Background/Aim: Breast cancer is the most common type of cancer among women around the world and the leading cause of cancer-related death among women. The knowledge about modifiable risk factors, such as diet, can be an acceptable, cheap and non-pharmacological prevention tool. The aim of this study was to investigate the association between dietary fat, dietary fatty acids, fish intake, and breast cancer in women. Patients and Methods: A case-control study was designed. A total of 201 consecutive, newly diagnosed, polish female cancer patients (mean age: 58 years) and 201 one-to-one age-matched controls were enrolled. A standardised questionnaire assessing various socio-demographic, clinical, lifestyle, and dietary characteristics was applied via face-to-face interviews. Detailed dietary intake information was assessed using a validated Food Frequency Questionnaire. Odds ratios (OR) and 95% confidence intervals (95%CI) were obtained using multiple unconditional logistic regression models controlling for non-dietary and dietary potential confounders. Results: Consumption of polyunsaturated fats (PUFA) over 10% of total energy intake was associated with a significantly lower risk of breast cancer compared to low intake of PUFA (OR=0.4, 95%CI=0.19-0.85). Low (<0.2) omega-3/ omega-6 ratio (OR=2.04, 95%CI=0.996-4.17), fish consumption less than once every six months (OR=3.37, 95%CI=1.57-7.23) and being overweight (OR=2.07, 95%CI=1.3-3.3) were associated with increased risk of breast cancer. Residents of rural areas had a significantly higher risk compared to women from urban areas (OR=1.8, 95%CI=1.06-3.03). Conclusion: High intake of PUFA can decrease the risk of breast cancer, while the low omega-3/omega-6 ratio increases the risk. In addition, overweight state, eliminating fish from the diet and living in rural areas can also increase the risk of breast cancer.

Following the economic changes in Poland, increasing health discrepancies were observed during a period of 20 years, which may be partly attributable to the consequences of unemployment. To assess the association between unemployment, major cardiovascular risk factors and mental health. A cross-sectional study in which data were collected between 2009 and 2010 during preventive health examinations by an occupational medicine service in Gdansk, Poland. Data on blood pressure, resting heart rate, information about smoking habits, body mass index and history of use of mental health services were collected during these assessments. Multiple logistic regression was used during data analysis to adjust for age, gender, education and length of employment. Study participants comprised 3052 unemployed and 2059 employed individuals. After adjustment for age, gender, education and number of previous employments, the odds ratio (OR) for hypertension in relation to unemployment was 1.02 [95% confidence interval (95% CI) 0.84-1.23]. There was a statistically significant negative association between being overweight and unemployment (OR = 0.81, 95% CI: 0.66-0.99). Smoking was positively associated with unemployment after adjustment for age and sex (OR = 1.45, 95% CI: 1.25-1.67). There was a positive relationship between mental ill-health and unemployment among study participants (OR = 2.05, 95% CI: 0.91-4.65), but this was not statistically significant. The patterns of major cardiovascular risk factors differed between unemployed and employed individuals in Poland. Our observations suggest employment status is a predictor of specific disease risk profiles; consequently, specific preventive measures are needed in unemployed individuals.

The aim of this study was to determine the risk factors for breast cancer in the Polish population. In total, 201 Polish women newly diagnosed with breast cancer and 201 one-to-one age-matched healthy controls participated in this case-control study. Data on sociodemographic characteristics, reproductive and menstrual history, medical history, lifestyle factors, and anthropometric measurements were collected by the interviewers. Odds ratios and 95% confidence intervals were obtained using multivariate unconditional logistic regression models controlling for potential confounders. Significant relationships were observed between BMI, alcohol use initiation, breastfeeding, education, and place of residence. Obese women had a higher risk of breast cancer than women with a BMI < 30 (OR = 1.9; 95% CI: 1.16 to 3.04). Early alcohol use initiation (≤15 years) was associated with an almost two-fold higher risk of breast cancer (OR = 1.98, 95% CI: 1.06 to 3.69). Breastfeeding for less than 3 months (OR = 2.3, 95% CI: 1.52 to 3.5), receiving a basic and vocational education (OR = 2.5, 95% CI: 1.49 to 4.19), and living in a rural area (OR = 1.7, 95% CI: 1.05 to 2.9) increased the risk of breast cancer. Prevention activities for breast cancer are already needed in adolescents and young women. A much greater emphasis should also be placed on breast cancer prevention campaigns in rural areas in Poland.

While breast cancer is the most common cancer in women around the world, it is necessary to know the nutritional factors that can have both protective and negative effects on the risk of breast cancer. Unfortunately, the results of the research still do not give a definite answer to the question: which food products or food ingredients reduce, and which increase the risk of breast cancer. At a time when the main source of knowledge of health for the majority of society is the internet, myths about this disease are still being replicated. Only on the basis of clear scientific evidence can we build an effective prevention program that can save millions of women from breast cancer. In this review, we decided to present nutritional risk factors whose impact on the risk of breast cancer was examined, however, the results are not conclusive, like: fibre, milk products

The use of artificial intelligence (AI) in healthcare encompasses a wide range of new diagnostic and therapeutic possibilities. In recent years, the popularity of AI has significantly increased. The use of AI-based innovations in medicine is expected to continue growing. AI using multi-element and multi-modal databases can enable the discovery of previously unknown connections, the more precise forecasts, more effective treatment options, and better access to healthcare. It should be noted that there are many unknown and unregulated issues regarding safety, ethics, methodology, and the feasibility of its use within existing information technology infrastructure. Despite the potential of AI, some innovations have not yet significantly improved healthcare. This suggests that, despite the popularity of this technology, its development and implementation will take time.