PDF(Pubmed)
Abstract：
BACKGROUND: The consumption of processed meats (PMs) and red meats are linked to the likelihood of developing colorectal cancer. Various theories have been proposed to explain this connection, focusing on nitrosyl-heme and heme iron intake. We hypothesized that differences in nitrosyl-heme and heme iron intakes will be associated with various sociodemographic and lifestyle factors.
METHODS: The study included 38,471 healthy volunteers (62% females) from five Spanish regions within the EPIC-Spain cohort. High-Performance Liquid Chromatography (HPLC) determined nitrosyl-heme and heme iron levels in the 39 most consumed PMs. Food intake was assessed using validated questionnaires in interviews. Nitrosyl-heme and heme iron intakes, adjusted for sex, age, body mass index (BMI), center, and energy intake, were expressed as geometric means due to their skewed distribution. Variance analysis identified foods explaining the variability of nitrosyl-heme and heme iron intakes.
RESULTS: The estimated intakes were 528.6 µg/day for nitrosyl-heme and 1676.2 µg/day for heme iron. Significant differences in nitrosyl-heme intake were found by sex, center, energy, and education level. Heme iron intake varied significantly by sex, center, energy, and smoking status. \"Jamón serrano\" and \"jamón cocido/jamón de York\" had the highest intake values, while \"morcilla asturiana\" and \"sangrecilla\" were key sources of nitrosyl-heme and heme iron.
CONCLUSIONS: This is the first study to estimate levels of nitrosyl-heme intake directly in PMs for a large sample, revealing variations based on sex, BMI, smoking, and activity. Its data aids future exposure estimations in diverse populations.
METHODS: The study included 38,471 healthy volunteers (62% females) from five Spanish regions within the EPIC-Spain cohort. High-Performance Liquid Chromatography (HPLC) determined nitrosyl-heme and heme iron levels in the 39 most consumed PMs. Food intake was assessed using validated questionnaires in interviews. Nitrosyl-heme and heme iron intakes, adjusted for sex, age, body mass index (BMI), center, and energy intake, were expressed as geometric means due to their skewed distribution. Variance analysis identified foods explaining the variability of nitrosyl-heme and heme iron intakes.
RESULTS: The estimated intakes were 528.6 µg/day for nitrosyl-heme and 1676.2 µg/day for heme iron. Significant differences in nitrosyl-heme intake were found by sex, center, energy, and education level. Heme iron intake varied significantly by sex, center, energy, and smoking status. \"Jamón serrano\" and \"jamón cocido/jamón de York\" had the highest intake values, while \"morcilla asturiana\" and \"sangrecilla\" were key sources of nitrosyl-heme and heme iron.
CONCLUSIONS: This is the first study to estimate levels of nitrosyl-heme intake directly in PMs for a large sample, revealing variations based on sex, BMI, smoking, and activity. Its data aids future exposure estimations in diverse populations.
摘要：
背景：加工肉类（PM）和红肉的消费与发生结直肠癌的可能性有关。已经提出了各种理论来解释这种联系，重点是亚硝酰血红素和血红素铁的摄入量。我们假设亚硝酰血红素和血红素铁摄入量的差异将与各种社会人口统计学和生活方式因素有关。
方法：该研究纳入了EPIC-西班牙队列中来自五个西班牙地区的38,471名健康志愿者（62%为女性）。高效液相色谱法（HPLC）测定了39个消耗最多的PM中的亚硝酰血红素和血红素铁水平。在访谈中使用经过验证的问卷评估食物摄入量。亚硝基血红素和血红素铁摄入量，适应性，年龄,体重指数（BMI），中心,和能量摄入，由于它们的偏斜分布，它们表示为几何均值。方差分析确定了食物，解释了亚硝酰血红素和血红素铁摄入量的变异性。
结果：亚硝酰血红素的估计摄入量为528.6µg/天，血红素铁的估计摄入量为1676.2µg/天。亚硝酰血红素摄入量的显着差异按性别发现，中心,能源,和教育水平。血红素铁的摄入量因性别而异，中心,能源,和吸烟状况。“Jamónserrano”和“Jamóncocido/JamóndeYork”的进气值最高，而“morcillaasturiana”和“sangrecilla”是亚硝酰血红素和血红素铁的主要来源。
结论：这是第一项直接评估大样本PM中亚硝酰血红素摄入量的研究，揭示基于性别的变化，BMI,吸烟,和活动。其数据有助于未来不同人群的暴露估计。
方法：该研究纳入了EPIC-西班牙队列中来自五个西班牙地区的38,471名健康志愿者（62%为女性）。高效液相色谱法（HPLC）测定了39个消耗最多的PM中的亚硝酰血红素和血红素铁水平。在访谈中使用经过验证的问卷评估食物摄入量。亚硝基血红素和血红素铁摄入量，适应性，年龄,体重指数（BMI），中心,和能量摄入，由于它们的偏斜分布，它们表示为几何均值。方差分析确定了食物，解释了亚硝酰血红素和血红素铁摄入量的变异性。
结果：亚硝酰血红素的估计摄入量为528.6µg/天，血红素铁的估计摄入量为1676.2µg/天。亚硝酰血红素摄入量的显着差异按性别发现，中心,能源,和教育水平。血红素铁的摄入量因性别而异，中心,能源,和吸烟状况。“Jamónserrano”和“Jamóncocido/JamóndeYork”的进气值最高，而“morcillaasturiana”和“sangrecilla”是亚硝酰血红素和血红素铁的主要来源。
结论：这是第一项直接评估大样本PM中亚硝酰血红素摄入量的研究，揭示基于性别的变化，BMI,吸烟,和活动。其数据有助于未来不同人群的暴露估计。
