paradigm in breast cancer biology. Mol Cell Endocrinol. 2017;457:13–9. [DOI] [PubMed] [Google Scholar]
- 54.Ahern TP, Broe A, Lash TL, Cronin-Fenton DP, Ulrichsen SP, Christiansen PM, Cole BF, Tamimi RM, Sørensen HT, Damkier P. Phthalate exposure and breast cancer incidence: a Danish nationwide cohort study. J Clin Oncol. 2019;37(21):1800–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Zinöcker MK, Lindseth IA. The Western Diet-Microbiome-Host Interaction and Its Role in Metabolic Disease. Nutrients 2018;10(3):365. [DOI] [PMC free article] [PubMed]
- 56.Lerner A, Matthias T. Changes in intestinal tight junction permeability associated with industrial food additives explain the rising incidence of autoimmune disease. Autoimmun Rev. 2015;14(6):479–89. [DOI] [PubMed] [Google Scholar]
- 57.Miclotte L, Van de Wiele T. Food processing, gut microbiota and the globesity problem. Crit Rev Food Sci Nutr. 2020;60(11):1769–82. [DOI] [PubMed] [Google Scholar]
- 58.Frank SA. Genetic predisposition to cancer—insights from population genetics. Nat Rev Genet. 2004;5(10):764–72. [DOI] [PubMed] [Google Scholar]
- 59.Edalati S, Bagherzadeh F, Jafarabadi MA, Ebrahimi-Mamaghani M. Higher ultra-processed food intake is associated with higher DNA damage in healthy adolescents. Br J Nutr. 2021;125(5):568–76. [DOI] [PubMed] [Google Scholar]
- 60.Stephenson GD, Rose DP. Breast cancer and obesity: an update. Nutr Cancer. 2003;45(1):1–16. [DOI] [PubMed] [Google Scholar]
- 61.Marino M, Puppo F, Del Bo C, Vinelli V, Riso P, Porrini M, Martini D. A systematic review of worldwide consumption of ultra-processed foods: findings and criticisms. Nutrients. 2021;13(8):2778. [DOI] [PMC free article] [PubMed]
- 62.Caplan L. Delay in breast cancer: implications for stage at diagnosis and survival. Front Public Health. 2014;2:87. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.