中文(繁體)
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
Cancer Epidemiology Biomarkers and Prevention 2008-Nov

Childbearing recency and modifiers of premenopausal breast cancer risk.

只有註冊用戶可以翻譯文章
登陸註冊
鏈接已保存到剪貼板
Neeraja B Peterson
Yifan Huang
Polly A Newcomb
Linda Titus-Ernstoff
Amy Trentham-Dietz
Gabriella Anic
Kathleen M Egan

關鍵詞

抽象

The purpose of this study was to examine the risk of premenopausal breast cancer for women in relation to childbearing recency and whether this association differs by breast-feeding history and/or the amount of weight gained during pregnancy. This analysis was based on data from a population-based case-control study composed of 1,706 incident cases of invasive breast cancer and 1,756 population controls from Wisconsin, New Hampshire, and Massachusetts. In a telephone interview conducted from 1996 to 2001, information was gathered on established breast cancer risk factors, as well as reproductive history, including amount of weight gained during the last full-term pregnancy and whether the child was breast-fed. Unconditional logistic regression was used to estimate odds ratios and Wald 95% confidence intervals for the risk of breast cancer. When compared with nulliparous women, women that had given birth within the past 5 years before breast cancer diagnosis in the cases or a comparable period in controls had a nonsignificant 35% increased risk of invasive breast cancer (odds ratio, 1.35; 95% confidence interval, 0.90-2.04), adjusting for age and known breast cancer risk factors (Ptrend = 0.14). We did not find a significant interaction with breast-feeding (Pinteraction = 0.30) or pregnancy weight gain (Pinteraction = 0.09).

加入我們的臉書專頁

科學支持的最完整的草藥數據庫

  • 支持55種語言
  • 科學支持的草藥療法
  • 通過圖像識別草藥
  • 交互式GPS地圖-在位置標記草藥(即將推出)
  • 閱讀與您的搜索相關的科學出版物
  • 通過藥效搜索藥草
  • 組織您的興趣並及時了解新聞研究,臨床試驗和專利

輸入症狀或疾病,並閱讀可能有用的草藥,輸入草藥並查看其所針對的疾病和症狀。
*所有信息均基於已發表的科學研究

Google Play badgeApp Store badge