The True Face of the Pyramid; Physical Activity Level and Cardiovascular Risk in Patients With Breast Cancer

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide. Many risk factors are thought to be important in the development of CVD; however, some risk factors can be controlled. Regular physical activity (PA) is recommended for the entire population for the primary prevention of CVD. PA and physical health are also believed to reduce other CVD risk factors such as body mass index, blood pressure and stress. Although oncological outcome is the most important factor for breast cancer survivors, CVD has emerged as an important cause of death among them. In particular, CVD mortality is known to increase 7 years after breast cancer diagnosis, and death due to CVD is more common in older patients than death from cancer. Higher levels of physical activity compared to low levels measured prior to breast cancer diagnosis were associated with statistically significantly lower all-cause mortality among women diagnosed with breast cancer. For breast cancer survivors, increasing PA during and after treatment has been reported to be safe and effective in improving cancer survival, alleviating cancer-related symptoms and improving quality of life. However, there is a lack of evidence regarding the effect of PA on cardiovascular outcomes in long-term breast cancer survivors.

This study aims to investigate the determination of optimal walking or moderate to vigorous PA in patients categorised according to their cardiovascular health status. We also aimed to evaluate the association of different levels of physical activity with cardiovascular risk in different age groups after breast cancer.

Demographic information: Participants' age, diagnosis, medical history (time since surgery (months), type of lymphedema, treatments received for lymphedema, radiotherapy (number of days), chemotherapy (number of cycles), type of surgery (lumpectomy, segmental mastectomy, modified radical mastectomy, radical mastectomy), occupation, body weight (kg), height (cm), body mass index (kg/m2), lean muscle mass and fat percentage will be assessed as part of anthropometric evaluation (Tanita Inner Scan BC 532, Tokyo, Japan). Waist and hip circumference measurements will be recorded. BMI, dominant and affected side, medical history, family history, lifestyle characteristics (smoking, exercise habits, alcohol intake), monthly income level will be recorded.

Assessment of Physical Activity Level: Physical activity level will be assessed with a triaxial accelerometer. SenseWear Armband (SWA) (Armband Model MF-SW, BodyMedia, Pittsburgh, USA) metabolic holter device with triaxial accelerometer sensors that detect skin temperature, galvanic skin response, heat flow, movement and position will be used to objectively measure activity level and energy consumption. After the configuration of the device is made, it will be given to the individuals to be worn for 7 consecutive days or more. Individuals will be asked to remove the device only when taking a shower and in situations requiring contact with water, such as swimming, and then dry the arm and reinsert the device. The device will be worn as described in the manual, with the left arm over the triceps muscle, making sure that the sensors are in contact with the person's arm, and adjusting the band tightness according to the person's arm. Individuals will be asked to continue their daily life activities as usual while wearing the device. The data obtained from the device will be recorded together with the individuals' date of birth, height, body weight, gender, dominant hand and smoking status.

Total energy expenditure, active energy expenditure, average number of steps, average MET, average physical activity index (PAL), average distance, duration of physical activity, duration of mild physical activity (<1.5 MET), duration of moderate physical activity (3-6 MET), duration of vigorous physical activity (6-9 MET), duration of very vigorous physical activity (>9 MET), duration of lying down, average sleep time and sleep efficiency data will be obtained from the device.