Department of Biostatistics, University of Nebraska Medical Center, Omaha, NE, USA.
Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
J Nutr. 2022 Jul 6;152(7):1711-1720. doi: 10.1093/jn/nxac067.
The associations of red and processed meat with chronic disease risk remain to be clarified, in part because of measurement error in self-reported diet.
We sought to develop metabolomics-based biomarkers for red and processed meat, and to evaluate associations of biomarker-calibrated meat intake with chronic disease risk among postmenopausal women.
Study participants were women who were members of the Women's Health Initiative (WHI) study cohorts. These participants were postmenopausal women aged 50-79 y when enrolled during 1993-1998 at 40 US clinical centers with embedded human feeding and nutrition biomarker studies. Literature reports of metabolomics correlates of meat consumption were used to develop meat intake biomarkers from serum and 24-h urine metabolites in a 153-participant feeding study (2010-2014). Resulting biomarkers were used in a 450-participant biomarker study (2007-2009) to develop linear regression calibration equations that adjust FFQ intakes for random and systematic measurement error. Biomarker-calibrated meat intakes were associated with cardiovascular disease, cancer, and diabetes incidence among 81,954 WHI participants (1993-2020).
Biomarkers and calibration equations meeting prespecified criteria were developed for consumption of red meat and red plus processed meat combined, but not for processed meat consumption. Following control for nondietary confounding factors, hazard ratios were calculated for a 40% increment above the red meat median intake for coronary artery disease (HR: 1.10; 95% CI: 1.07, 1.14), heart failure (HR: 1.26; 95% CI: 1.20, 1.33), breast cancer (HR: 1.10; 95% CI: 1.07, 1.13) for, total invasive cancer (HR: 1.07; 95% CI: 1.05, 1.09), and diabetes (HR: 1.37; 95% CI: 1.34, 1.39). HRs for red plus processed meat intake were similar. HRs were close to the null, and mostly nonsignificant following additional control for dietary potential confounding factors, including calibrated total energy consumption.
A relatively high-meat dietary pattern is associated with somewhat higher chronic disease risks. These elevations appear to be largely attributable to the dietary pattern, rather than to consumption of red or processed meat per se.
红色肉类和加工肉类与慢性病风险的关联仍需阐明,部分原因是自我报告的饮食存在测量误差。
我们试图开发基于代谢组学的红色肉类和加工肉类生物标志物,并评估生物标志物校准的肉类摄入量与绝经后妇女慢性病风险之间的关联。
研究参与者为参加妇女健康倡议(WHI)研究队列的女性。这些参与者在 1993-1998 年期间,年龄在 50-79 岁,在美国 40 个临床中心入组,这些中心开展了嵌入式人体喂养和营养生物标志物研究。文献报道的肉类消费代谢组学相关性被用于在一项 153 名参与者喂养研究(2010-2014 年)中从血清和 24 小时尿液代谢物中开发肉类摄入量生物标志物。在一项 450 名参与者的生物标志物研究(2007-2009 年)中,使用这些生物标志物来开发线性回归校准方程,以调整 FFQ 摄入量的随机和系统测量误差。在 81954 名 WHI 参与者(1993-2020 年)中,使用生物标志物校准的肉类摄入量与心血管疾病、癌症和糖尿病的发病率相关。
针对红肉类和红加加工肉类的联合摄入,开发了符合预设标准的生物标志物和校准方程,但针对加工肉类的摄入则没有。在控制非饮食混杂因素后,计算出了冠状动脉疾病(HR:1.10;95%CI:1.07,1.14)、心力衰竭(HR:1.26;95%CI:1.20,1.33)、乳腺癌(HR:1.10;95%CI:1.07,1.13)、总侵袭性癌症(HR:1.07;95%CI:1.05,1.09)和糖尿病(HR:1.37;95%CI:1.34,1.39)的红肉类中位数摄入量增加 40%的风险比(HR)。在进一步控制饮食潜在混杂因素,包括校准后的总能量摄入后,HR 接近零,且大多数无统计学意义。
较高的肉类饮食模式与稍高的慢性病风险相关。这些升高似乎主要归因于饮食模式,而不是红色或加工肉类的摄入量本身。