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LITHUANIAN UNIVERSITY OF HEALTH SCIENCES
ACADEMY OF MEDICINE
FACULTY OF PUBLIC HEALTH
Nitika Singh
A CASE-CONTROL STUDY TO ASSESS RISK FACTORS OF
BREAST CANCER AMONG PATIENTS OF HOSPITAL OF
LITHUANIAN UNIVERSITY OF HEALTH SCIENCES KAUNO
KLINIKOS
Master thesis
Program: Applied Public Health
Student
Nitika Singh
Supervisor: Dr. Loreta Strumylaitė Consultant: Dr. Eglė Jonaitienė
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SUMMARY
Applied Public Health
A CASE-CONTROL STUDY TO ASSESS RISK FACTORS OF BREAST CANCER AMONG PATIENTS OF HOSPITAL OF LITHUANIAN UNIVERSITY OF HEALTH SCIENCES KAUNO KLINIKOS
Nitika Singh
Supervisor: Dr. Loreta Strumylaitė MD, DSc, Department of Preventive Medicine Consultant: Dr. Eglė Jonaitienė MD, PhD, Clinic of Radiology of LSMU Hospital
Faculty of Public Health, Medical Academy, Lithuanian University of Health Sciences, Kaunas; 2020.
Aim of the study: To evaluate associations between breast cancer and lifestyle, environmental and socio-economic factors.
Objectives
1. To analyse the associations of lifestyle factors with breast cancer. 2. To explore the connections of environmental factors with breast cancer. 3. To determine the role of socio-economic factors with breast cancer.
Methodology: A Case-control study involving 55 patients with breast cancer and 97 controls was conducted in the Hospital of Lithuanian University of Health Sciences Kauno Klinikos from August 2019 to February 2020. A structured questionnaire was used to gather information from the participants. Multivariate unconditional logistic regression was used to calculate odds ratio (OR) and 95% confidence interval.
Result: After adjustment for age, alcohol and education, the ORs of breast cancer in woman who eat sour cream and curd/curd cheese more than 5-6 times per week were 3.49(95% CI 1.30-9.42) and 3.87(95% CI 1.18-12.68), respectively. OR of breast cancer was 3.68(95% CI 1.46-9.24) in women who don’t drink ground bean coffee. Our data didn’t define the association between breast cancer risk and smoking, alcohol. We didn’t find an association between breast cancer risk and environmental factors like dust, chemical, other harmful factors, stress at work, shift work and night shift. The OR of breast cancer was 0.42(0.19-0.92) in women who are living in a village after adjustment for age, alcohol and
3 education. We didn’t find an association between breast cancer and income, education and marital status.
Conclusion: Sour cream, curd/ curd cheese is associated with about 4 times higher breast cancer risk, however, drinking ground bean coffee is related to about 4 times lower risk of breast cancer. Living in a village is related to 2 times lower breast cancer risk as compared to living in cities / towns. Since sour cream, curd cheese, and coffee drinking are a modifiable risk factor for breast cancer, every woman should be informed and advised to eat less sour cream, curd/ curd cheese and add ground bean coffee in their dietary habits. Statistically significant association between breast cancer risk and use of alcohol, smoking, consumption of different sorts of breads, vegetables, fruits, dairy products and meat product is not found. Different factors of work environmental factors and other socioeconomic factors are not related to breast cancer risk.
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TABLE OF CONTENTS
ACKNOWLEDGEMNT ………. 5
LIST OF ABBREVIATIONS ………. 6
1. INTRODUCTION ……… 7
AIMS AND OBJECTIVES ………. 9
2. LITERATURE REVIEW ………. 10
2.1. Lifestyle factors and breast cancer ………. 10
2.2. Environmental factors and breast cancer ……… 16
2.3. Socioeconomic factors and breast cancer ……… 18
2.4. Risk factors related to breast cancer ……… 21
3. RESEARCH METHODOLOGY ………... 23
3.1. Type of research ………. 23
3.2. Research method ………. 23
3.3. Research instrument ……… 23
3.4. Statistical data analysis ……… 24
3.5. Research ethics ……… 25
4. RESULT ……… 26
4.1. Characteristics of study group ……… 26
4.2. The associations of lifestyle factors with risk of breast cancer ... 27
4.3. The association of environmental factors with risk of breast cancer ... 37
4.4. The association of socio-economic factors with breast cancer ... 38
DISCUSSION OF RESULT ... 40 CONCLUSION ... 43 PRACTICAL RECOMMENDATIONS ... 44 LITERATURE ... 45 ANNEX 1 ... 50 ANNEX 2 ... 60
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ACKNOLEDGEMENT
The long and challenging journey would not have come to end without the help of many people who helped me; with all my heart I would like to thank each one of them.
I would like to thank Dr. Loreta Strumylaitė for guiding me during this tough but worthy journey of writing a thesis on the assessment of breast cancer risk factors in patient of a hospital of Lithuanian University of Health Sciences Kauno Klinikos. Dr. Strumylaitė had given her invaluable time and effort to guide me during this thesis without her help my work would not have been possible. Her loving and caring nature for her students is admirable. Along with a profound knowledge base she gave me and also helped me to organize my thesis work so that I can do my work in the limited time I had. The academic staff of LSMU who have taught me subjects that have helped me to transfer the knowledge I gained into a thesis work, their efforts and commitment helped me to develop my career in the Public health domain. I would like to thank my father “Mr. Minender Singh” and mother “Mrs. Lalita Devi” who always motivated me to focus on work and to produce good results from my work. Their trust in me had helped me sail through the tough and challenging time of my thesis work. My research work could not have been a reality without the help and support of Dr. Eglė Jonaitienė who collected initial data and organized it in an effective manner which was the basis for my thesis work. Besides, I am thankful to Professor Rima Kregždytė and Professor Janina Petkevičienė who helped me to analyse data in SPSS software which is very crucial for my research work. My friends Anchit Yadav, Anshul Pagariya, Nitish Virmani also kept me motivated and happy during this challenging period, their presence has helped me to produce this research work. At last, I would like to thank almighty god for showering the blessing on me.
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LIST OF ABBREVIATION
IARC: International Agency for Research on Cancer
WHO: World Health Organization OR: Odds Ratio
CI: Confidence interval BMI: Body Mass Index ER: Estrogen Receptor
PR: Progesterone Receptor
HR: Hazard Ratio
CBC: Contralateral Breast Cancer RR: Risk Ratio
SRR: Summary Relative Risk
PCB: Poly Chlorinated Biphenyl PBDE: Poly Brominated Diethyl Ether MEHP: Mono Ethyl Hexyl Phthalate PBDEs: Poly Brominated Diphenyl Ethers PCBs: Poly Chlorinated Biphenyls
PBB: Poly Brominated Biphenyl OCPs: Organo Chlorine Pesticides PFAAs: Per Fluoro Alkyl Acids
GLOBOCAN- Global Cancer Incidence, Mortality and Prevalence.
TNM: Tumour, Node, Metastasis
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1. INTRODUCTION
Breast cancer is the most common cancer in the women worldwide. Every year it affects more than two million women and also causes the highest number of death among women.[1] In 2018, there were 2 088 849 breast cancer incidence cases worldwide and estimating an increase in the incident cases to 2 407 748 in 2025. [2] Globally, the incidence rate varies significantly from 19.3 per 100,000 women in Eastern Africa to 89.7 per 100,000 women in Western Europe. The incidence rate os below 40 per 100000 in the most of the developing regions. African countries have the lowest incidence rate for cancer but for breast cancer incidence rates are increasing.[3]
In 2018, breast cancer incident cases were 522 513 in all over the Europe and is estimating an increase in the breast cancer cases from 522 513 to 545 723 in 2025. The number of deaths from breast cancer were 626 679 worldwide, of which 137 707 were in Europe. Estimated number of prevalent cases (5 year) in 2018 were 6 875 099 worldwide and in Europe were 2 054 887. [3]
In 2018, breast cancer was the most common cancer site (28.2% of all cancers) in the European female population and also the leading cause of death (16.2% of cancer death). Northern and Western Europe had the highest rate of breast cancer incidence. [4]
In 2018, number of incident cases in Lithuania were 1742 and estimating a reduction to 1727 cases in 2025. Deaths from breast cancer in Lithuania were 575 in 2018 and estimating an increase in the number of deaths to 577 in 2025 with 6733 cases during 5-year prevalence. [2] In Lithuania, the mortality rate was higher than the average of European (22.7 vs. 21.8 per 100,000 women), while the estimated incidence rate was below the European average (80.6 vs. 100.9 per 100,000 women. [4]
According to The World Health Organization (WHO) about one third of deaths from cancer are because of factors related to lifestyle, such as lack of physical activity and high body mass index, low intake of fruit and vegetable, and use of tobacco and alcohol. [5] Alcoholic beverages are a proved risk factor of breast cancer. Other risk factors for the disease with sufficient evidence in humans are the use of estrogens and estrogen-progestogen as contraceptives or menopausal therapy, X and gamma radiation. [6]
Age, factors related to reproductive life, family history on breast cancer and socioeconomic status are also known risk factors for breast cancer. These factors can explain only part of breast cancer cases.
8 The other part can be related to other lifestyle or environmental risk factors such as active and passive smoking, solar radiation, exposure to different chemicals.[7]
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AIMS AND OBJECTIVES
Aim
To evaluate associations between breast cancer and lifestyle, environmental and socio-economic factors.
Objectives
1. To analyse the associations of lifestyle factors with breast cancer. 2. To explore the connections of environmental factors with breast cancer. 3. To determine the role of socio-economic factors with breast cancer.
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2. LITERATURE REVIEW
2.1. LIFESTYLE FACTORS AND BREAST CANCER
A study done by Dieterich M. et al. found some of the factors like smoking, stress, obesity, diabetes mellitus being risk factors for breast cancer. other factors like physical activities and healthy diet found to be prevented for risk of breast cancer and some of them like breast implant had no significant risk for breast cancer. Author also advised that small changes in daily routine habit can prevent the risk of breast cancer during menopause age and that is up to 34% because breast cancer is multiethiological disease. [8]
A Randomized controlled trial was done by Livaudais-Toman J. L. et al. to estimate the impact of a primary based intervention on breast cancer knowledge, risk perception and concern. The study includes women with no personal history of breast cancer, and randomized them to the control group or primary care setting intervention group and found that 655 patients completed follow-up interview and 580 intervention. During follow-up, 71% of intervention and 73% of control women perceived their risk of breast cancer correctly.24% intervention and 22% control women were concerned about breast cancer. At follow-up (24% vs. 16%; p = 0.002), intervention women have more knowledge (OR = 1.62, 95% CI:1.19-2.23) of breast cancer risk as they correctly answered ≥ 75%.[9]
Kaminska M. et al. done a study on breast cancer risk factors. When all the risk factors initiating the process are considered to be a criterion for influencing the individual neoplasty transformation process, they were divided into two groups, intrinsic and extrinsic group. In the intrinsic group, the key factor was age, sex, race, and genetic makeup and extrinsic group lifestyle, diet, long term medical interventions, oral hormonal contraceptive, and/or hormonal replacement therapy were included. The intrinsic group found occurrence of benign proliferative lesions in the mammary gland and the extrinsic group identify that the factors that can be modified may help develop preventative strategies that reduce the incidence of breast cancer. [10]
2.1.1. Alcohol and breast cancer
A hospital-based case-control study was carried out by Strumylaite et al. The study included 585 breast cancer cases and 1170 controls showed low-to-moderate alcohol intake was associated with higher risk of breast cancer. After adjustment for age and other confounders women who consumed ≤5
11 drinks/week and 5 drinks/week had 1.75- and 3.13-times greater risk of breast cancer compared with non-drinkers for ≥10 years. It has been also found that low-to- moderate alcohol use was related to the risk of estrogen receptor-positive breast cancer with the strongest association in postmenopausal women.[11]
Ellingjord-Dale M et al. done a case control study based on the Norwegian Breast Cancer Screening Program included 4402 breast cancer cases and five controls matched to each case. The authors compared never drinker to the current alcohol 6+ glasses a week and found breast cancer risk associated with current alcohol consumption [OR=1.26, 95% CI:1.09–1.45]. However, this increase in risk was found only for luminal A–like breast cancer. The authors concluded that luminal A–like breast cancer subtype is associated with current use of alcohol.[12]
2.1.2. Body Mass Index (BMI) and breast cancer
In 2016, a case-control study was done by J. Nguyen et al. In this study, 492 breast cancer cases and 1306 controls with an age range from 25 to 75 were included. There were no significant differences between cases and controls in height (154.8 cm vs. 155.4 cm, 𝑝 = 0.1). In this study, the authors found a positive association of increasing BMI with risk of breast cancer.[13]
A case-control study and meta-analysis of BMI and breast cancer molecular subtypes was done by Li H. et al. The study included 1256 breast cancer cases and 1416 healthy women as controls. The authors found that the risk of both luminal and triple-negative tumors is associated with higher BMI (P trend<0.001). Meta-analysis was found positive dose responses between BMI and risk of both ER-PR and luminal subtypes (P trend<0.05).[14]
In contrast, Ekenga C. et at. studied the risk of breast cancer in 47,649 women participated in a sister study with an occupational history and 1798 women were diagnosed with breast cancer during follow-up, found a significantly lower risk of breast cancer in women having BMI ≥ 25 and ≥ ¾ active work (HR 0.64; 95 % CI 0.42–0.98).[15]
2.1.3. Dietary habits and breast cancer
Mobarakeh et al. done a case control study among Iranian women and found that heavy consumption of fat products like cheese and milk was significantly related to higher risk of breast cancer. No use of mayonnaise in salad and use of olive oil in cooking decreased risk of breast cancer. High consumption of fruits and vegetable was also related to lower risk of breast cancer.[16]
12 Castello A. et al. conducted a case control study among Spanish women to find out the connection between dietary pattern and risk of breast cancer. Author included three types of dietary pattern, first, western pattern – was characterized by high intakes of high-fat dairy products, processed meat, refined grains, sweets, caloric drinks and other convenience food and sauces and by low intakes of low-fat dairy products and whole grains. The second dietary pattern – named Prudent pattern – denoted high intakes of low-fat dairy products, vegetables, fruits, whole grains and juices. The third dietary pattern– the Mediterranean pattern – loaded high in fish, vegetables, legumes, boiled potatoes, fruits, olives and vegetable oil, and low in the juices. The study included 1017 cases and 1017 controls and found that higher risk of breast cancer was related to the western dietary pattern (OR =1.46 95% CI 1.06–2.01), mainly in premenopausal women (OR= 1.75; 95% CI 1.14–2.67) on the other there was lower risk related to the Mediterranean pattern (OR = 0.56 (95% CI 0.40–0.79) and there was no association between Prudent dietary pattern and risk of breast cancer. The results of this study confirmed that all breast cancer subtype, mainly triple-negative tumours are preventable if the diet is rich in fruits, vegetables, legumes, oily fish and vegetable oils. Higher risk of breast cancer was related to western dietary pattern.[17]
Ahmed K. et al. carried out a descriptive case-control study to examine the association of different factors with breast cancer. Fatty food, marital status and use of alcohol were non-significant factors for breast cancer in the study. Author concluded that the visualization of the non-significant factors for breast cancer will help increase awareness among women from Bangladesh and around the world.[18]
2.1.4. Physical activity and breast cancer
A study of physical activity and risk of breast cancer in postmenopausal women was carried out by Eliassen A.H et al., In this study 95,396 women were followed up for 20 years. The authors reported that women who walked briskly >1 hour /day had 1.2 times lower risk of breast cancer (HR=0.85, 95% CI, 0.78-0.93; P for trend <0.001) compared to those walking briskly & <1 hour/day. Lower risk of breast cancer was associated with increasing physical activity at menopausal and postmenopausal women.[19]
A case-control study carried out by Yen S. et al. in Kelantan, Malaysia. The aim of this study was to explore an association between lifetime physical, occupational, household, recreational/sports activity
and risk of breast cancer. The study included 122 cases of breast cancer and 121 controls and found no association between breast cancer and lifetime physical, occupational and sports/recreational activities among Kelantanese women. Lifetime Household activities significantly reduce the risk of breast cancer.[20]
13 Ellingjord-Dale M. et al., conducted a nested case control study from the Norwegian Breast Cancer Screening Program and found that the physical activity (4+hr/week vs. none) has been associated with 15% lower luminal-A cancer risk, the relationship was not clear in other subtypes of breast cancer. The authors concluded that luminal A–like breast cancer subtype is associated with physical activity.[12]
2.1.5. Breast feeding and breast cancer
A prospective cohort study done by Butt S. et al., to identify the relation of breastfeeding duration to the risk of breast cancer’s different subgroups. The study included 14092 women and followed a mean of 10.2 years and 424 breast cancer incidents were diagnosed. Results showed that all quartiles of breastfeeding have similar risk for breast cancer and there is no association between breastfeeding duration with the risk of different subgroups of breast cancer.[21]
Akbari A. et al. carried out a case control study among Iranian women. The study included 376 cases and 425 controls and matched according to socioeconomic status, reproductive issues and demographic variants. The data showed that parity reduced the risk of Breast Cancer (OR=1.8, CI:1.3– 2.7, p<0.001,) and breastfeeding is protective (OR=0.39, 95% CI:0.27–0.56, p = 0.0001). The authors found the best result with 1–3 parity and 24 months breast feeding and mean duration of 18–24 months per child (OR=0.7, 95% CI:0.5–0.98, p = 0.037). It has been also found that efficient breastfeeding with full term pregnancies and parities decreased the risk of breast cancer than with nonpregnant and nulliparous women or never breastfed women. The authors recommended 1-3 number of pregnancies and duration of breastfeeding not less than 18 months.[22]
2.1.6. Reproductive factors and breast cancer
Risk of breast cancer and its connection with anthropometric and reproductive factors in the UK Biobank female cohort based prospective study of 273,436 females were studied by Al-Aimi K. et al. in 2018. Over 9 years of follow up authors found the breast cancer cases were 14,231with 3,378 (23.7%) incident cases with an incidence rate of 2.09 per 1000 person-year. In pre-menopausal, having a low BMI, first degree family history of breast cancer, nulliparous, high reproductive interval index, low waist to hip ratio, late age at first live birth, an increase in age, height, early menarche age, and long contraceptive use duration were all significantly associated with an increased breast cancer risk. In post-menopausal, being taller, having a high BMI, getting older, nulliparous, late age at first live birth, and high reproductive interval index, first degree breast cancer family history were all significantly associated
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with an increased risk of breast cancer. Breast cancer risk reduction up to 50% can be achieved by lower reproductive interval index, an early first live birth, and increased number of children suggested by population attributable fraction (PAF).[23]
De Almeida G. et al. done a case-control study titled “Reproductive Risk Factors Differ Among Breast Cancer Patients and Controls in a Public Hospital of Paraiba, Northeast Brazil”. The study included 81 cases of breast cancer and 162 aged-matched controls. The result showed that the risk of breast cancer was significantly increased in parous women with age at menarche ≤12, single parity and reproductive period >10 years was OR=2.120 CI:1.043-4.308, p=0.038, OR=3.748 CI:1.459-9.627, p=0.06 and OR=3.042 CI:1.421-6.512, p=0.04 respectively. The results showed that modifiable reproductive factors contribute to the risk of breast cancer. Women can reduce the risk of breast cancer through knowledge of factors such as the protective effects of breastfeeding.[24]
A case-control study and meta-analysis on reproductive factors and breast cancer molecular subtypes was done by Li H. et al. In this study, total 1256 breast cancer cases and 1416 controls were included. The result showed that Nulliparity and early menarche increased the luminal tumor risk by 1.39 and 1.26 times respectively. Women with non-breastfeeding have a high-risk for all subtypes (ORluminal=
1.35, ORER-PR-=1.74, ORHER2= 1.97, ORTriple-ve=1.85) in breast cancer. [14]
Ekenga C. et al. done a cohort study, which included 47,649 interviewed women and 1,798 women were diagnosed with breast cancer during follow-up. The authors found that the occupational activity
(HR=0.67, 95 % CI:0.45–0.98) reduces the risk of breast cancer for postmenopausal women.[15]
A descriptive case-control study carried out by Ahmed K. et al. found that the lack of awareness and illiteracy was the main cause of breast care. Patient’s mean age was 43.0, the significant factor in ascending order was hormone therapy (p<0.0000, OR=4.897), abortion (p<0.0001, OR=3.452), early start menarche (p<0.0002, OR=3.500), family history (p<0.0022, OR=3.235), and late menopause (p<0.0093, OR=3.674) with both χ2 test and logistic regression analyses. The authors concluded that the visualization of the correlation between significant factors for breast cancer will help in increasing awareness among women from Bangladesh and around the world.[18]
2.1.7. Smoking and breast cancer
A large cohort study done by Catsburg C. et al., included 89,835 women followed to a mean of 22.1 years, as a result, 6,549 incidences of breast cancer have been confirmed. The authors found that association of breast cancer with cumulative exposure (40 pack-years vs. 0: HR= 1.19; 95% CI=1.06– 1.13) , intensity (40 cigarettes per day vs. 0: HR=1.21; 95% CI=1.04–1.40), duration (40 years vs. 0:
15 HR=1.57; 95% CI =1.29–1.92), and latency (40 years since initiation vs. 0: HR=1.19; 95% CI=1.10– 1.53) of cigarette smoking, and higher risk of breast cancer was observed in the number of years smoking before pregnancy than in the comparative years after pregnancy (among parous women, 5 years pre pregnancy vs. 0: HR=1.18; 95% CI=1.10–1.26). The authors concluded a strong role of cigarette smoking in breast cancer etiology and emphasized the importance of timing of exposure.[25]
Knight A. et al. carried out a WECARE study, i.e. a large population-based case-control study. The study included 51,521 females with asynchronous contralateral breast cancer (CBC) and 52,212 controls. The authors found that the females exposed to both current smoking and current alcohol at the time of first breast cancer diagnosis increased the risk of breast cancer. (RR=1.62, 95% CI 1.24–2.11). CBC risk (RR=1.54, 95% CI 1.18–1.99) was elevated in the females who drank alcohol and smoked after diagnosed with breast cancer. Women who consumed ≥ 10 cigarettes per day was also associated with increased CBC risk (RR=1.50, 95% CI 1.08–2.08; p-trend=0.03).[26]
A cohort study was done by Anderson Z.J. et al. on active smoking and risk factor of breast cancer in a Danish nurse. The authors used the data of 21,831 female nurses from nationwide Danish Nurse Cohort. During the mean follow-up of 15.7 years, 1167 females developed breast cancer. At the cohort baseline 30% of nurses were former smoker and 33.7% were current smoker. After comparison with non-smoker versus non-smoker authors found a 18% increased risk of breast cancer in ever (RR=1.18, 95% CI=1.04-1.34) and 27% in the current (RR= 1.27, CI=1.11-1.46) smokers. Author also detected a dose-response relationship with an intensity of smoking with the risk of breast cancer and found a higher risk of breast cancer in the women who smoke >15 g/day (RR=1.31, CI=1.11–1.56) or >20 pack-years (RR=1.32, CI=1.12–1.55). The highest risk of breast cancer among parous women who heavily smoked (>10 pack-years) before first childbirth (RR=1.58; CI=1.20-2.1).[27]
A hospital-based case-control study performed by Strumylaite L. et al. found that lifetime exposure to passive smoking is associated with greater risk of breast cancer. Women who experienced exposure to passive smoking at home had almost 2 times (OR =1.88; 95% CI: 1.38-2.55) higher risk of breast cancer, women who had exposure at home and at work had almost 3 times greater risk (OR =2.80, 95% CI: 1.84-4.25) of breast cancer, both compared with never exposed regularly. There was no significant association between breast cancer risk and passive smoking at work.[28]
Ellingjord-dale M. et al. conducted a nested case control study from the Norwegian breast cancer screening program and found that smoking >20 cigarettes per day has a cumulative OR of 1.41 with significant patterns for HER2-negative, luminal B–like and luminal A–like cancer. Author concluded that luminal A–like breast cancer subtype was associated with smoking.[12]
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A meta-analysis of retrospective (case–control) and prospective (cohort) observational studies was conducted by Macacu A. et al. based on Active and passive smoking and risk of breast cancer. Meta-analysis of random effects has been used to calculate summary relative risk (SRR). Forever active smoking, in 27 prospective studies, the SRR for breast cancer was 1.10 (95 % CI [1.09–1.12]). In 44 retrospective studies, the SRR was 1.08 (95 % CI [1.02–1.14]). SRRs for current active smoking were 1.13 (95 % CI [1.09–1.17]) in 27 prospective studies and 1.08 (95 % CI [0.97–1.20]) in 22 retrospective studies. Forever passive smoking, in 11 prospective studies, the SRR for breast cancer was1.07 (95 % CI [1.02–1.13). In 20 retrospective studies, the SRR was 1.30 (95 % CI [1.10–1.54]). The authors found a consistent evidence that women who smoke tobacco have a moderate increase in their risk of breast cancer.[29]
2.2. ENVIRONMENTAL FACTORS AND BREAST CANCER
A case control study done by Holmes A. et al. to measure the association between breast cancer and exposure to select environmental chemicals among Alaska Native women. The study included 75 cases and 95 controls. Samples of urine and serum were collected from participants. Urine was analyzed for 10 phthalate metabolites and serum was analyzed for 34 polychlorinated biphenyl (PCB) congeners, 9 persistent pesticides, , and 8 polybrominated diethyl ether (PBDE) congeners and found that Cases had a lower serum concentration of most pesticides and 3 indicators PCB congeners (138/158; PCB-153, PCB-180) than controls. Cases (GM=38.8 ng/g lipid) had higher brominated diethyl ether-47 than controls (GM=25.1 ng/g lipid) (p=0.04). Who has urinary mono-(2-ethylhexyl) phthalate (MEHP) concentrations above the median were higher odds of being a case; this relationship was observed in both univariate (OR=2.16, 95% CI:1.16-4.05, p=0.02) and multivariable (OR=2.43, 95% CI:1.13-5.25, p=0.02) and also found that breast cancer may be associated with Exposure to the parent compound of the metabolite MEHP.[30]
Ekenga C. et al. done a prospective cohort study, 47,640 included participants were included and followed. 1,966 cases of breast cancer appear during follow through. The authors found an increased risk of breast cancer associated with the exposure to gasoline or petroleum products at the workplace (HR=2.3, 95%CI:1.1–4.9).[31]
A population-based case-control study done by Glass D. et al. to find out the association between occupational exposure to solvents and risk of breast cancer. The study included 1205 cases and 1789 controls and found about a one-third of women were exposed to the solvents occupationally. Women
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who were exposed to aliphatic solvents and aromatic solvents had a high risk of age adjusted breast cancer OR=1.21, 95% CI:0.99–1.48 and OR=1.21, 95% CI:0.97– 1.52 respectively.[32]
In 2017, Hegewald J. et al. done a case control study based on health insurance records. The study included 6643 cases and 471596 control of women aged ≥40 years. At 24-hour aircraft noise level 55-59dB, the authors observed an increased risk (OR 55–59 dB 1.41, 95% CI:1.04–1.90) for ER negative tumors but not for ER positive (OR 55–59 dB 0.95, 95% CI 0.75–1.20).[33]
A case control study is done by Wielsoe M. et al. in Inuit includes 77 cases and 84 controls to identify the associations between the serum levels in environmental pollutants and breast cancer. A sample of blood and information on reproductive history and lifestyle is collected from participants through a questionnaire. The serum levels were determined of 9 polybrominated diphenyl ethers (PBDEs),14 polychlorinated biphenyls (PCBs), 1 polybrominated biphenyl (PBB), 11 organochlorine pesticides (OCPs), and 16 perfluoroalkyl acids (PFAAs). After analysis, the authors found a positive association between breast cancer risk and PCBs and PFAAs and this association indicate exposure to Environmental Persistent Organic Pollutants may be a factor increasing the risk of breast cancer among Inuit women. [34]
A cohort study was done by Sorensen M. et al. on exposure to road traffic and railway noise and postmenopausal breast cancer. The study included 29,875 women and followed a mean of 12.3 years and 1,219 postmenopausal breast cancer cases were identified during follow-up. The authors found a higher risk of Estrogen Receptor Negative breast cancer during the previous 1, 5 and 10 years were associated with 28% (95% CI: 1,04–1, 56) and 23% (95% CI: 1,00–1,51) and 20% (95% CI: 1,97–1,48), by an increase in 10 dB road traffic noise, respectively. Furthermore, increasing the railway noise by 10 dB, increases the risk of breast cancer by 38% (95% CI: 1.01–1.89). Author found no association between estrogen receptor positive breast cancer and railway noise and road traffic. [35]
Andersen Z. et al. done a cohort study to examine the effect of long-term exposure to road traffic noise and incidence of breast cancer. The study included 22,466 women nurses. Data is collected by the Danish Cancer Registry on breast cancer incidence and from Danish Breast Cancer Cooperative. Author found a positive association between noise level and estrogen receptor positive (ER+) (HR=1.23, 95% CI:1.06–1.43, N=494), progesterone receptor positive (PR+) (HR=1.21, CI:1.02–1.42, N=393) and progesterone receptor negative (PR-) (HR=1.10, CI:0.89–1.37, N=218) breast cancer but not estrogen receptor negative (ER-) (HR=0.93, CI:0.70–1.25, N=117) breast cancer. [36]
Silva A. et al. done a case control study in the state of Mato Grasso, Brazil to evaluate the association between breast cancer and pesticide use. The study included 85 cases of confirmed breast
18 cancer women and 266 controls. The authors found a higher risk of developing breast cancer in the women aged more than 50 years and experienced early menarche (OR=2.08, 95% CI: 1.06–4.12) and the women who is living with pesticides near cropland (OR=2.37, 95% CI: 1.78–3.16).[37]
2.3. SOCIOECONOMIC FACTORS AND BREAST CANCER
Lyle G et al. done a systematic review in 2017 included 44 studies and found a higher incidence rate of breast cancer in women with higher socioeconomic status while the association between socioeconomic status and diagnosis were negative.[38]
A study is done by Coccia M. to evaluate the relationship between breast cancer incidence and per capita earnings across nations, data were obtained from GLOBOCAN in 52 countries, together with world bank economic indicators of gross domestic product per capita. Author found a powerful positive association between the incidence of breast cancer and per capita gross domestic product, Pearson's r= 65.4 percent, the estimated relationship indicates that 1 percent higher per capita gross domestic product increases the anticipated age-standardized incidence of breast cancer by about 35.6 percent (p< 0.001) within the temperate zones (latitudes). [39]
Fei X. et al. carried out a study on Urban-Rural Disparity of Breast Cancer and Socio-economic Risk Factors in China. The authors found a higher incidence rate of breast cancer in Urban regions (33.20/100,000 in 2005, 33.10/100,000 in 2006, 33.96/ 100,000 in 2007, 35.60/100,000 in 2008, and 34.25/100,000 in 2009, respectively) as compared to the rural region (12.23/100,000 in 2005, 13.24/100,000 in 2006, 15.63/100,000 in 2007, 15.52/100,000 in 2008, and 16.98/100,000 in 2009, respectively). About 2.3 times higher incidence rate in urban regions than in rural regions and observed that higher incidence of breast cancer was related to higher socio-economic status.[40]
A cross-sectional comparison between East and West is done Badr L. et al. to find out the breast cancer risk factors. This is a descriptive, cross-sectional comparative design that evaluated the risk factors for breast cancer. The study included 105 Lebanese American women with 250 Lebanese controls. The Lebanese- Americana group used contraceptives more, OR = 1.74, p = 0.027, breast fed longer χ2= 11.68, p = .008, , exercised more, OR = 1.61, p < 0.001, and consumed more vegetables, OR= 1.22, p = 0.002 and fruits, OR = 1.27 p = 0.001 than their Lebanese counterparts. The Lebanese group smoked more, OR = 1.42, p = 0.001, had menopause at an older age, t = 2.66, p = 0.05, and were five times more likely to live close to a main road or highway, OR = 5.75, p = 0.001 than the Lebanese-American group. Author concluded that Lebanese women had a higher risk of developing breast cancer and less awareness about
19 the advantages of breast cancer screening methods, which require the value of promoting healthy styles of life and education.[41]
2.3.1. Education and breast cancer
Liu Y. et al. done a study to Assess the impact of the diagnosis, clinical and pathological characteristics, implementation rate, and treatment selection of the educational levels of female breast cancer patients in China. The significant differences were found in the different educational level of the women in comparison with treatment choice and pathological characteristics. Patients’ education level was an independent factor of TNM staging at diagnosis. Patient with lower education was significantly found later tumor stage and implementation of correct investigation rate were lower and same with the choice of treatment or implementation of treatment. This study suggests that strategies should be developed for more precise and effective breast cancer prevention and treatment strategies for lower education patients.[42]
2.3.2. Income and breast cancer
Lehrer S. et al. done a study on affluence and breast cancer, in this study, author include high income, high socioeconomic status and affluence effect on increase in breast cancer incidence and in this study instead of block group socioeconomic status author took US census income data on breast cancer patient. The researcher found a significant connection between income and the incidence of breast cancer in 50 states of US data and Columbian women, r=0.623, p<0.001. In men significant positive correlation found in breast cancer between incidence and income, r= 0.098, p=<0.001.[43]
A retrospective study done by Riba L.A. et al. explore the association between socioeconomic factors and breast cancer. The data used from theNational Cancer Database consisted of 6,66,487 females diagnosed with breast cancer. The patients were classified by household income and insurance status. Household income was classified in 2 categories, high income (≥$63 000) and low income (<$63 000). The author found that the patients who diagnosed on later stages had lower income (<$63 000) (OR, 1.23; 95% CI, 1.21‐1.24) and no insurance (OR, 1.64; 95% CI, 1.58‐1.69). Higher chances of undergoing mastectomy for the patients with lower income (OR, 1.08; 95% CI, 1.07‐1.09) and no insurance (OR, 1.05; 95% CI, 1.01‐1.09). Patients with lower income (OR, 0.51; 95% CI, 0.50‐0.52) and no insurance (OR, 0.27; 95% CI, 0.26‐0.29) were less likely to receive immediate breast reconstruction. Patients with
20 lower income (OR, 0.90; 95% CI, 0.84‐0.96) and no insurance (OR, 0.52; 95% CI, 0.44‐0.61) were less frequent in administration of systemic therapy.[44]
2.3.3. Occupation and breast cancer
In 2017, a study on the influence of occupational level on breast cancer in China and diagnosis and treatment stages were done by Liu Y. et al. in China. The significant differences were found in different occupations of the women in comparison with treatment choice and pathological characteristics. These factors were independent factors of TNM staging diagnosis. Patient with the lower income occupation was significantly found later tumor stage and lower rate of implementation of correct investigation and same with the choice of treatment or implementation of treatment. This study suggests, for the patient with specific occupation groups, strategies should work in regard to treatment and effective breast cancer prevention. [42]
A population-based cohort study on the Occupation and Breast Cancer Risk Among Shanghai Women carried out by Ji B. et.al. A total of 74942 women data was taken from 1997 to 2007. In this study, previously diagnosed cases were 586 women with breast cancer and 438 women were newly diagnosed with breast cancer during follow-up. Eight controls from cancer-free cohort participants were selected at random for each case. Increased risk of breast cancer was found in engineering/forestry/agriculture technicians, teaching personnel, sewing workers/tailoring, and examiners/testers/measurers who started their career at least 20 years ago with the odds ratios of 1.6 (95% CI:1.0–2.4), 1.5 (95% CI:1.1–2.0), 1.6 (95% CI:1.0– 2.7) and 1.5 (95% CI:1.1–2.1) respectively. Also, breast cancer risk was significantly increased in health care workers/medical, administrative, clerical workers, postal/telecommunication workers, and odd-job workers started their career at least 20 years ago (OR=1.4, 95% CI:1.0–2.0), (OR=1.5, 95% CI:1.0–2.4), (OR=2.2, 95% CI:1.0–5.5) and (OR=1.7, 95% CI:1.1–2.8) respectively.[45]
A review was done by Engel C. et al. to find out the relationship between female breast cancer and their occupation. The review is done by 142 articles and suggested that the females who is working in the medical profession (OR=1.7, 95% CI: 1.04–2.79), as flight attendants(OR=1.40, 95% CI:1.30–1.50), sales and retail [42 % increase (OR=1.42; 95% CI:1.00–2.00)43 to more than double the risk (OR 2.2, 95% CI:1.00–4.80)], some production positions(OR=1.71, 95% CI: 0.99–2.95), and scientific technical staff are likely to have a higher risk of breast cancer. moreover, Exposure to ionizing radiation (OR=1.6, 95% CI: 1.1–2.2), job stress (HR=1.40, 95% CI; 1.1–1.9), night-shift work[4% (RR=1.04; 95% CI: 1.00–
21 1.10) to 79% (RR=1.79, 95% CI: 1.25–2.57)], sedentary work (HR=1.70; 95% CI:1.13–2.55) and exposure to some chemicals like the solvent (OR=1.15, 95% CI: 0.98–1.35)and pesticides (RR=2.6, 95% CI: 1.1–5.9) at work may increase the risk of breast cancer. On the other hand, physical activity at work reduced the risk of breast cancer.[46]
Liu T. et al. done a meta-analysis is done to assess the breast cancer risk among Female Flight attendants. The authors conducted a random effect model to calculate standard incidence ratios (SIR) and 95% confidence interval and found that the SIR was 1.40 (95% CI:1.30–1.50) for breast cancer in female flight attendants, therefore the risk of breast cancer is higher in female flight attendants than the general public.[47]
A case control study is done by Brophy J. et.al. to evaluate the association between risk of breast cancer and occupation. The study included 1005 cases confirmed with breast cancer and randomly selected 1146 controls. The result indicates the higher risk of breast cancer in the women who is working with potentially high exposures to carcinogens and endocrine disruptors (OR = 1.42, 95% CI:1.18-1.73), agriculture (OR = 1.36, 95% CI:1.01-1.82), food canning (OR = 2.35, 95% CI:1.00-5.53), bars-gambling (OR = 2.28, 95% CI:0.94-5.53), automotive plastics manufacturing (OR = 2.68, 95% CI:1.47-4.88), metalworking (OR = 1.73, 95% CI:1.02-2.92). Breast cancer risk was highest for food canning (OR = 5.70, 95% CI:1.03-31.5) and automotive plastics (OR = 4.76, 95% CI:1.58-14.4) in premenopausal women.[48]
2.4. Risk factors related to breast cancer
Table 1. Risk factors related to breast cancer. [60]
Risk factors Protective Predisposing controversial
Age
Gender
diabetes
Obesity and overweight
Family history
Genetic factors
22
Alcohol
Physical activity more
Duration of sleep
Age at menarche
Late age at menopause
Ovulatory menstrual cycle
Pregnancy characteristics
Full term pregnancy
Lesser breast-fed duration
Abortion
Hormonal contraceptive methods
Ovulation stimulating drugs
Postmenopausal hormone therapy
Air pollution
Radiation
Night work
Diet
23
3.
RESEARCH METHODOLGY
3.1. Type of research study
A case-control study3.2. Research Method
From August 2019 to February 2020 a hospital-based case-control study was conducted in the Hospital of Lithuanian University of Health Sciences Kauno Klinikos. The cases were defined as women diagnosed with breast cancer and the controls were women with no personal history of breast cancer. The cases were the women came for breast surgery in the Department of Breast Surgery, A total of 70 questionnaires were given to the breast cancer patients and 55 of the agreed to fill in the questionnaires (response rate – 78.5 %). The controls were the women came for screening under National Mammography Screening Program for Breast Cancer in Department of Radiology, Lithuanian University of Health SciencesKauno Klinikos. A total of around 161 questionnaires were given to the women agreed to participate in the Program and 115 questionnaires were collected (response rate – 71.42%). From 115 we excluded 18 questionnaires because only 1-2 pages were filled by the respondents so in total, we used 97 questionnaires (response rate – 60.2%).
In order to satisfy research objectives, quantitative and qualitative variable were used to achieve the goal of the research. A questionnaire was prepared with all information according to the requirements of objectives and the goal of research.
3.3. Research Instrument
A questionnaire was elaborated to evaluate women’s attitudes towards risk factors of breast cancer that are lifestyle, environmental, demographic and socio-economic factors. The questionnaire consisted of the following sections:
(1) demographic and socio-economic factors, (2) personal history of diseases
(3) height and weight
(4) family history on cancer,
(5) lifestyle factors (smoking, alcohol, physical activity, diet) (6) woman’s reproductive history
24 The attitudes of the respondents regarding risk factors were estimated using different scale ranging. The copy of the questionnaire is given at the Appendix No. 1
It was prepared by scientists of neuroscience institute, Lithuanian University of Health Sciences.
3.4. Statistical Data Analysis
The obtained data were coded and analysed with a statistical program IBM SPSS statistic - version 21. The data were analysed by using descriptive statistical methods for both qualitative and quantitative variables.
All women were grouped into 2 categories defined by: smoking (ever smoker, never smoker), alcohol (ever user, never user), dietary habits such as breakfast, coffee drinking and use of supplements ( yes, no), use of vegetables in summer and winter (> 3times , ≤ 3 times), salty food (like, dislike), supplement salt (never, When you lack salt/almost always without even tasting), fatty food (very often/often, rarely/not eat) and dietary items such as white bread, dark bread, french bread, pasta, rice, milk, sour cream, butter on bread, margarine on bread, curd/curd cheese, fermented cheese, eggs, beef/veal, pork, chicken, smoked meat(ham/sausages/bacon), Fish Salted (e.g. herring, salmon, etc.), Fish Fried or cooked, Carrots, Cabbage, Tomatoes, Sweet pepper (paprika), Garlic, Onions (roots), Pickled cabbage, Citrus fruits, Other fruits, Sweets, Black tea, Green tea, Other tea (herbal, etc.) (< 1-4 times /week, >5-6 times/week).
Women were grouped into 2 categories identified by exercise, leisure as walk and bicycle (never/rarely and sometimes/often/always), walking (>30 min, ≤30 min) and household work (>60 min, ≤60 min).
Women were grouped in 2 categories defined by dust, chemicals, other harmful factors at work, shift work, night shift work (yes, no), stress at work (never/rare, sometimes/often/always).
Socio-economic factors, living place (city, town/village), education (specialized secondary or lower, some university or higher), income (≤555, > 555) were grouped in 2 categories for all women. Marital status (single, married/ living unmarried, divorced/widow) was grouped in 3 categories for all women.
Multivariate unconditional logistic regression models were applied to estimate the association between breast cancer risk and lifestyle, environmental and socioeconomic factors in calculating the odds ratio (ORs) and their 95% confidence intervals (CIs). Models included the main risk factors of breast
25 cancer: age (a) and age, education (specialized secondary or lower, some university or higher) and alcohol (ever users and non-users) or BMI (b).
3.5. Research Ethics
All cases and controls of this study were signed a consent form and received information about the purpose of the study as well as the guarantee of confidentiality in the preamble of the questionnaire. All gathered information was kept in confidentiality and generalized so to prevent any identification of research participants. The study protocol was approved by the Bioethics Centre of Lithuanian University of Health Sciences (BEC-VS(M)-76). The copy of ethical approval is given at the Appendix No.2
26
4. RESULT
4.1. Characteristics of a study group
The cases and controls were similar in respect to age, BMI and education, however the cases more oftenly live in the city and family history of breast cancer in the first line of relatives was more prevalent among the cases. (Table 4.1.1.)
Table 4.1.1. Characteristics of cases and control
Variable Cases (n=55) Controls (n=97) P value for difference Age (years)(mean, SD) 58.96 (12.52) 58.89 (5.52) 0.96 Age (n, %)
Body Mass index (mean, SD) 26.85(6.55) 28.04(4.94) 0.21
Living place (n, %)
Town/village 16(29.1) 43(46.7) 0.04
City 39(70.9) 49(53.3)
Education (n, %)
Elementary/incomplete secondary/ Secondary / special secondary
35(66) 54(60.7)
University / incomplete university 18(34) 35(39.3) 0.52
Family history on breast cancer (mother) (n, %)
No 49(89.1) 94(97) 0.04
Yes 6(10.9) 2(2.1)
Family history on breast cancer (grandmother) (n, %)
27
No 53(96.4) 95(99) 0.30
Yes 2(3.6) 1(1)
4.2. The associations of lifestyle factors with risk of breast cancer
The majority of women in the study group were non-smokers. After adjustment for age, both smoking and use of alcohol were not related to risk of breast cancer (Table 4.2.1.). Although both ORs were higher than 1, they were not statistically significant. After adjustment for age, education and alcohol OR for association of smoking with breast cancer risk remained the same. There was no change in OR for breast cancer risk and alcohol use after adjusting for age, education and BMI.
Table 4.2.1 shows the associations between breast cancer risk and smoking as well as use of alcohol.
Variable Cases n (%) Controls n (%) OR (95% CI)a OR (95% CI)b Smoking Ever smokers 9(16.4) 27(29) 1 1 Non smokers 46(83.6) 66(71) 2.21(0.93-5.27) 2.12(0.85-5.31) Alcohol Ever users 26(52) 50(60.2) 1 1 Non users 24(48) 33(39.8) 1.41(0.68-2.92) 1.25(0.59-2.64)
ORa=adjusted for age
ORb for smoking= adjusted for age, education and alcohol ORb for alcohol= adjusted for age, education and BMI
Exercise, leisure as walk and bicycle, walking and household work was not related to breast cancer in both models: the first model was adjusted for age and second model was adjusted for age, education and alcohol. (Table 4.2.2.)
28 Table 4.2.2. Odds ratios (OR) and 95% confidence intervals (CI) for the association of physical activity with breast cancer
Variable Cases n (%) Controls n (%) OR (95% CI)a OR (95% CI)b Exercise Never/rarely 21(43.8) 46(55.4) 1 1 Sometimes/often/always 27(56.3) 37(44.6) 0.65(0.31-1.33) 0.74(0.34-1.59) Leisure, walk Never/rarely 39(82.3) 67(77.9) 1 1 Sometimes/often/always 9(18.8) 19(22.1) 1.23(0.50-2.99) 1.20(0.50-3.36) Leisure, bicycle Never/rarely 14(35) 36(44.4) 1 1 Sometimes/often/always 26(65) 45(55.6) 0.69(0.31-1.51) 0.72(0.31-1.66) Walking (min) >30 14(42.4) 28(45.9) 1 1 <=30 19(57.6) 33(54.1) 0.93(0.39-2.22) 1.09(0.42-2.85)
Household work (min)
>60 21(53.8) 31(43.1) 1 1
<=60 18(46.2) 41(56.9) 1.47(0.67-3.25) 1.68(0.72-3.91)
ORa=adjusted for age
ORb=adjusted for age, education and alcohol
We found that eating breakfast, use of salty food, supplement salt, fatty foods and eating vegetables in winter and summer were not associated to breast cancer risk after adjustment for age (Table 4.2.3.). Similar findings were obtained after adjustment for age, education, and alcohol. Whereas nonusers of the supplement had a higher risk of breast cancer (OR 2.23, 95% CI:1.09-4.58) in the first
29 model which was adjusted for age, however relationship became insignificant after further adjustment for age, education, and alcohol.
Table 4.2.3. Odds ratios (OR) and 95% confidence intervals (CI) for the association of dietary habits with breast cancer
Variable Cases n (%) Controls n (%) OR (95% CI)a OR (95% CI)b Breakfast Yes 43(82.7) 72(78.3) 1 1 No 9(17.3) 20(21.7) 0.70(0.28-1.72) 0.65(0.24-1.74) Salty foods Like 16(30.8) 31(33.7) 1 1 Dislike 36(69.2) 61(66.3) 1.17(0.56-2.43) 0.94(0.43-2.04) Supplement salt Never 17(32.1) 34(37) 1 1
When you lack salt/almost always without even tasting 36(67.9) 58(63) 1.19(0.58-2.45) 1.18(0.54-02.56) Fatty foods Very often/often 12(22.6) 17(18.5) 1 1 Rarely/not eat 41(77.4) 75(81.5) 0.77(0.34-1.78) 0.95(0.38-2.39) Vegetable summer >3 times 38(86.4) 64(86.5) 1 1 <=3 times 6(13.6) 10(13.5) 1.00(0.34-3.00) 0.98(0.28-3.40)
30 Vegetable winter >3 times 17(43.5) 34(51.5) 1 1 <=3 times 23(57.5) 33(48.5) 0.72(0.33-1.59) 0.69(0.29-1.60) Supplements Yes 28(53.8) 65(72.2) 1 1 No 24(46.2) 25(27.8) 2.23(1.09-4.58) 1.85(0.86-3.98)
ORa=adjusted for age
ORb=adjusted for age, education and alcohol
I didn’t find an association between breast cancer and consumption of white bread, dark bread, French bread, pasta and rice in both models (Table 4.2.4.). The first model was adjusted for age and second model was adjusted for age, education and alcohol.
Table 4.2.4. Odds ratios (OR) and 95% confidence intervals (CI) for the association of bread, pasta and rice with breast cancer
Variable Cases n (%)
Controls n (%) OR (95% CI)a OR (95% CI)b
White bread <1-4 times/ week 31(75.6) 49(77.8) 1 1 >5-6 times/ week 10(24.4) 14(22.2) 1.21(0.47-3.12) 1.19(0.44-3.20) Dark bread <1-4 times/ week 29(56.9) 37(49.3) 1 1 >5-6 times/ week 22(43.1) 38(50.7) 0.73(0.35-1.54) 0.67(0.30-1.48) French bread <1-4 times/ week 35(85.4) 56(88.9) 1 1 >5-6 times/ week 6(14.6) 7(11.1) 1.54(0.47-5.06) 1.22(0.34-4.31)
31 Pasta <1-4 times/ week 46(93.9) 65(97%) 1 1 >5-6 times/ week 3(6.1) 2(3) 2.11(0.34-13.16) 1.76(0.28-11.19) Rice <1-4 times/ week 48(96) 70(97.2) 1 1 >5-6 times/ week 2(4) 2(2.8) 1.46(0.20-10.79) 1.08(0.14-8.35) ORa=adjusted for age
ORb=adjusted for age, education and alcohol
I found that dairy products like milk, butter on bread, margarine on bread, fermented cheese, and eggs after adjustment for age were found a statistically non-significant to Breast cancer and similar results were found after adjustment for age, education, and alcohol (Table 4.2.5.)
Significant differences were observed between cases and controls for sour cream and curd/curd cheese (Table 4.2.5.). Multivariate logistic regression was performed for both the variables to analyse risk factors for breast cancer. Both factors were significantly related to increased breast cancer risk: for breast cancer and sour cream and curd/curd cheese, the ORs adjusted for age were 2.93(95% CI: 1.15-7.43) and 2.86(95% CI: 1.02-8.05), respectively; after further adjustment for alcohol and education the ORs were: 3.49(95% CI: 1.30-9.42) and 3.87(95% CI: 1.18-12.68), respectively.
Table 4.2.5. Odds ratios (OR) and 95% confidence intervals (CI) for the association of dairy products with breast cancer
Variable Cases n (%) Controls n (%) OR (95% CI)a OR (95% CI)b Milk <1-4 times/ week 34(73.9) 54(83.1) 1 1 >5-6 times/ week 12(26.1) 11(16.9) 1.94(0.74-5.06) 2.09(0.74-5.93) Sour cream <1-4 times/ week 35(70) 61(87.1) 1 1 >5-6 times/ week 15(30) 9(12.9) 2.93(1.15-7.43) 3.49(1.30-9.42)
32 Butter on bread <1-4 times/ week 34(66.7) 42(63.6) 1 1 >5-6 times/ week 17(33.3) 24(36.4) 0.86(0.39-1.88) 1.03(0.45-2.37) Margarine on bread <1-4 times/ week 29(87.9) 45(95.7) 1 1 >5-6 times/ week 4(12.1) 2(4.3) 3.09(0.53-17.98) 3.26(0.50-21.07) Curd/curd cheese <1-4 times/ week 39(76.5) 63(88.7) 1 1 >5-6 times/ week 12(23.5) 8(11.3) 2.86(1.02-8.05) 3.87(1.18-12.68) Fermented cheese <1-4 times/ week 44(91.7) 59(88.1) 1 1 >5-6 times/ week 4(8.3) 8(11.9) 0.72(0.20-2.60) 0.57(0.15-2.14) Eggs <1-4 times/ week 49(94.2) 63(84) 1 1 >5-6 times/ week 3(5.8) 12(16) 0.32(0.09-1.20) 0.38(0.10-1.48)
ORa=adjusted for age
ORb=adjusted for age, education and alcohol
After adjustment for age, consumption of beef/veal, pork, chicken, smoked meat(ham/sausages/bacon) were found statistically non-significant associated with Breast cancer risk and a similar pattern was observed after adjustment for age, education and alcohol (Table 4.2.6.).
33 Table 4.2.6. Odds ratios (OR) and 95% confidence intervals (CI) for the association of meat and its products with breast cancer
ORa=adjusted for age
ORb=adjusted for age, education and alcohol
After adjustment for age, consumption of fish salted (e.g. Herring, salmon etc.) and Fish fried or cooked, was not significantly associated with Breast cancer risk (Table 4.2.7.). Similar findings were determined after adjustment for age, education and alcohol.
Variable Cases n (%) Controls n (%) OR (95% CI)a OR (95% CI)b Beef/Veal <1-4 times/ week 41(97.6) 53(94.6) 1 1 >5-6 times/ week 1(2.4) 3(5.4) 0.43(0.04-4.30) 0.38(0.03-4.79) Pork <1-4 times/ week 42(89.4) 66(90.4) 1 1 >5-6 times/ week 5(10.6) 7(9.6) 1.13(0.33-3.81) 0.93(0.26-3.30) Chicken <1-4 times/ week 43(86) 67(91.8) 1 1 >5-6 times/ week 7(14) 6(8.2) 2.00(0.60-6.67) 2.14(0.57-8.01) Smoked meat (ham/sausages/bacon) <1-4 times/ week 42(87.5) 61(91) 1 1 >5-6 times/ week 6(12.5) 6(9) 1.46(0.44-4.84) 1.72(0.46-6.36)
34 Table 4.2.7. Odds ratios (OR) and 95% confidence intervals (CI) for the association of fish habits with breast cancer
ORa=adjusted for age
ORb=adjusted for age, education and alcohol
After adjustment for age, consumption of Carrots, cabbage, tomato, onion >5-6 times in a day was found insignificant to Breast cancer risk and similar pattern was observed after adjustment for age, education and alcohol although the consumption of these vegetables had higher OR (Table 4.2.8.). Consumption of sweet pepper(paprika), garlic, pickled cabbage, citrus fruits, other fruits, Sweets >5-6 times a day after adjustment for age was insignificant for Breast cancer and similar observation was found when adjusted for age, education and alcohol.
Table 4.2.8. Odds ratios (OR) and 95% confidence intervals (CI) for the association of vegetables and fruits with breast cancer.
Variable Cases n (%) Controls n (%) OR (95% CI)a OR (95% CI)b Carrots <1-4 times/ week 41(80.4) 64(83.1) 1 1 >5-6 times/ week 10(19.6) 13(16.9) 1.25(0.50-3.13) 1.38(0.52-3.65) Variable Cases n (%) Controls n (%) OR (95% CI)a OR (95% CI)b
Fish Salted (eg herring, salmon, etc.)
<1-4 times/ week 48(98) 70(98.6) 1 1
>5-6 times/ week 1(2) 1(1.4) 1.45(0.90-23.80) 1.37(0.08-23.83)
Fish Fried or cooked
<1-4 times/ week 44(97.8) 70(93.3) 1 1
35 Cabbage <1-4 times/ week 39(78) 68(86.1) 1 1 >5-6 times/ week 11(22) 11(13.9) 1.76(0.70-4.45) 1.37(0.51-3.64) Tomatoes <1-4 times/ week 20(39.2) 38(50) 1 1 >5-6 times/ week 31(60.8) 38(50) 1.55(0.75-3.18) 1.87(0.85-4.11) Sweet pepper (paprika) <1-4 times/ week 39(90.7) 56(82.4) 1 1 >5-6 times/ week 4(9.3) 12(17.6) 0.48(0.14-1.60) 0.52(0.15-1.82) Garlic <1-4 times/ week 40(78.4) 60(81.1) 1 1 >5-6 times/ week 11(21.6) 14(18.9) 1.19(0.49-2.91) 1.17(0.44-3.14) Onions (roots) <1-4 times/ week 31(66) 55(74.3) 1 1 >5-6 times/ week 16(34) 19(25.7) 1.53(0.68-3.44) 1.44(0.60-3.43) Pickled cabbage <1-4 times/ week 42(79.2) 64(82.1) 1 1 >5-6 times/ week 11(20.8) 14(17.9) 1.20(0.49-2.89) 1.17(0.45-3.04) Citrus fruits <1-4 times/ week 43(89.6) 61(80.3) 1 1 >5-6 times/ week 5(10.4) 15(19.7) 0.47(0.16-1.39) 0.59(0.19-1.86) Other fruits <1-4 times/ week 34(69.4) 53(72.6) 1 1
36 >5-6 times/ week 15(30.6) 20(27.4) 1.17(0.53-2.59) 1.24(0.53-2.95)
Sweets
<1-4 times/ week 43(89.6) 66(91.7) 1 1
>5-6 times/ week 5(10.4) 6(8.3) 1.23(035-4.33) 1.03(0.25-4.18)
ORa=adjusted for age
ORb=adjusted for age, education and alcohol
Consumption of black tea, green tea, other tea (herbal tea), found non-significant to breast cancer after adjustment for age (Table 4.2.9.). We found a similar relation after adjustment for age, education and alcohol. People who do not drink ground bean coffee had significantly higher risk of breast cancer compared to coffee drinkers (OR 3.49(95% CI:1.50-8.15).
Table 4.2.9. Odds ratios (OR) and 95% confidence intervals (CI) for the association of dietary habits with breast cancer.
Variable Cases n (%) Controls n (%) OR (95% CI)a OR (95% CI)b Black tea <1-4 times/ week 36(81.8) 52(82.5) 1 1 >5-6 times/ week 8(18.2) 11(17.5) 1.05(0.38-2.87) 1.11(0.38-3.23) Green tea <1-4 times/ week 32(68.1) 43(68.3) 1 1 >5-6 times/ week 15(31.9) 20(31.7) 1.01(0.45-2.27) 1.02(0.43-2.46)
Other tea (herbal, etc.)
<1-4 times/ week 31(67.4) 45(68.2) 1 1
>5-6 times/ week 15(32.6) 21(31.8) 1.03(0.46-2.31) 1.21(0.51-2.86)
37
Yes 34(64.4) 79(85.9) 1 1
No 18(34.6) 13(14.1) 3.49(1.50-8.15) 3.68(1.46-9.24)
ORa=adjusted for age
ORb=adjusted for age, education and alcohol
4.3. The association of environmental factors with risk of breast cancer
After adjustment for age in the first model and age, education and alcohol in the second model, we didn’t find an association between breast cancer and dust, chemicals, other harmful factors and stress at work (Table 4.3.1.). There was no association between breast cancer risk and shift work as well as night shift work in first model that is adjusted for age and after adjustment for age, education and alcohol similar pattern was observed.
Table 4.3.1. Odds ratios (OR) and 95% confidence intervals (CI) for the association of environmental factors with breast cancer.
Variable Cases n (%) Controls n (%) OR (95% CI)a OR (95% CI)b Dust Yes 10(37) 16(35.6) 1 1 No 17(63) 29(64.4) 0.94(0.35-2.58) 0.86(0.28-2.60) Chemicals Yes 10(37) 26(51) 1 1 No 17(63) 25(49) 1.70(0.65-4.46) 2.38(0.80-7.04) Others Yes 7(29.2) 13(34.2) 1 1 No 17(70.8) 25(65.8) 1.23(0.40-3.78) 1.13(0.28-4.51) Stress
38 Never/rare 13(28.3) 20(23.8) 1 1 Sometimes/often/always 33(71.7) 64(76.2) 0.77(0.34-1.76) 0.93(0.38-2.30) Shift work Yes 11(23.4) 18(21.4) 1 1 No 36(76.6) 66(78.6) 0.79(0.33-1.90) 0.96(0.33-2.83) Night shift Yes 11(23.4) 20(23.8) 1 1 No 36(76.6) 64(76.2) 0.91(0.38-2.15) 1.96(0.65-5.93)
ORa=adjusted for age
ORb=adjusted for age, education and alcohol
4.4. The association of socio-economic factors with breast cancer
Socio economic factors: income, marital status was founded insignificant to breast cancer risk after adjustment for age and similar pattern was observed after adjustment for age, education and alcohol (Table 4.4.1.). We found that people living in the village/town has lower risk when compared to people living in a city in both models adjusted for age and adjusted for age, education and alcohol (OR 0.47 95% CI:0.23-0.95 and OR 0.42 95% CI:0.19-0.92 respectively). There was no association between education and breast cancer risk after adjustment for age and age, alcohol and BMI.
Table 4.4.1. Odds ratios (OR) and 95% confidence intervals (CI) for the association of Socio-economics factors with breast cancer
Variable Cases n (%) Controls n (%) OR (95% CI)a OR (95%)b Living place (n, %) City 39(70.9) 49(53.3) 1 1 Town/village 16(29.1) 43(46.7) 0.47(0.23-0.95) 0.42(0.19-0.92)
39 Education (n, %)
Specialized secondary or lower
35(66) 54(60.7) 1 1
Some university or higher 18(34) 35(39.3) 0.79(0.39-1.61) 1.33(0.62-2.87)
Income (EUR) (n, %) ≤555 32(59.3) 48(53.9) 1 1 >555 22(40.7) 41(46.1) 0.81(0.39-1.70) 1.06(0.44-2.51) Marital status (n, %) Single 4(7.4) 3(3.2) 1 1 Married/living unmarried 28(51.9) 64(68.8) 1.44(0.28-7.33) 1.53(0.27-8.52) Divorced/widow 22(40.7) 26(28) 0.47(0.21-1.02) 0.49(0.21-1.16)
ORa=adjusted for age
ORb=adjusted for age, education and alcohol
40
Discussion
Breast cancers develop in a complicated, continuous way. The development has multiple factors, multiple steps and environment-gene interactions also play an important role in origin. Breast cancer has been studied widely and many researchers have conducted much research in the field. In-depth analysis of factors like lifestyle, and healthcare factors, geographical features have to be analysed so that risk factors for breast cancer can be managed through which preventive strategies could be formulated [58].
We carried out a hospital-based case-control study involving 152 women. We found smoking and alcohol is non-significant to breast cancer, however Strumylaite L. [11] found alcohol is significant to breast cancer and Dale M. [12] found breast cancer is predominantly associated with alcohol, smoking. On the other hand, Prescott J. found smoking in not associated with breast cancer risk in younger women. [49].
We found no association between physical activity and breast cancer, whereas Dale M. [12] concluded that physical activity is predominantly associated with breast cancer.
We found non-significant association between breakfast, salty food, supplement salt, fatty food, use of supplements and breast cancer risk, however Binukumar B. [57] concluded that increased consumption of total fat and saturated fat were found to be positively associated with the development of breast cancer and Khusi L. [50] also found use of vitamin A, C, E is associated with decreased breast cancer risk. We didn’t find other research on breast cancer risk and breakfast, salty food and supplement salt.
We found non-significant association between breast cancer and use of vegetables in summer and winter, carrot, cabbage, tomatoes, sweet pepper, garlic, onion, pickled cabbage, citrus fruits, sweets whereas Castello A. [17] also found no association for prudent pattern diet with breast cancer, but Mediterranean dietary pattern is associated with lower breast cancer risk and authors concluded that a diet rich in fruits, vegetables, legumes associated for preventing all types of breast cancer.
We found that non-drinker of coffee has a higher risk of breast cancer as compare to coffee drinker And Ganmaa D. [51] done a cohort study and observed no association between caffeinated and decaffeinated coffee and tea consumption and risk of breast cancer however, we also found that black tea, green tea and other tea are not associated with breast cancer.
