Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
School of Public Health, University of Washington, Seattle, WA, USA.
J Nutr. 2022 Apr 1;152(4):1107-1117. doi: 10.1093/jn/nxac004.
We recently developed protein and carbohydrate intake biomarkers using metabolomics profiles in serum and urine, and used them to correct self-reported dietary data for measurement error. Biomarker-calibrated carbohydrate density was inversely associated with chronic disease risk, whereas protein density associations were mixed.
To elucidate and extend this earlier work through biomarker development for protein and carbohydrate components, including animal protein and fiber.
Prospective disease association analyses were undertaken in Women's Health Initiative (WHI) cohorts of postmenopausal US women, aged 50-79 y when enrolled at 40 US clinical centers. Biomarkers were developed using an embedded human feeding study (n = 153). Calibration equations for protein and carbohydrate components were developed using a WHI nutritional biomarker study (n = 436). Calibrated intakes were associated with chronic disease incidence in WHI cohorts (n = 81,954) over a 20-y (median) follow-up period, using HR regression methods.
Previously reported elevations in cardiovascular disease (CVD) with higher-protein diets tended to be explained by animal protein density. For example, for coronary heart disease a 20% increment in animal protein density had an HR of 1.20 (95% CI: 1.02, 1.42) relative to the HR for total protein density. In comparison, cancer and diabetes risk showed little association with animal protein density beyond that attributable to total protein density. Inverse carbohydrate density associations with total CVD were mostly attributable to fiber density, with a 20% increment HR factor of 0.89 (95% CI: 0.83, 0.94). Cancer risk showed little association with fiber density, whereas diabetes risk had a 20% increment HR of 0.93 (95% CI: 0.88, 0.98) relative to the HRs for total carbohydrate density.
In a population of postmenopausal US women, CVD risk was associated with high-animal-protein and low-fiber diets, cancer risk was associated with low-carbohydrate diets, and diabetes risk was associated with low-fiber/low-carbohydrate diets.
我们最近利用血清和尿液代谢组学图谱开发了蛋白质和碳水化合物摄入的生物标志物,并利用这些生物标志物来校正自我报告的饮食数据中的测量误差。生物标志物校正后的碳水化合物密度与慢性病风险呈负相关,而蛋白质密度的相关性则较为复杂。
通过开发蛋白质和碳水化合物成分(包括动物蛋白和纤维)的生物标志物,进一步阐明和扩展之前的工作。
采用前瞻性疾病关联分析方法,对美国绝经后女性的妇女健康倡议(WHI)队列进行研究,这些女性在 40 个美国临床中心入组时年龄为 50-79 岁。生物标志物的开发采用嵌入式人体喂养研究(n=153)。蛋白质和碳水化合物成分的校准方程是使用 WHI 营养生物标志物研究(n=436)开发的。在 20 年(中位数)随访期间,使用 HR 回归方法,将校准后的摄入量与 WHI 队列中慢性疾病的发病率进行了关联。
之前报告的高蛋白饮食与心血管疾病(CVD)升高之间的关系,往往可以用动物蛋白密度来解释。例如,对于冠心病,与总蛋白密度相比,动物蛋白密度增加 20%,其 HR 为 1.20(95%CI:1.02,1.42)。相比之下,动物蛋白密度与癌症和糖尿病风险之间的关联,除了与总蛋白密度有关之外,几乎没有关联。总心血管疾病的负相关碳水化合物密度主要归因于纤维密度,20%的增量 HR 因子为 0.89(95%CI:0.83,0.94)。癌症风险与纤维密度几乎没有关联,而糖尿病风险与总碳水化合物密度相比,其 HR 增加了 20%,为 0.93(95%CI:0.88,0.98)。
在一群绝经后美国女性中,CVD 风险与高动物蛋白和低纤维饮食有关,癌症风险与低碳水化合物饮食有关,糖尿病风险与低纤维/低碳水化合物饮食有关。