To evaluate the relationship between body size, physical activity and risk of breast cancer, we conducted a case-control study with 669 cases and 682 population-based controls in Jiangsu Province of China. A structured questionnaire was used to elicit detailed information. All subjects completed an in-person interview. The body mass index (BMI) was calculated based on weights and heights. Unconditional logistic regression analysis was performed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) as measures of risk for breast cancer. Current height, weight and weight at around age 20 years were significantly positively correlated with risk of breast cancer. Obese women (current BMI > or = 25 kg/m2) were at significantly increased risk for developing breast cancer (adjusted OR= 1.35, 95%CI: 1.01-1.81), but, between BMI at around age 20 years and risk of breast cancer showed an inverse association (P for trend = 0.001). Women who had middle physical force work were at significantly lowered OR (0.62, 95%CI: 0.41-0.93) compared with women of headwork. Using women who standing or ambulation per day less than one hour as the reference, women who standing or ambulation more than one hour had a decreased risk of breast cancer. Using women who slept less than 5 hours per day as the reference, the women who slept 5-8 hours were at significantly decreased risk of breast cancer. Women who had habit of recreational physical activity were at significantly decreased risk (adjusted OR= 0.68, 95%CI: 0.53-0.88), with an inverse association between the exercise times per week and risk of breast cancer (P for trend = 0.025). These findings support that breast cancer risk is associated with body size, and that moderate occupational and recreational physical activity has protective effects on breast cancer.

Download full-text PDF

Source

Publication Analysis

Top Keywords

breast cancer
44
risk breast
32
physical activity
16
body size
12
decreased risk
12
risk
11
breast
11
cancer
11
size physical
8
activity risk
8

Similar Publications

In this paper, the pH-sensitive targeting functional material NGR-poly(2-ethyl-2-oxazoline)-cholesteryl methyl carbonate (NGR-PEtOz-CHMC, NPC) modified quercetin (QUE) liposomes (NPC-QUE-L) was constructed. The structure of NPC was confirmed by infrared spectroscopy (IR) and nuclear magnetic resonance hydrogen spectrum (H-NMR). Pharmacokinetic results showed that the accumulation of QUE in plasma of the NPC-QUE-L group was 1.

View Article and Find Full Text PDF

Aim: Dynamic cancer control is a current health system priority, yet methods for achieving it are lacking. This study aims to review the application of system dynamics modeling (SDM) on cancer control and evaluate the research quality.

Methods: Articles were searched in PubMed, Web of Science, and Scopus from the inception of the study to November 15th, 2023.

View Article and Find Full Text PDF

Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a deep learning-based algorithm (BBMIL) to predict classical biomarkers, immunotherapy-associated gene signatures, and prognosis-associated subtypes directly from hematoxylin and eosin stained histopathology images. BBMIL showed the best performance among comparative algorithms on the prediction of classical biomarkers, immunotherapy related gene signatures, and subtypes.

View Article and Find Full Text PDF

Sarcopenia as a Prognostic Factor and Multimodal Interventions in Breast Cancer.

Int J Gen Med

December 2024

Department of Thyroid and Breast Surgery, Quzhou People's Hospital, Quzhou, 324000, People's Republic of China.

Objective: This study aims to demonstrate the impact of sarcopenia on the prognosis of early breast cancer and its role in early multimodal intervention.

Methods: The clinical data of patients (n=285) subjected to chemotherapy for early-stage breast cancer diagnosed pathologically between January 1, 2016, and December 31, 2020, in our hospital were retrospectively analyzed. Accordingly, the recruited subjects were divided into sarcopenia (n=85) and non-sarcopenia (n=200) groups according to CT diagnosis correlating with single-factor and multifactorial logistic regression analyses.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!