Fish consumption in relation to breast cancer: A case-control study

doi:10.21203/rs.3.rs-4202460/v1

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Fish consumption in relation to breast cancer: A case-control study

https://doi.org/10.21203/rs.3.rs-4202460/v1

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Background: Even though regular fish consumption is highly recommended to reduce the risk of developing several cancers, available evidence on the association between breast cancer and fish is inconclusive. We aimed to explore the association between fish consumption and breast cancer in a well-characterized population of Iranian women.

Methods: This study enrolled 350 newly diagnosed stage I-IV breast cancer patients and 700 cancer-free controls living in Isfahan. Controls had no family history of breast cancer and were matched to cancer patients in term of age and socioeconomic status (SES). Dietary intakes were determined using a validated food frequency questionnaire (DS-FFQ). In addition, data on potential confounding factors were collected using pre-tested questionnaires.

Results: After adjusting for potential confounders, women in the highest quartile of fish consumption had a lower odds of breast cancer than those in the lowest quartile (OR: 0.57, 95% CI: 0.34-0.95). The stratified analysis by menopausal status revealed an inverse association in postmenopausal women (OR: 0.53, 95% CI: 0.30-0.94).

Conclusions: Our findings suggest higher fish consumption is associated with a lower likelihood of having breast cancer, particularly in post-menopause. The findings should be interpreted with caution due to the case-control study design. To further examine this association, prospective studies are needed.

Fish

seafood

diet

breast cancer

case-control study

Breast cancer is the most frequently diagnosed type of cancer and the fifth biggest cause of cancer-related death globally [1]. Each woman has a 13% risk of breast cancer in the United States. This translates to one in every eight women developing breast cancer in the life course [2]. According to the Global Cancer Statistics 2020, 2.3 million women were diagnosed with breast cancer resulting in 685,000 deaths worldwide, which has more than doubled over the last two decades[3]. Breast cancer in recent years, in underdeveloped countries have soared [4]. Geographic variation in the incidence rate of breast cancer may be attributed to modifiable lifestyle factors, highlighting the need for preventive approaches.

Aside from family history and genetics, several environmental and lifestyle-related factors are the main drivers in the etiology of breast cancer; among them, diet has received the greatest attention [5]. In particular, fish intake has long been studied in relation to various health outcomes. Fish is the most abundant dietary source of omega-3 long-chain polyunsaturated fatty acids (n-3 LCPUFAs), as well as protein, vitamin D, B vitamins, calcium, selenium, zinc, magnesium, and other nutrients [6, 7]. It has previously been linked to a lower risk of all-cause mortality [8], coronary heart disease incidence and mortality [9], diabetes [10], stroke [11], and several cancers [12–14]. Its consumption has also been examined in relation to breast cancer; however, findings were inconsistent. Even though some studies reported a significant protective association [15, 16], others failed to reach such an association [17–19]. In general, the research results appear conflicting. The significance of the results may be affected by the varying levels of fish intake among nations.

Due to vast geographical differences, the demographics of breast cancer patients in developing countries are distinct from those in industrialized nations. Changes in dietary habits and lifestyle as a result of globalization and economic development, as well as the availability of breast cancer screening programs, may influence the breast cancer risk of the population. The majority of studies on the association between fish consumption and health outcomes have been conducted in countries with a high fish intake. Then, it remains unknown if the favorable contribution of fish intake to human health exists in countries with a low fish intake as well. This is particularly relevant for people residing in the Middle East, where fish consumption is low and dietary intakes are differ from other parts of the world [20]. Given the increasing incidence of breast cancer among women along with nutrition transition in this region, this study was designed to assess the relationship between fish consumption and odds of breast cancer in Iranian females.

Study population

This population-based case-control study included women over the age of 30 in Isfahan, Iran. Enrollment of study participants started in 2013 and ended in 2015. We recruited women with breast cancer using convenience sampling from patients referred to hospitals or private clinics who were undergoing chemotherapy, surgical tumor resection, or radiotherapy. The diagnosis was based on physical examination, mammography exam, and pathological confirmation performed during the maximum of last six months. Women with breast cancer included in the study had been diagnosed with invasive primary breast tumors, and whose histological medical records were available. Age-matched controls (± 5 years) were randomly selected among healthy women in the healthcare institutions in Isfahan, considering their living place as a measure of socio-economic status (SES). Inclusion/Exclusion criteria for the control group were (i) being women, (ii) having Iranian nationality, (iii) no history of any malignancy, cystic mass, and pathological states, (iv) no prior history of hormone replacement therapy, (v) following no specific diet-programs.

Dietary intakes assessment

Usual dietary intakes of the study population during the previous year were obtained using a dish-based Willett-format 106-item semiquantitative food frequency questionnaire (DS-FFQ) [21]. The questionnaire validity and details about its design and food items were previously reported [21]. Briefly, this questionnaire included five groups of foods and dishes: (1) cooked or canned foods called mixed dishes (29 items); (2) foods that are based on carbohydrates (various kinds of potatoes, biscuits, bread, cakes, ten items); (3) dairies (butter, yogurt, and cream, nine items); (4) fruit and vegetables (22 items); and (5) miscellaneous food products and beverages (sweets, junk foods, nuts, desserts and drinks, 36 items). The consumption frequency of each food item was questioned using nine multiple-choice responses ranging from “never or less than once a month” to “12 or more times per day”. The consumption frequency of fish items was assessed using six multiple-choice frequency responses ranging from "never or less than once a month" to "1–2 times per day". A trained nutritionist performed face-to-face interviews to complete the DS-FFQ. Study participants were requested to report their habitual intakes of food items during the last year. All reported frequencies were converted to grams per day considering given portion sizes in the questionnaire. This was done by a nutritionist using a previously published booklet on household measures of foods [22]. The Nutritionist IV Software (based on the USDA nutrient databank and modified for Iranian foods) was utilized to assess the participants' daily nutrient intakes. Fish intake was calculated by summing up total fish and canned tuna. The reliability and validity of the DS-FFQ were investigated in a subset of 200 randomly selected participants [21]. The DS-FFQ was completed by all participants in the validation study at the study baseline and six months later. Three detailed dietary records were obtained from participants for this validation study, which served as the gold standard. According to the findings of this study, the DS-FFQ may indicate reasonably valid and reliable measures of long-term dietary intakes in the Iranian population; for example, the dietary carbohydrate intake as determined by the DS-FFQ was considerably correlated with the average of three dietary records (r = 0.81).

Breast cancer assessment

Breast cancer diagnosis was made by physical examination and mammographic exams that final conformation was determined by pathological tests. All breast cancer patients were females of Iranian nationality with newly diagnosed breast cancer of stage I-IV.

Assessment of covariates

An overall pretested socio-economic status questionnaire filled by face-to-face interview was applied to collect information on age, residential area, education, family history of breast cancer in their immediate family, alcohol drinking, smoking status, marital status, menopausal status, prior lactating, supplement use, and past disease history. Body weight was measured with light clothing and without shoes, using a digital scale (Seca, Hamburg, Germany) to the nearest 0.1 Kg. Height was quantified without shoes, in the standing position, and near to the wall by employing a tape meter to the nearest 0.5 cm. Body mass index (BMI) was computed by dividing weight in kilograms by height per square meters. Participants were categorized according to BMI into “normal” and “overweight or obese” (18.5–24.9 and > 25 Kg/m², respectively). Short-form translated Persian International Physical Activity Questionnaire (IPAQ) was employed through face-to-face interviews to assess participants’ physical activity. This translated form has been proved in previous studies to describe the exact information about physical activity among the people of Iran [23–26]. The information obtained from IPAQ was expressed as a metabolic equivalent time per week (METs/week).

Statistical analysis

The sample size calculation was according to the hypothesis that an unhealthy diet might increase breast cancer odds by 1.5 times. Considering a type I error of 5%, a study power of 80%, a typical ratio of 0.25, and a ratio of controls to cases as 2, the required sample size was estimated at almost 350 breast cancer patients and 700 seemingly healthy controls.

Participants were divided into quartiles based on their fish consumption. To begin, the energy-adjusted dietary intake of fish was calculated using the residual method [27]. To examine differences in quantitative variables across quartiles of fish consumption and between cases and controls, we respectively used one-way analysis of variance (ANOVA) and independent samples' t-test (preceded by the Levene’s test for homogeneity of variances). The chi-square test was used to investigate the distribution of categorical variables across fish consumption quartiles. Analysis of covariance (ANCOVA) was used to compare participants' dietary intake across quartiles of fish intake, which was adjusted for age, and total energy intake. We calculated odds ratios (ORs) for breast cancer using binary logistic regression in adjusted models. We controlled for age (continuous) and energy intake (continuous) in the first model. Additional adjustments were made in the second model for education (educated/non-educated), marital status (single/married), social-economic status (poor/middle/high class), residential area (urban/rural), dietary supplement use (yes/no), family history of breast cancer (yes/no), disease history (yes/no), physical activity (MET-h/week), smoking (non-smoker/smoker), alcohol drinking (yes/no), breastfeeding history (yes/no), and menopausal status (premenopausal/postmenopausal). Further adjustments were made in the third model for dietary intake such as refined grains (continuous), whole grains (continuous), fruit (continuous), vegetables (continuous), dairy (continuous), nuts (continuous), and legumes (continuous). In the final model, BMI was controlled to rule out the confounding effect of obesity on the association between fish intake and breast cancer. These covariates were selected based on previous studies [28–30], as well as significant differences in fish intake between quartiles. Participants in the first quartile of fish consumption were considered as the reference category in these analyses. We treated these categories as ordinal variables to determine the overall trend in ORs for breast cancer across fish consumption quartiles. We conducted all statistical analyses via SPSS software (version 26; SPSS Inc., Chicago, IL). A two-sided P-value < 0.05 was regarded as statistically significant for all tests.

Table 1 details the baseline characteristics of the study population (across case and controls as well as across quartiles of fish consumption). Compared to controls, breast cancer patients were older, more likely to be postmenopausal, current smokers, and less likely to be educated and married. In addition, they had a lower BMI and a breast cancer family history. Women in the highest quartile of fish consumption were younger, had a higher BMI, more likely to be educated, premenopausal, live in urban areas. In addition, they had higher consumption of alcohol, and higher socioeconomic status than women in the lowest quartile of fish consumption.

Table 1

General characteristics of the study participants based on cases and controls as well as across quartiles of fish intake.
	Groups			Quartile of fish intake
	Controls (n = 700)	Cases (n = 350)	P^*	Q1 n = 306	Q2 n = 218	Q3 n = 260	Q4 n = 266	P^*
Age (years)	61.0 ± 10.3	65.3 ± 11.2	< 0.001	64.7 ± 10.3	61.9 ± 10.9	60.7 ± 10.5	62.0 ± 11.3	< 0.001
BMI (kg/m²)	25.5 ± 5.0	21.8 ± 4.8	< 0.001	23.5 ± 5.3	23.6 ± 4.4	25.1 ± 5.3	24.9 ± 5.6	< 0.001
Physical activity (MET-h/week)	34.8 ± 6.5	35.4 ± 6.7	0.20	34.5 ± 6.8	35.3 ± 6.5	35.2 ± 6.3	35.4 ± 6.7	0.44
Residing in rural area, n (%)	447 (63.9)	224 (64.0)	0.96	238 (77.8)	157 (72.0)	155 (59.6)	121 (45.5)	< 0.001
Married, n (%)	618 (88.3)	261 (74.6)	< 0.001	242 (79.1)	178 (81.7)	224 (86.2)	235 (88.3)	0.08
Educated, n (%)	202 (28.9)	61 (17.4)	< 0.001	29 (9.5)	45 (20.6)	79 (30.4)	110 (41.4)	< 0.001
Poor Social Economic Status, n (%)	203 (29.0)	117 (33.4)	0.31	133 (43.5)	75 (34.4)	68 (26.2)	44 (16.5)	< 0.001
Disease history (yes), n (%)^a	61 (8.7)	36 (10.3)	0.41	32 (10.5)	21 (9.6)	24 (9.2)	20 (7.5)	0.68
Current smokers, n (%)^b	91 (13.0)	61 (17.4)	0.05	43 (14.1)	35 (16.1)	39 (15.0)	35(13.2)	0.82
Family history of breast cancer, n (%)	24 (3.4)	33 (9.4)	< 0.001	20 (6.5)	11 (5.0)	17 (6.5)	9 (3.4)	0.31
History of breast feeding, n (%)	236 (33.7)	119 (34.0)	0.93	110 (35.9)	73 (33.5)	87 (33.5)	85 (32.0)	0.79
Alcohol drinking, n (%)^c	52 (7.4)	16 (4.6)	0.08	6 (2.0)	7 (3.2)	22 (8.5)	33 (12.4)	< 0.001
Supplement use, n (%)^d	71 (10.1)	33 (9.4)	0.71	40 (13.1)	19 (8.7)	27 (10.4)	18 (6.8)	0.08
Post menopause, n (%)	542 (77.4)	309 (88.3)	< 0.001	267 (87.3)	171 (78.4)	202 (77.7)	211 (79.3)	0.01
- Data are reported as mean ± SD or percentage. ^a Subjects with a history of diabetes, heart disease, stroke, or cancer ^b Individuals who smoke at least one cigarette per day ^c People who regularly drink alcohol (2–3 times a week) ^d Supplementation with multivitamins and minerals ^* Obtained from ANOVA for continuous variables and chi-square test for categorical variables. Abbreviations: BMI: body mass index, MET: Metabolic equivalent of task

Women with breast cancer had higher intakes of total energy, total fat, saturated fatty acids (SFAs), and fruits than women without breast cancer (Table 2). They also consumed lower amounts of carbohydrates, protein, polyunsaturated fatty acids (PUFAs), monounsaturated fatty acids (MUFAs), thiamine, riboflavin, niacin, folate, whole grains, vegetables, red and process meats, poultry, legumes, and nuts.

Table 2

Dietary and nutrient intakes of study participants based on cases and controls as well as across quartiles of fish intake.
	Groups			Quartiles of fish intake
	Controls (n = 700)	Cases (n = 350)	P^*	Q1 n = 306	Q2 n = 218	Q3 n = 260	Q4 n = 266	P^*
Total energy intake (kcal/d)	2164 ± 25	2525 ± 36	< 0.001	2247 ± 39	2132 ± 46	2285 ± 42	2454 ± 42	< 0.001
Nutrient intakes
Carbohydrate (g/d)	320.6 ± 1.9	310.6 ± 2.8	0.005	323.0 ± 2.9	323.6 ± 3.4	322.0 ± 3.1	301.0 ± 3.1	< 0.001
Protein (g/d)	80.7 ± 0.7	71.3 ± 1.1	< 0.001	71.9 ± 1.1	75.9 ± 1.3	80.5 ± 1.2	82.5 ± 1.2	< 0.001
Total Fat (g/d)	81.6 ± 0.8	90.6 ± 1.1	< 0.001	85.0 ± 1.2	82.4 ± 1.4	81.2 ± 1.3	89.3 ± 1.3	< 0.001
Cholesterol (mg/d)	191.8 ± 3.7	185.0 ± 5.3	0.30	154.4 ± 5.2	180.8 ± 6.2	193.6 ± 5.7	233.0 ± 5.6	< 0.001
SFA (g/d)	27.6 ± 0.9	41.1 ± 1.3	< 0.001	37.3 ± 1.3	30.1 ± 1.6	27.7 ± 1.5	32.0 ± 1.4	< 0.001
PUFA (g/d)	11.0 ± 0.2	8.0 ± 0.3	< 0.001	8.6 ± 0.4	9.8 ± 0.4	10.4 ± 0.4	11.5 ± 0.4	< 0.001
MUFA (g/d)	20.8 ± 0.2	19.4 ± 0.3	< 0.001	19.0 ± 0.3	20.6 ± 0.3	20.7 ± 0.3	21.2 ± 0.3	< 0.001
n-3 Fatty acids (g/d)	0.88 ± 0.02	1.00 ± 0.03	0.002	0.82 ± 0.03	0.91 ± 0.03	0.91 ± 0.03	1.20 ± 0.03	< 0.001
Thiamine (mg/day)	2.0 ± 0.01	1.8 ± 0.02	< 0.001	2.0 ± 0.02	2.0 ± 0.03	2.0 ± 0.02	1.9 ± 0.02	0.002
Riboflavin (mg/day)	2.3 ± 0.01	2.2 ± 0.02	< 0.001	2.2 ± 0.02	2.3 ± 0.03	2.3 ± 0.02	2.3 ± 0.02	< 0.001
Niacin (mg/d)	26.5 ± 0.2	23.3 ± 0.3	< 0.001	24.7 ± 0.3	25.2 ± 0.4	26.5 ± 0.3	25.4 ± 0.3	0.003
Folate (µg/d)	605.5 ± 4.3	551.0 ± 6.1	< 0.001	585.1 ± 6.5	588.2 ± 7.7	605.6 ± 7.1	571.3 ± 7.0	0.008
Food groups
Refined grains (g/d)	97.1 ± 2.8	90.0 ± 4.0	0.16	78.4 ± 4.1	97.4 ± 4.9	96.2 ± 4.5	110.0 ± 4.4	< 0.001
Whole grains (g/d)	326.1 ± 5.0	298.4 ± 7.1	0.002	343.5 ± 7.3	321.3 ± 8.7	329.4 ± 7.9	270.4 ± 7.9	< 0.001
Fruits (g/d)	149.2 ± 5.3	203.8 ± 7.6	< 0.001	157.7 ± 7.9	135.4 ± 9.3	163.2 ± 8.5	209.0 ± 8.4	< 0.001
Vegetables (g/d)	145.2 ± 3.3	110.6 ± 4.8	< 0.001	111.0 ± 4.9	118.7 ± 5.8	137.7 ± 5.3	168.1 ± 5.3	< 0.001
Red and processed meats (g/d)	84.6 ± 2.5	66.9 ± 3.6	< 0.001	70.8 ± 3.8	76.7 ± 4.5	87.8 ± 4.1	80.5 ± 4.1	0.02
Poultry (g/d)	67.0 ± 2.5	48.5 ± 3.6	< 0.001	58.9 ± 3.8	60.5 ± 4.5	66.0 ± 4.1	58.4 ± 4.0	0.52
Dairy (g/d)	229.6 ± 5.5	238.4 ± 8.0	0.378	200.5 ± 8.2	222.4 ± 9.7	236.6 ± 8.8	273.7 ± 8.8	< 0.001
Legumes (g/d)	16.1 ± 0.6	12.1 ± 0.8	< 0.001	12.0 ± 0.8	14.7 ± 1.0	15.2 ± 0.9	17.6 ± 0.9	< 0.001
Nuts (g/d)	3.0 ± 0.2	1.0 ± 0.3	< 0.001	1.1 ± 0.3	2.1 ± 0.4	3.2 ± 0.3	3.2 ± 0.3	< 0.001
Fish (g/d)	8.4 ± 1.2	10.9 ± 1.7	0.25	0.0 ± 0.0	2.0 ± 1.9	5.1 ± 1.8	29.8 ± 1.8	< 0.001
Data are presented as mean ± standard error (SE) *All values were adjusted for age and energy intake, except for dietary energy intake, which was only adjusted for age using ANCOVA. Abbreviations: SFA: saturated fatty acid; PUFA: polyunsaturated fatty acid; MUFA; monounsaturated fatty acid

Crude and multivariable-adjusted ORs along with the corresponding 95% confidence intervals (CIs) for breast cancers across quartiles of fish intake are outlined in Table 3. There was a significant inverse association between fish consumption and breast cancer (OR: 0.58; 95% CI: 0.42–0.82, P_trend=0.001), even after adjusting for potential confounders (OR 0.57; 95% CI 0.34–0.95, Ptrend = 0.02); indicating that higher fish consumption was associated with a lower odds of breast cancer.

Table 3

Multivariable-adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) for breast cancer across quartiles of fish intake
	Quartiles of fish intake
	Q1	Q2	Q3	Q4	P _trend^*
Crude	1.00	0.33 (0.22–0.48)	0.38 (0.27–0.55)	0.58 (0.42–0.82)	0.001
Model 1	1.00	0.36 (0.24–0.54)	0.40 (0.27–0.58)	0.52 (0.36–0.74)	< 0.001
Model 2	1.00	0.34 (0.22–0.53)	0.40 (0.27–0.60)	0.56 (0.38–0.84)	0.003
Model 3	1.00	0.37 (0.23–0.58)	0.48 (0.31–0.74)	0.59 (0.37–0.95)	0.02
Model 4	1.00	0.32 (0.19–0.52)	0.49 (0.30–0.78)	0.57 (0.34–0.95)	0.02
Model 1: Adjusted for age and energy intake Model 2: Additionally, adjusted for education, marital status, social economic status, residential area, supplement use, family history of breast cancer, disease history, physical activity, smoking, alcohol drinking, breast feeding history, and menopausal status Model 3: Further adjustment for refined grains, whole grains, fruits, vegetables, dairy, nuts, legumes, and n-3 Fatty acids Model 4: Additional adjustment for BMI *Obtained from binary logistic regression

In the stratified analysis by menopausal status (Table 4), there was no significant association between fish intake and chance of breast cancer among premenopausal women, neither before (OR: 0.49; 95% CI: 0.20–1.18) nor after considering potential confounders (OR: 0.15; 95% CI: 0.02–1.84). However, greater fish intake was inversely associated with the chance of breast cancer in postmenopausal women (OR: 0.62; 95% CI: 0.43, 0.90). The association was robust after controlling for potential confounders (OR: 0.53; 95% CI 0.30, 0.94). Moreover, there was a significant inverse relationship between fish consumption and the chance of breast cancer in normal-weight women (OR: 0.41; 95% CI: 0.21, 0.80), while no association was found in overweight or obese women (OR: 1.60; 95% CI: 0.49, 5.27) (Table 5).

Table 4

Multivariable-adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) for breast cancer across quartiles of fish intake stratified based on menopausal status
	Quartiles of fish intake
	Q1	Q2	Q3	Q4	P _trend^*
Premenopausal women
Crude	1.00	0.06 (0.01–0.30)	0.26 (0.10–0.69)	0.49 (0.20–1.18)	0.37
Model 1	1.00	0.07 (0.01–0.32)	0.25 (0.09–0.66)	0.47 (0.19–1.2)	0.34
Model 2	1.00	0.07 (0.01–0.37)	0.30 (0.10–0.90)	0.55 (0.17–1.80)	0.55
Model 3	1.00	0.08 (0.01–0.53)	0.34 (0.08–1.33)	0.71 (0.14–3.49)	0.77
Model 4	1.00	0.01 (0.01–0.12)	0.24 (0.03–1.63)	0.15 (0.02–1.84)	0.94
Postmenopausal women
Crude	1.00	0.41 (0.27–0.62)	0.43 (0.29–0.63)	0.62 (0.43–0.90)	0.005
Model 1	1.00	0.44 (0.28–0.67)	0.43 (0.29–0.65)	0.49 (0.33–0.73)	< 0.001
Model 2	1.00	0.42 (0.27–0.66)	0.43 (0.28–0.67)	0.53 (0.34–0.82)	0.002
Model 3	1.00	0.40 (0.24–0.66)	0.50 (0.31–0.80)	0.55 (0.32–0.93)	0.01
Model 4	1.00	0.34 (0.20–0.58)	0.48 (0.28–0.78)	0.53 (0.30–0.94)	0.01
Model 1: Adjusted for age and energy intake Model 2: Additionally, adjusted for education, marital status, social economic status, residential area, supplement use, family history of breast cancer, disease history, physical activity, smoking, alcohol drinking, and breast-feeding history Model 3: Further adjustment for refined grains, whole grains, fruits, vegetables, dairy, nuts, legumes, and n-3 Fatty acids Model 4: Additional adjustment for BMI *Obtained from binary logistic regression

Table 5

Multivariable-adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) for breast cancer across quartiles of fish intake stratified by BMI status
	Quartiles of fish intake
	Q1	Q2	Q3	Q4	P _trend^*
Normal-weight women
Crude	1.00	0.30 (0.19–0.48)	0.53 (0.34–0.82)	0.56 (0.36–0.86)	0.02
Model 1	1.00	0.31 (0.19–0.50)	0.51 (0.32–0.81)	0.47 (0.30–0.75)	0.004
Model 2	1.00	0.32 (0.19–0.53)	0.54 (0.33–0.90)	0.50 (0.30–0.85)	0.02
Model 3	1.00	0.35 (0.20–0.61)	0.69 (0.39–1.21)	0.47 (0.25–0.87)	0.04
Model 4	1.00	0.34 (0.18–0.61)	0.66 (0.36–1.18)	0.41 (0.21–0.80)	0.03
Overweight or obese women
Crude	1.00	0.30 (0.13–0.69)	0.23 (0.11–0.49)	0.78 (0.43–1.41)	0.27
Model 1	1.00	0.37 (0.15–0.88)	0.24 (0.11–0.53)	0.67 (0.36–1.27)	0.14
Model 2	1.00	0.39 (0.15–1.01)	0.23 (0.10–0.54)	0.72 (0.34–1.53)	0.17
Model 3	1.00	0.46 (0.15–1.46)	0.33 (0.12–0.88)	1.65 (0.52–5.19)	0.50
Model 4	1.00	0.34 (0.11–1.07)	0.31 (0.11–0.84)	1.60 (0.49–5.27)	0.54
Model 1: Adjusted for age and energy intake Model 2: Additionally, adjusted for education, marital status, social economic status, residential area, supplement use, family history of breast cancer, disease history, physical activity, smoking, alcohol drinking, breast feeding history, and menopausal status Model 3: Further adjustment for refined grains, whole grains, fruits, vegetables, dairy, nuts, legumes, and n-3 Fatty acids Model 4: Additional adjustment for BMI *Obtained from binary logistic regression

In this case-control study, we found an inverse association between fish consumption and chance of breast cancer, indicating that a higher fish intake was associated with a lower odds of breast cancer. Despite the absence of a significant association in premenopausal women, we found a protective association between normal weight and postmenopausal women.

According to the World Health Organization (WHO) report, over 2.3 million women will be diagnosed with breast cancer by 2050 [31, 32]. Breast cancer has been recognized as the most common kind of cancer among Iranian women and is associated with a significant burden of mortality, based on crude mortality statistics. [33, 34]. Previous studies demonstrated that diet exerts an effect on the risk of developing breast cancer [35]. Even though a variety of dietary components have been studied in relation to breast cancer, fish consumption has gotten little attention to this point. The present study revealed that fish consumption was associated with a reduced risk of breast cancer, particularly in postmenopausal women. In keeping with our findings, a Korean case-control study indicated a protective association between fish intake and breast cancer risk [16]. This was also observed in a prospective study of 35,298 Chinese Singaporean women followed for five years. Also reported is the beneficial relationship between fish consumption and other forms of cancer, including colorectal, liver, and lung cancers [36–38]. In contrast to our findings, Kiyabu et al. [39] found no association between total fish consumption and breast cancer risk in a 14-year prospective analysis of Japanese women. Another cohort study of British women revealed no relationship between fish consumption and breast cancer incidence [40]. In addition, a prospective cohort study of Danish postmenopausal women revealed that women with a higher fish consumption had a greater risk of developing breast cancer [18]. Various factors, including sample size, considering several potential confounders, cancer stage at diagnosis, different cooking methods across various populations, different ranges of fish consumption, and different types of fish, such as salted, oily, and lean fish, may explain these divergent findings across different studies in different regions [41] as well as different methodologies used to examine fish intake and breast cancer. Furthermore, the role of measurement errors in dietary assessment cannot be ignored [27].

Multiple mechanisms may explain the beneficial association between fish consumption and breast cancer risk. Previous research has linked the preventive effect of fish against breast cancer to its high omega-3 PUFA concentration [16, 19]. Omega-3 PUFA may reduce breast cancer risk by downregulating the inflammatory cascade, increasing fatty acid (FA) breakdown while decreasing FA production, causing apoptosis and inhibiting cell proliferation [42, 43]. In addition, n-3 PUFA could reduce estrogen synthesis, hence inhibiting estrogen-induced cell proliferation [44, 45]. Specifically, studies employing cell lines and mouse models have demonstrated that n-3 PUFA inhibit the formation of breast tumors [46]. In addition, the anti-inflammatory properties of EPA (Eicosapentaenoic acid) and DHA (Docosahexaenoic acid) and their ability to alter the fatty acid structure of cell membranes make susceptible individuals’ suitable candidates for breast cancer prevention [43, 47]. Fish also include essential micronutrients such as magnesium, phosphate, potassium, and protein, which might have a role in this regard [48–50]. In addition, fish has been recognized as a key source of B-vitamins, including riboflavin, niacin, and folate [51], which the breast cancer-preventive benefits of these nutrients have been shown in prior studies [52–54]. Fish may be contaminated by environmental contaminants such as heavy metals, pesticides, or organic pollutants, which may have estrogenic effects [55]. These constituents in fish may diminish or even negate the health benefits of eating fish [56]. Because these chemicals accumulate in fat tissue, one would expect the increased risk to be greater with higher eating of fatty fish compared to ingestion of lean fish [55]. In the current study, after stratification by menopausal status, the protective link of fish consumption remained significant for postmenopausal women but was no longer significant for premenopausal women. This discrepant outcome may be explained by the small number of premenopausal women in our study (23% of controls and 12% of breast cancer patients). Additionally, premenopausal and postmenopausal women differ in reproductive and adiposity characteristics that have opposing effects on breast tissue sensitivity [57, 58].

Several potential strengths of the current investigation must be highlighted. Accurate assessment of study exposure and adjustment for a wide range of confounding variables, an acceptable sample size, and being the first study among women in the Middle East can be noted. In addition, newly diagnosed cases of breast cancer were included in this investigation. Therefore, changes in dietary intakes were less likely. we also calculated energy adjusted amount of fish intake in this study, which can help reduce participants’ misclassification. The limitations of this study, however, should be considered when interpreting its findings. A major limitation of this study is cancer treatment before dietary assessments. Therefore, the precision of acquired data indicating fish frequency may be impacted by a random error known as diagnostic bias and due to the nature of case-control studies, our study was susceptible to selection and recall biases, which would make it impossible to assume causality. Furthermore, as with other epidemiological studies, the use of FFQ may result in participants’ misclassification. Although we used a validated FFQ for dietary intake assessment, this FFQ was validated in a nonmalignant population, so there is cause for concern for populations with cancer and during cancer treatment. Second, the relationship between breast cancer and nutrition is complicated, particularly because breast cancer is a multifactorial and complex disease. Third, we also did not investigate the types of fish (fatty or lean), their sources (sea/salty water or fresh water), or their preparation methods (boiled, fried, salted, canned, etc.), which could have an impact on the observed association. It is suggested that these characteristics be taken into account in future studies on fish consumption. Fourth, we did not collect information on estrogen or progesterone receptor status, as well as breast cancer stage. Fifth, breast cancer patients may recall their past diet differently in the context of their cancer diagnosis, or they might have altered their diet prior to diagnosis as a result of early signs of the disease. Sixth, the IPAQ questionnaire used in our research assesses physical activities performed by individuals during the previous nine days, which does not account for total lifetime physical activity. The questionnaire assesses current activity levels across various domains of physical activity during a typical week. Consequently, our investigation did not assess patterns of lifetime physical activity. In addition, sedentary behavior data were not considered in our survey, and we focused primarily on assessing various domains of physical activity, such as work-related activities, transportation, domestic chores, and leisure activities. Seventh, it is impossible to rule out the possibility of residual confounding in this study as in all observational studies. Finally, over 80% of the population were postmenopausal women, and it would be interesting to conduct additional research on premenopausal women.

The current case-control study found a statistically significant inverse association between fish consumption and likelihood of having breast cancer, especially in postmenopausal women. This finding is significant in light of the region's low fish consumption. These data support the role of food in breast cancer prevention.

Acknowledgements

Not applicable.

Authors’ contributions

CA, and AE contributed in conception, design, statistical analyses, data interpretation and manuscript drafting. SBK, HH and LA contributed in data collection, interpretation and manuscript drafting. FF contributed to the data analysis and approving the final manuscript. AE supervised the study. All authors contributed to the article and approved the submitted version.

Funding

No financial support was provided in any way for this research.

Availability of data and materials

The datasets generated and/or analyzed during the current study are not publicly available, but are available from the corresponding author at reasonable request.

Conflict of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Ethics approval and consent to participate

The study was performed by the ethical standards promoted by the 1964 Declaration of Helsinki and its later amendments, and the Ethical Committee approved its protocol of Isfahan University of Medical Sciences in Isfahan, Iran. Informed consent was taken from all study participants after acquaintance with the study methodology.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Author details

¹Department of Clinical Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran.

²Hypertension and Cardiovascular risk factors Research Center, Medical and Surgical Sciences Department, Alma Mater Studio rum University of Bologna, Bologna, Italy

³Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran.

⁴Faculty of Medicine, Iran University of Medical Sciences (IUMS), Tehran, Iran

⁵Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran

⁶Department of Community Nutrition, School of Nutrition and Food Science, Isfahan University of Medical Sciences, Isfahan, Iran

⁷Obesity and Eating Habits Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.

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Fish consumption in relation to breast cancer: A case-control study

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Abstract

INTRODUCTION

METHODS

Study population

Dietary intakes assessment

Breast cancer assessment

Assessment of covariates

Statistical analysis

RESULTS

DISCUSSION

Declarations

References

Additional Declarations

Status:

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