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Article(id=1216517516730483598, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1216517514570417012, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20250422005, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1745251200000, receivedDateStr=2025-04-22, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1767969977790, onlineDateStr=2026-01-09, pubDate=1755187200000, pubDateStr=2025-08-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1767969977790, onlineIssueDateStr=2026-01-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1767969977790, creator=13701087609, updateTime=1767969977790, updator=13701087609, issue=Issue{id=1216517514570417012, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='15', pageStart='1', pageEnd='322', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1767969977276, creator=13701087609, updateTime=1768211590858, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1217530915467743720, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1216517514570417012, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1217530915467743721, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1216517514570417012, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=157, endPage=166, ext={EN=ArticleExt(id=1216517518223655852, articleId=1216517516730483598, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Monitoring and health risk assessment of 26 kinds of metal multi-elements in cereals in Handan City, columnId=1151923892655846010, journalTitle=Journal of Food Safety & Quality, columnName=Special Topic: Food Safety Risk Assessment and Risk Monitoring, runingTitle=null, highlight=null, articleAbstract=

Objective To investigate the distribution of 26 kinds of metal elements (Pb, Cd, Hg, As, Cr, Al, Mn, Cu, Ba, V, Se, Sb, Ni, Sn, Li, B, Zn, K, Na, Ca, Mg, Fe, Sr, Mo, Co, Rb) and assess the dietary risk with cereals in Handan City. Methods A total of 51 cereal samples (wheat and maize) were analyzed for 26 kinds of metal elements using inductively coupled plasma mass spectrometry (ICP-MS). Statistical analysis was performed on the detection results, and nutritional and exposure risk assessments were conducted for macro- and trace elements using the individual pollution index, target hazard quotient, carcinogenic risk, and estimated daily intake. Results The method demonstrated good linearity, high accuracy, and sensitivity. Among the 26 kinds of metal elements, 24 kinds of metal elements were detected in the cereal samples, except for Hg and Li. Principal component analysis and correlation analysis revealed interspecies differences between wheat and maize, as well as distinct correlations among different elements. The contamination levels of 5 kinds of heavy metals (Pb, Cd, Hg, As, Cr) were within safe limits. The target hazard index of 19 kinds of metal elements and the carcinogenic risk index for Pb were significantly below threshold levels, indicating no health risks, but the carcinogenic risk assessment for As suggested potential health risks. Nutritional assessment showed that the cereals were rich in K and Mg, but low in Na. However, Cr exposure reached nearly 300% of the adequate daily intake, indicating a significant health concern. Conclusion The established method is effective for multi-element analysis in cereals. This research findings provide updated dietary intake assessment of multi-elements of Handan adult consumers. The dietary assessment indicates that intake of cereals in Handan City poses no significant health risks, but particular attention should be paid to Cr and As contamination.

, correspAuthors=Wei-Hao LI, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Ying-Ying LIAN, Yan-Fei FANG, Yong-Hong HAN, Hui-Min YAN, Yan ZHAO, Lu ZHANG, Wei-Hao LI), CN=ArticleExt(id=1216517519351923697, articleId=1216517516730483598, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=邯郸市谷物制品中26种金属多元素监测与健康风险评估, columnId=1151923892995109553, journalTitle=食品安全质量检测学报, columnName=专题：食品安全风险评估与风险监测, runingTitle=null, highlight=null, articleAbstract=目的 了解邯郸市售谷物制品中26种金属多元素(Pb、Cd、Hg、As、Cr、Al、Mn、Cu、Ba、V、Se、Sb、Ni、Sn、Li、B、Zn、K、Na、Ca、Mg、Fe、Sr、Mo、Co、Rb)的含量分布, 并对其进行健康风险评估。方法 采用电感耦合等离子体质谱法(inductively coupled plasma mass spectrometry, ICP-MS)对市售的51份谷物制品(小麦与玉米)进行26种金属多元素检测, 对检测结果进行统计分析, 结合单因子污染指数、靶标危害指数、致癌指数和膳食摄入量对常量与微量元素进行营养与暴露风险评估。结果 方法线性良好, 准确度与灵敏度高。谷物中除Hg和Li元素外, 其余24种金属多元素均有检出。主成分分析和相关性分析显示小麦与玉米存在种间差异, 不同元素的相关性有区别。Pb、Cd、Hg、As、Cr 5种重金属污染水平整体处于安全水平, 19种金属的靶标危害指数和Pb致癌风险指数远低于警戒值, 处于安全水平, As的致癌风险评估处于潜在风险。营养膳食评估显示谷物富含K和Mg, 低Na, Cr的每日摄入量为推荐摄入量的3倍左右, 需要引起关注。结论 本研究建立的方法可有效用于谷物多元素的测定, 为邯郸市居民金属多元素健康评估提供了科学依据, 邯郸市谷物制品健康评估水平整体处于较为健康水平, 但需持续关注Cr和As元素的健康风险。, correspAuthors=李伟昊, authorNote=null, correspAuthorsNote=
*李伟昊(1976—), 男, 博士, 主任技师, 主要研究方向为食品安全。E-mail:
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连莹莹(1985—), 女, 硕士, 副主任技师, 主要研究方向为食品安全风险监测。E-mail:

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连莹莹(1985—), 女, 硕士, 副主任技师, 主要研究方向为食品安全风险监测。E-mail:

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连莹莹(1985—), 女, 硕士, 副主任技师, 主要研究方向为食品安全风险监测。E-mail:

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International Journal of Environmental Research and Public Health, 2021, 18(5): 2617., articleTitle=Hazardous heavy metals accumulation and health risk assessment of different vegetable species in contaminated soils from a typical mining city, central China, refAbstract=null)], funds=[Fund(id=1217127917486789172, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, awardId=23422083170, language=CN, fundingSource=邯郸市科学技术研究与发展计划项目(23422083170), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1217127907911192702, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, xref=null, ext=[AuthorCompanyExt(id=1217127907919581312, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, companyId=1217127907911192702, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Handan Centre for Disease Control and Prevention, Handan 056002, China), AuthorCompanyExt(id=1217127907927969921, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, companyId=1217127907911192702, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=邯郸市疾病预防控制中心, 邯郸 056002)])], figs=[ArticleFig(id=1217127913443479958, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=EN, label=Fig.1, caption=Correlation analysis of metal elements in cereals, figureFileSmall=3vCcr7reOFk+6pncAW9LnQ==, figureFileBig=dDB6q8zoBXYUOlvY4dZjjg==, tableContent=null), ArticleFig(id=1217127913544143258, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=CN, label=图1, caption=谷物中金属元素相关性分析

注: *P≤0.05; **P≤0.01, 图3同。

, figureFileSmall=3vCcr7reOFk+6pncAW9LnQ==, figureFileBig=dDB6q8zoBXYUOlvY4dZjjg==, tableContent=null), ArticleFig(id=1217127913665778079, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=EN, label=Fig.2, caption=PCA of metal elements in cereals, figureFileSmall=CrMuUY9A1fubTKauTrc0Bw==, figureFileBig=Ue0KDFMjRrz4C9YhgvnPpg==, tableContent=null), ArticleFig(id=1217127913791607202, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=CN, label=图2, caption=谷物制品中金属元素的PCA

注: A. 谷物制品中PCA分析得分图; B. 谷物制品中PCA分析载荷图。

, figureFileSmall=CrMuUY9A1fubTKauTrc0Bw==, figureFileBig=Ue0KDFMjRrz4C9YhgvnPpg==, tableContent=null), ArticleFig(id=1217127913913242025, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=EN, label=Fig.3, caption=Comparative analysis of metal elements content in maize and wheat, figureFileSmall=pPaSRFWKE/nC+qFcZt7/2g==, figureFileBig=Bs7y3YJ1b09Ydvo2ZcE9lA==, tableContent=null), ArticleFig(id=1217127914030682545, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=CN, label=图3, caption=玉米与小麦中金属元素含量与组间比对分析

注: A. 必需常量元素; B. 必需微量元素; C. 其他元素; ***P≤0.001。

, figureFileSmall=pPaSRFWKE/nC+qFcZt7/2g==, figureFileBig=Bs7y3YJ1b09Ydvo2ZcE9lA==, tableContent=null), ArticleFig(id=1217127914127151544, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=EN, label=Table 1, caption=

Isotopes and internal standard elements of 26 kinds of elements

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 质荷比(m/z) 内标 元素 质荷比(m/z) 内标
B 11 45Sc Na 23 45Sc
Mg 24 45Sc Al 27 45Sc
K 39 45Sc Ca 43 45Sc
Li 7 45Sc V 51 45Sc
Cr 53 45Sc Mn 55 45Sc
Fe 56 45Sc Co 59 45Sc
Ni 60 72Ge Cu 63 72Ge
Zn 66 72Ge As 75 72Ge
Se 78 72Ge Rb 85 72Ge
Sr 88 72Ge Mo 95 115In
Cd 111 115In Sn 118 115In
Sb 121 115In Ba 137 115In
Hg 202 115In Pb 208 115In
), ArticleFig(id=1217127914211037627, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=CN, label=表1, caption=

26种元素的同位素和内标元素

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 质荷比(m/z) 内标 元素 质荷比(m/z) 内标
B 11 45Sc Na 23 45Sc
Mg 24 45Sc Al 27 45Sc
K 39 45Sc Ca 43 45Sc
Li 7 45Sc V 51 45Sc
Cr 53 45Sc Mn 55 45Sc
Fe 56 45Sc Co 59 45Sc
Ni 60 72Ge Cu 63 72Ge
Zn 66 72Ge As 75 72Ge
Se 78 72Ge Rb 85 72Ge
Sr 88 72Ge Mo 95 115In
Cd 111 115In Sn 118 115In
Sb 121 115In Ba 137 115In
Hg 202 115In Pb 208 115In
), ArticleFig(id=1217127914303312322, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=EN, label=Table 2, caption=

Grading standards for metal pollution index

, figureFileSmall=null, figureFileBig=null, tableContent=
级别 Pi 等级 P综 等级
1 Pi≤0.7 安全 P综≤0.7 安全
2 0.7<Pi≤1 警戒 0.7<P综≤1 警戒
3 1<Pi≤2 轻污染 1<P综≤2 轻污染
4 2<Pi≤3 中度污染 2<P综≤3 中度污染
5 Pi≥3 重度污染 P综≥3 重度污染
), ArticleFig(id=1217127914416558535, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=CN, label=表2, caption=

金属污染指数分级标准

, figureFileSmall=null, figureFileBig=null, tableContent=
级别 Pi 等级 P综 等级
1 Pi≤0.7 安全 P综≤0.7 安全
2 0.7<Pi≤1 警戒 0.7<P综≤1 警戒
3 1<Pi≤2 轻污染 1<P综≤2 轻污染
4 2<Pi≤3 中度污染 2<P综≤3 中度污染
5 Pi≥3 重度污染 P综≥3 重度污染
), ArticleFig(id=1217127915725181391, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=EN, label=Table 3, caption=

RfD of metal multi-elements

, figureFileSmall=null, figureFileBig=null, tableContent=
金属 参考计量RfD/[mg/(kg·d)] 金属 参考计量RfD/[mg/(kg·d)]
As 0.0003 Hg 0.0003
Al 1.0000 Mn 0.1400
B* 9.6000 Mo 0.0050
Ba 0.2000 Ni 0.0054
Cd 0.0005 Pb 0.0014
Co 0.0300 Sb 0.0004
Cr 0.0030 Se 0.0050
Cu 0.0050 V* 7.7000
Fe 0.3000 Zn 0.3000
Li 0.0020
), ArticleFig(id=1217127915871982042, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=CN, label=表3, caption=

金属多元素的RfD

, figureFileSmall=null, figureFileBig=null, tableContent=
金属 参考计量RfD/[mg/(kg·d)] 金属 参考计量RfD/[mg/(kg·d)]
As 0.0003 Hg 0.0003
Al 1.0000 Mn 0.1400
B* 9.6000 Mo 0.0050
Ba 0.2000 Ni 0.0054
Cd 0.0005 Pb 0.0014
Co 0.0300 Sb 0.0004
Cr 0.0030 Se 0.0050
Cu 0.0050 V* 7.7000
Fe 0.3000 Zn 0.3000
Li 0.0020
), ArticleFig(id=1217127915968451037, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=EN, label=Table 4, caption=

DRIS index of each nutrient (mg/d)

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 EAR RNI UL AI
Ca 650 800 2000 -
K - - - 2000
Na - - - 1500
Mg 280 330 - -
Fe 男: 9/女: 15 男: 12/女: 20 42 -
Zn 男: 10.4/女: 6.1 男: 12.5/女: 7.5 40 -
Se 0.05 0.06 0.4 -
Cu 0.60 0.8 8.0 -
Mn - - 11 男: 4.5/女: 4.0
Mo 0.085 0.1 0.9 -
Cr - - - 0.03
), ArticleFig(id=1217127916094280165, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=CN, label=表4, caption=

各营养素的DRIS指数(mg/d)

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 EAR RNI UL AI
Ca 650 800 2000 -
K - - - 2000
Na - - - 1500
Mg 280 330 - -
Fe 男: 9/女: 15 男: 12/女: 20 42 -
Zn 男: 10.4/女: 6.1 男: 12.5/女: 7.5 40 -
Se 0.05 0.06 0.4 -
Cu 0.60 0.8 8.0 -
Mn - - 11 男: 4.5/女: 4.0
Mo 0.085 0.1 0.9 -
Cr - - - 0.03
), ArticleFig(id=1217127916190749163, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=EN, label=Table 5, caption=

Detection status of various elements in cereals (n=51)

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 检出率/% 含量分布/(mg/kg)
P25 P50 P75 P95 最小值 最大值 平均值
Ba 100 0.0730 0.3430 0.7900 1.0300 0.0300 1.1100 0.4550
V 55 0.0020 0.0045 0.0068 0.0138 0.0440 0.0145 0.0052
Ca 100 12.9000 70.9000 94.2000 137.2000 5.4100 191.0000 59.8000
Cd 57 0.0015 0.0095 0.0139 0.0163 0.0030 0.0168 0.0085
Co 94 0.0030 0.0043 0.0066 0.0082 0.0020 0.0089 0.0047
K 100 1344.0000 1547.0000 1985.0000 2972.0000 982.0000 4436.0000 1764.0000
Al 100 1.0000 2.1300 3.2700 7.2400 0.0820 9.1500 2.6300
Mg 100 144.0000 201.0000 318.0000 578.0000 40.7000 379.0000 240.0000
Mn 100 0.9690 3.8800 5.4200 9.9000 0.4160 12.8000 3.7200
Mo 100 0.2000 0.2270 0.2720 0.4700 0.1400 0.5450 0.2460
Na 67 0.2500 5.2300 6.7900 9.1100 0.5100 15.0000 4.0200
Ni 100 0.0593 0.2000 0.2380 0.2810 0.0108 0.2350 0.1610
Pb 61 0.0020 0.0104 0.0416 0.0956 0.0050 0.1520 0.0239
Sr 100 0.0677 0.2690 0.9900 1.2600 0.0381 0.5900 0.5250
Sb 33 0.0025 0.0025 0.0066 0.0270 0.0071 0.0820 0.0070
Fe 100 5.2200 10.3000 13.5000 22.5000 2.1100 24.8000 10.4000
Cu 100 0.4520 1.2300 1.3900 2.0300 0.2580 2.7200 1.0400
Se 67 0.0025 0.0161 0.0275 0.1120 0.0050 0.7690 0.0342
Sn 14 0.0025 0.0025 0.0025 0.5800 0.0081 0.9820 0.0466
Zn 75 0.1000 2.6600 5.1000 16.1000 1.3100 21.0000 4.0100
Cr 100 0.1640 0.3550 0.4230 0.4920 0.0820 0.5330 0.2990
As 59 0.0020 0.0072 0.0120 0.0260 0.0046 0.0296 0.0083
B 49 0.0250 0.0250 0.4270 1.6400 0.0550 2.1200 0.3130
Rb 51 0.0050 0.4010 1.0500 2.7600 0.4450 4.4300 0.6790
), ArticleFig(id=1217127916316578291, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=CN, label=表5, caption=

谷物中各元素检出情况(n=51)

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 检出率/% 含量分布/(mg/kg)
P25 P50 P75 P95 最小值 最大值 平均值
Ba 100 0.0730 0.3430 0.7900 1.0300 0.0300 1.1100 0.4550
V 55 0.0020 0.0045 0.0068 0.0138 0.0440 0.0145 0.0052
Ca 100 12.9000 70.9000 94.2000 137.2000 5.4100 191.0000 59.8000
Cd 57 0.0015 0.0095 0.0139 0.0163 0.0030 0.0168 0.0085
Co 94 0.0030 0.0043 0.0066 0.0082 0.0020 0.0089 0.0047
K 100 1344.0000 1547.0000 1985.0000 2972.0000 982.0000 4436.0000 1764.0000
Al 100 1.0000 2.1300 3.2700 7.2400 0.0820 9.1500 2.6300
Mg 100 144.0000 201.0000 318.0000 578.0000 40.7000 379.0000 240.0000
Mn 100 0.9690 3.8800 5.4200 9.9000 0.4160 12.8000 3.7200
Mo 100 0.2000 0.2270 0.2720 0.4700 0.1400 0.5450 0.2460
Na 67 0.2500 5.2300 6.7900 9.1100 0.5100 15.0000 4.0200
Ni 100 0.0593 0.2000 0.2380 0.2810 0.0108 0.2350 0.1610
Pb 61 0.0020 0.0104 0.0416 0.0956 0.0050 0.1520 0.0239
Sr 100 0.0677 0.2690 0.9900 1.2600 0.0381 0.5900 0.5250
Sb 33 0.0025 0.0025 0.0066 0.0270 0.0071 0.0820 0.0070
Fe 100 5.2200 10.3000 13.5000 22.5000 2.1100 24.8000 10.4000
Cu 100 0.4520 1.2300 1.3900 2.0300 0.2580 2.7200 1.0400
Se 67 0.0025 0.0161 0.0275 0.1120 0.0050 0.7690 0.0342
Sn 14 0.0025 0.0025 0.0025 0.5800 0.0081 0.9820 0.0466
Zn 75 0.1000 2.6600 5.1000 16.1000 1.3100 21.0000 4.0100
Cr 100 0.1640 0.3550 0.4230 0.4920 0.0820 0.5330 0.2990
As 59 0.0020 0.0072 0.0120 0.0260 0.0046 0.0296 0.0083
B 49 0.0250 0.0250 0.4270 1.6400 0.0550 2.1200 0.3130
Rb 51 0.0050 0.4010 1.0500 2.7600 0.4450 4.4300 0.6790
), ArticleFig(id=1217127916446601724, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=EN, label=Table 6, caption=

Pollution index of 5 kinds of heavy metals in cereals

, figureFileSmall=null, figureFileBig=null, tableContent=
种类 Pi 污染
程度		 Pc 污染
程度
Pb Cd Cr As Hg
玉米 0.088 0.037 0.189 0.008 0.075 安全 0.149 安全
小麦 0.187 0.135 0.414 0.025 0.075 安全 0.316 安全
合计 0.120 0.085 0.299 0.017 0.075 安全 0.228 安全
), ArticleFig(id=1217127916555653633, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=CN, label=表6, caption=

谷物中5种重金属的污染指数

, figureFileSmall=null, figureFileBig=null, tableContent=
种类 Pi 污染
程度		 Pc 污染
程度
Pb Cd Cr As Hg
玉米 0.088 0.037 0.189 0.008 0.075 安全 0.149 安全
小麦 0.187 0.135 0.414 0.025 0.075 安全 0.316 安全
合计 0.120 0.085 0.299 0.017 0.075 安全 0.228 安全
), ArticleFig(id=1217127916748591631, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=EN, label=Table 7, caption=

EDI levels of metal multi-elements of residents [mg/(kg d)]

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 EDI (×10-3) 元素 EDI (×10-3)
K 8389 B 1.49
Mg 1141 Cr 1.42
Ca 284 Mo 1.17
Fe 49.5 Ni 0.766
Na 19.1 Sn 0.222
Zn 19.1 Se 0.163
Mn 17.7 Pb 0.114
Al 12.5 Cd 0.0404
Cu 4.95 As 0.0394
Rb 3.23 Sb 0.0333
Sr 2.50 V 0.0249
Ba 2.16 Co 0.0224
Li* 0.0476 Hg* 0.00710
), ArticleFig(id=1217127916861837847, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=CN, label=表7, caption=

居民的金属多元素EDI水平[mg/(kg d)]

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 EDI (×10-3) 元素 EDI (×10-3)
K 8389 B 1.49
Mg 1141 Cr 1.42
Ca 284 Mo 1.17
Fe 49.5 Ni 0.766
Na 19.1 Sn 0.222
Zn 19.1 Se 0.163
Mn 17.7 Pb 0.114
Al 12.5 Cd 0.0404
Cu 4.95 As 0.0394
Rb 3.23 Sb 0.0333
Sr 2.50 V 0.0249
Ba 2.16 Co 0.0224
Li* 0.0476 Hg* 0.00710
), ArticleFig(id=1217127916983472672, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=EN, label=Table 8, caption=

Health risk assessment of 19 kinds of metal elements in cereals

, figureFileSmall=null, figureFileBig=null, tableContent=
金属 THQ (×10-3) 金属 THQ (×10-3)
As 0.1313 Hg 0.0237
Al 0.0125 Mn 0.1264
B 0.0002 Mo 0.2340
Ba 0.0108 Ni 0.1418
Cd 0.0808 Pb 0.0812
Co 0.0007 Sb 0.0833
Cr 0.4740 Se 0.0325
Cu 0.9892 V 0.0000
Fe 0.1649 Zn 0.0636
Li 0.0238
), ArticleFig(id=1217127917088330279, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=CN, label=表8, caption=

谷物中19种金属元素健康风险评估

, figureFileSmall=null, figureFileBig=null, tableContent=
金属 THQ (×10-3) 金属 THQ (×10-3)
As 0.1313 Hg 0.0237
Al 0.0125 Mn 0.1264
B 0.0002 Mo 0.2340
Ba 0.0108 Ni 0.1418
Cd 0.0808 Pb 0.0812
Co 0.0007 Sb 0.0833
Cr 0.4740 Se 0.0325
Cu 0.9892 V 0.0000
Fe 0.1649 Zn 0.0636
Li 0.0238
), ArticleFig(id=1217127917193187882, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=EN, label=Table 9, caption=

Assessment of dietary intake of nutrients in cereals

, figureFileSmall=null, figureFileBig=null, tableContent=
营养素 每100 g营养
成分		 EAR/% RNI/% UL/% AI/%
Ca 5.98 mg 2.81 2.29 0.91 *
K 176 mg * * * 27.0
Na 0.402 mg * * * 0.08
Mg 24 mg 26.2 22.2 * *
Fe 1.04 mg 男: 35.3/
女: 21.2		 男: 26.5/
女: 15.9		 7.57 *
Zn 0.401 mg 男: 11.8/
女: 20.1		 男: 9.81/
女: 16.3		 3.07 *
Se 3.42 μg 26.2 16.7 2.61 *
Cu 0.104 mg 53.0 39.8 3.98 *
Mn 0.372 mg * * 10.3 男: 25.3/
女: 31.0
Mo 24.6 μg 88.5 75.2 8.36 *
Cr 29.9 μg * * * 305
), ArticleFig(id=1217127917302239788, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516730483598, language=CN, label=表9, caption=

谷物中营养素膳食摄入量评估

, figureFileSmall=null, figureFileBig=null, tableContent=
营养素 每100 g营养
成分		 EAR/% RNI/% UL/% AI/%
Ca 5.98 mg 2.81 2.29 0.91 *
K 176 mg * * * 27.0
Na 0.402 mg * * * 0.08
Mg 24 mg 26.2 22.2 * *
Fe 1.04 mg 男: 35.3/
女: 21.2		 男: 26.5/
女: 15.9		 7.57 *
Zn 0.401 mg 男: 11.8/
女: 20.1		 男: 9.81/
女: 16.3		 3.07 *
Se 3.42 μg 26.2 16.7 2.61 *
Cu 0.104 mg 53.0 39.8 3.98 *
Mn 0.372 mg * * 10.3 男: 25.3/
女: 31.0
Mo 24.6 μg 88.5 75.2 8.36 *
Cr 29.9 μg * * * 305
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邯郸市谷物制品中26种金属多元素监测与健康风险评估
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连莹莹 , 方彦飞 , 韩永红 , 闫慧敏 , 赵艳 , 张璐 , 李伟昊 *
食品安全质量检测学报 | 专题：食品安全风险评估与风险监测 2025,16(15): 157-166
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食品安全质量检测学报 | 专题：食品安全风险评估与风险监测 2025, 16(15): 157-166
邯郸市谷物制品中26种金属多元素监测与健康风险评估
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连莹莹 , 方彦飞, 韩永红, 闫慧敏, 赵艳, 张璐, 李伟昊*
作者信息
  • 邯郸市疾病预防控制中心, 邯郸 056002

    • 连莹莹(1985—), 女, 硕士, 副主任技师, 主要研究方向为食品安全风险监测。E-mail:

通讯作者:

*李伟昊(1976—), 男, 博士, 主任技师, 主要研究方向为食品安全。E-mail:
Monitoring and health risk assessment of 26 kinds of metal multi-elements in cereals in Handan City
Ying-Ying LIAN , Yan-Fei FANG, Yong-Hong HAN, Hui-Min YAN, Yan ZHAO, Lu ZHANG, Wei-Hao LI*
Affiliations
  • Handan Centre for Disease Control and Prevention, Handan 056002, China
出版时间: 2025-08-15 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250422005
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摘要
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目的 了解邯郸市售谷物制品中26种金属多元素(Pb、Cd、Hg、As、Cr、Al、Mn、Cu、Ba、V、Se、Sb、Ni、Sn、Li、B、Zn、K、Na、Ca、Mg、Fe、Sr、Mo、Co、Rb)的含量分布, 并对其进行健康风险评估。方法 采用电感耦合等离子体质谱法(inductively coupled plasma mass spectrometry, ICP-MS)对市售的51份谷物制品(小麦与玉米)进行26种金属多元素检测, 对检测结果进行统计分析, 结合单因子污染指数、靶标危害指数、致癌指数和膳食摄入量对常量与微量元素进行营养与暴露风险评估。结果 方法线性良好, 准确度与灵敏度高。谷物中除Hg和Li元素外, 其余24种金属多元素均有检出。主成分分析和相关性分析显示小麦与玉米存在种间差异, 不同元素的相关性有区别。Pb、Cd、Hg、As、Cr 5种重金属污染水平整体处于安全水平, 19种金属的靶标危害指数和Pb致癌风险指数远低于警戒值, 处于安全水平, As的致癌风险评估处于潜在风险。营养膳食评估显示谷物富含K和Mg, 低Na, Cr的每日摄入量为推荐摄入量的3倍左右, 需要引起关注。结论 本研究建立的方法可有效用于谷物多元素的测定, 为邯郸市居民金属多元素健康评估提供了科学依据, 邯郸市谷物制品健康评估水平整体处于较为健康水平, 但需持续关注Cr和As元素的健康风险。
谷物  /  玉米  /  小麦  /  电感耦合等离子体质谱法  /  重金属  /  风险评估

Objective To investigate the distribution of 26 kinds of metal elements (Pb, Cd, Hg, As, Cr, Al, Mn, Cu, Ba, V, Se, Sb, Ni, Sn, Li, B, Zn, K, Na, Ca, Mg, Fe, Sr, Mo, Co, Rb) and assess the dietary risk with cereals in Handan City. Methods A total of 51 cereal samples (wheat and maize) were analyzed for 26 kinds of metal elements using inductively coupled plasma mass spectrometry (ICP-MS). Statistical analysis was performed on the detection results, and nutritional and exposure risk assessments were conducted for macro- and trace elements using the individual pollution index, target hazard quotient, carcinogenic risk, and estimated daily intake. Results The method demonstrated good linearity, high accuracy, and sensitivity. Among the 26 kinds of metal elements, 24 kinds of metal elements were detected in the cereal samples, except for Hg and Li. Principal component analysis and correlation analysis revealed interspecies differences between wheat and maize, as well as distinct correlations among different elements. The contamination levels of 5 kinds of heavy metals (Pb, Cd, Hg, As, Cr) were within safe limits. The target hazard index of 19 kinds of metal elements and the carcinogenic risk index for Pb were significantly below threshold levels, indicating no health risks, but the carcinogenic risk assessment for As suggested potential health risks. Nutritional assessment showed that the cereals were rich in K and Mg, but low in Na. However, Cr exposure reached nearly 300% of the adequate daily intake, indicating a significant health concern. Conclusion The established method is effective for multi-element analysis in cereals. This research findings provide updated dietary intake assessment of multi-elements of Handan adult consumers. The dietary assessment indicates that intake of cereals in Handan City poses no significant health risks, but particular attention should be paid to Cr and As contamination.

cereals  /  maize  /  wheat  /  inductively coupled plasma mass spectrometry  /  heavy metals  /  risk assessment
连莹莹, 方彦飞, 韩永红, 闫慧敏, 赵艳, 张璐, 李伟昊. 邯郸市谷物制品中26种金属多元素监测与健康风险评估. 食品安全质量检测学报, 2025 , 16 (15) : 157 -166 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250422005
Ying-Ying LIAN, Yan-Fei FANG, Yong-Hong HAN, Hui-Min YAN, Yan ZHAO, Lu ZHANG, Wei-Hao LI. Monitoring and health risk assessment of 26 kinds of metal multi-elements in cereals in Handan City[J]. Journal of Food Safety & Quality, 2025 , 16 (15) : 157 -166 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250422005
正文
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0 引言
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联合国世界粮农组织(Food and Agriculture Organization of the United Nation, FAO)统计显示, 我国是世界上小麦第一生产国和消费国, 玉米第二大生产国和消费国。稻谷是我国居民口粮消费的主体, 占口粮消费量的60%以上。其中玉米和小麦是北方地区居民能量摄入主要来源[1]。谷物制品除了作为碳水化合物, 还富含蛋白质、维生素和各种矿物质[2]。《中国居民膳食指南2022》建议成年人每天摄入谷类食物200~300 g, 推荐全谷物食物50~150 g。根据在人体中的含量, 元素可分为常量元素(>0.01%)和微量元素(<0.01%)。世界卫生组织(World Health Organization, WHO)将微量元素分为必需微量元素、可能必需微量元素和潜在毒性元素。根据WS/T 578.2—2018《中国居民膳食营养素参考摄入量 第2部分: 常量元素》、WS/T 578.3—2017《中国居民膳食营养素参考摄入量 第3部分: 微量元素》和《中国居民膳食营养素参考摄入量2023版》[3]中规定, Ca、Na、K、Mg这4种为常量营养金属元素, Fe、Zn、Cu、Se、Cr、Co、Mo这7种为必需微量金属元素; B、Mn、Ni、V这4种为可能必需微量金属元素。我国GB 2762—2022《食品安全国家标准 食品中污染物限量》明确了谷物中5类重金属污染物Pb、Cd、Hg、As、Cr的限量值。
As、Pb、Cd、Cr和Hg是对人体有危害的金属, 可造成儿童生长发育迟缓、肾脏损伤[4]、贫血、心血管疾病等[5]。目前对谷物类食品的重金属污染研究较多, 有研究发现安徽省小麦食品[6]中重金属综合污染指数为轻度污染, 河南省部分玉米[7]和华北地区[8]部分谷物中Pb含量超标等。同时, 多种常量和微量元素在人类健康和疾病中起着重要的作用[9], 根据它们在新陈代谢中的作用机制的不同, 金属元素显示出营养和毒理学多重效应[10]。因此对玉米和小麦中多种元素进行分析研究, 对于我国居民的饮食健康具有十分重要的意义。金属元素检出方法众多, 有原子荧光光谱法[11]、石墨炉原子吸收光谱法、火焰原子吸收光谱法[11]、电感耦合等离子体发射光谱法(inductively coupled plasma/optical emission spectrometry, ICP-OES)[12]、电感耦合等离子体质谱法(inductively coupled plasma mass spectrometry, ICP-MS)法等。其中ICP-MS方法[13]检出灵敏度高, 线性好, 可以一次性检测多种金属与类金属元素, 本研究采用该方法对邯郸地区的玉米与小麦样品的26种金属多元素进行含量检测。目前邯郸地区谷类食品中金属多元素的研究结果较少, 本研究结合内梅罗污染指数法[14]、靶标危害指数(target hazard quotient, THQ)[15]与危害指数(hazard index, HI)、致癌风险指数(carcinogenic risk, CR)[16]、膳食营养素参考(dietary reference intakes, DRIs)[17]等多项指标, 对金属多元素摄入的健康风险进行评估, 结合相关性分析、主要成分分析、非参数检验等多种统计方法分析谷物制品中金属多元素的分布情况和种间特征, 为邯郸地区食品安全检测和质量安全标准制定等提供科学依据和理论支持。
1 材料与方法
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1.1 样品来源
在邯郸地区大型超市、小型超市、农贸市场、网店、种植环节共采集51份谷物制品, 包含26份玉米面样品与25份小麦粉样品, 采样样品范围覆盖农村与城市地区, 样品以邯郸本地为主, 其余均来自河北省其他地市。
1.2 试剂
ICP-MS分析用多元素(Al, As, B, Ba, Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Mo, Na, Ni, Pb, Rb, Sb, Se, Sn, Sr, V, Zn)标准溶液、ICP-MS分析内标(Bi, Ge, In, Sc, Y)标准溶液(质量浓度100 μg/mL, 国家有色金属及电子材料分析测试中心); Hg标准溶液(质量浓度为1000 μg/mL, 中国计量科学研究院); 硝酸(电子纯, 国药集团化学试剂有限公司); 双氧水(优级纯, 上海沃凯生物技术有限公司); 大米成分分析标准物质、河南小麦成分分析标准物质(30 g/瓶, 中国地质科学院地球物理地球化学勘查研究所); 所有实验用水均为超纯水。
1.3 仪器与设备
NexIon-350 x型号电感耦合等离子体质谱仪(美国铂金埃尔默公司); Ethos Up微波消解仪(意大利迈尔斯通公司); AE-240万分之一天平(瑞士梅特勒托利多公司)。
1.4 实验方法
1.4.1 样品制备与标液配制
称取0.3 g(精确至0.001 g)充分混匀的谷物制品于微波消解罐中, 按照GB 5009.268—2016《食品安全国家标准 食品中多元素的测定》第一法ICP-MS法进行消解, 用超纯水定容至25 mL, 混匀备用, 同时做空白实验。微波消解的程序设定如下: 从室温升至120 ℃, 升温时间5 min, 恒温5 min; 从120 ℃升至160 ℃, 升温时间5 min, 恒温10 min; 从160 ℃升至200 ℃, 升温时间5 min, 恒温25 min。用1%的硝酸溶液逐级稀释混合标准溶液和内标使用液, Hg标准溶液现用现配。
1.4.2 ICP-MS上机检测
仪器开机后抽真空, 待真空度满足条件后, 进行调谐, 仪器参数设置如下: 射频功率1600 W; 等离子体气流量19 L/min; 辅助气流量1.2 L/min; 雾化器流量1 L/min; 采集模式: 跳峰扫描; 重复测定3次。编辑测定方法, 根据待测元素的性质选择相应的内标元素, 采用动能主导碰撞模式(kinetic energy dominated collision mode, KED)在线加入内标, 进行各元素的分析。26种金属元素的同位素质荷比(m/z)和内标元素见表1。
1.4.3 质量控制
实验过程中采取有证标准物质测定、试剂空白测定、样品空白测定、加标回收等多种质控措施, 保证检测数据的可靠性。
1.5 评价标准
1.5.1 判断依据
根据元素在人体中的含量, 元素可分为常量元素(>0.01%)和微量元素(<0.01%)。参考WS/T 578.2—2018和WS/T 578.3—2017对谷物中的营养素进行评价。参考GB 2762—2022对谷物中的重金属污染物进行评价。
1.5.2 内梅罗指数法
采用单因子污染指数法(individual pollution index, Pi)和综合污染指数法(combined pollution index, P综)对金属污染程度进行分级评价, 计算见公式(1)~(2)。
Pi=$\frac{{C}_{i}}{{S}_{i}}$
P综=$\sqrt{\frac{{P}^{\text{2}}{}_{\text{max}}+{P}^{\text{2}}{}_{\text{ave}}}{2}}$
式中: Pi为第i个元素的污染指数, 对单个金属的污染程度进行描述; Ci表示样品中该金属的实测值, mg/kg; Si表示该金属的限量值, mg/kg; P综为所有金属的综合污染指数; Pmax为各单因子污染指数中的最大值; Pave为各单因子污染指数的平均值。结合参考文献, Pi和P综的评价分级标准见表2。
1.5.3 健康风险评估
(1)摄入量评估
对金属的每日摄入量(estimated daily intake, EDI)进行评估, 计算公式见式(3)。
EDI=$\frac{C\times IRD\times EF\times ED}{BW\times AT}$×10-3
式中: EDI为每日摄入量, mg/(kg·d); C为某种金属的平均含量, mg/kg; IRD为该类食品的每日摄入量(daily intake rates), g/d, 根据中国疾病预防控制中心营养与健康所数据年鉴, 我国居民粮谷类平均摄入量为305.8 g, 作为谷物的摄入量进行计算; EF为暴露频率(exposure frequency), 365 d/year; ED为暴露时间(exposure duration), 采用平均寿命70年进行计算; BW为人群的平均体重(body weight), 64.3 kg[14]; AT为平均接触非致癌物时间(average exposure time), 定为平均寿命70×365 d。
(2) THQ与HI评估
通过THQ来评估单个元素的引起的饮食摄入健康风险, HI来评估金属多元素共同作用引起的健康风险, 计算见公式(4)~(5)。
THQ=$\frac{EDI}{RfD}$
HI=${\sum }_{i=1}^{n}$THQ
式中: RfD为经口摄入参考计量(oral reference dose), 各金属的参考摄入计量[14,18-19]见表3。当THQ和HI值<1时, 说明人群没有较大的健康风险; 当THQ和HI值>1时, 说明有害因素暴露对人群具有严重健康风险, 其值越大, 健康风险越高。
(3)致癌风险评估
通过CR来评估致癌因子的致癌风险, 计算见公式(6)。
CR=EDI×CSFo
式中: CSFo为致癌斜率因子(oral carcinogenic slope factor)[14], 由美国环保局(U.S. Environmental Protection Agency, USEPA)制定, [mg/(kg·d)]-1, 各元素的致癌斜率因子[14,18]分别为: As 1.5(无机砷); Pb 0.0085。CR值的判定标准如下: CR>1×10-4时, 高风险; 1×10-6<CR <1×10-4, 潜在风险; CR<1×10-6, 风险较低或无风险[16]。
(4)营养素膳食摄入评估
参考GB 28050—2025标准, 对谷物中人体必需元素含量采用每100 g食品中可食部分的具体数值进行标示。以WS/T 578.2—2018、WS/T 578.3—2018和《中国居民膳食营养素参考摄入量2023》推荐的膳食营养素参考摄入量(dietary reference intakes, DRIs)[20]对每日营养素摄入量进行膳食摄入量评估。计算公式见式(7)。
DRIs/%=$\frac{C\times IRD}{\text{DRIs}}$×10-3×100%
式中: DRIs指数包括: 平均需要量(estimated average requirement, EAR)、推荐摄入量(recommended nutrient intake, RNI)、适宜摄入量(adequate intake, AI)、可耐受最高摄入量(tolerable upper intake level, UL); C为测定的该营养素的含量, mg/kg; IRD为谷物食品的每日摄入量, 305.8 g/d。具体各类DRIs值见表4。
1.6 数据处理
采用Excel 2021软件和SPSS 22.0软件进行数据统计与分析, Prism 10和Origin 2024软件绘图。低于检出限的数据, 按照检出限的1/2进行统计分析。
2 结果与分析
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2.1 方法学评价
26种金属多元素标准曲线相关系数r在0.9991~1.0000之间, 检出限与GB 5009.268—2016第一法一致, 回收率范围在88.8%~103.5%, 有证标准物质测定值在有效区间, 说明实验方法准确度良好。
2.2 谷物中各元素的总体检出情况
51种谷物样品中共有24种金属元素检出, Hg和Li元素均未检出。其中: Ba、Ca、K、Al、Mg、Mn、Mo、Ni、Sr、Fe、Cu、Cr这12种元素的检出率为100%, V、Cd、Co、Na、Pb、Se、Zn、As、Rb这9种元素的检出值大于50%, Sb、Sn和B这3种元素的检出率小于50%。谷物所有检出元素中平均含量最高元素为K (1764 mg/kg), 含量最低元素为V (0.0052 mg/kg)。具体检出情况见表5。
2.3 谷物中金属多元素含量的统计学分析
以检出的除Hg和Li外的24种金属元素含量为指标, 使用Origin 2024软件对51份谷物样品进行了相关性分析, 根据金属含量分布特征, 分析方法[18]选择Spearman, 结果显示Na、Al、Ca、V、Cr、Mn、B、Ni、Cu、Zn、As、Se、Sr、Cd、Ba、Rb互为显示显著相关, 协同作用强; Mg和Al、Ca、V、Mn、Fe、Co、B、Cu、Zn、Se、Mo、Sn、Sb、Rb、Pb有显著相关; Al、K、Co、Mn互为显著相关; Ca、Cr、Fe、Mo互为显著相关; V与Co显著相关; ; Fe与Co、Ni、Cu、As、Sr、Ba、Mo互为显著相关。其他元素间相关系较弱。具体相关性分析结果见图1。
采用SPSS 22.0对所有的谷物样品进行主成分分析(principal component analysis, PCA), 通过PCA的得分图可看出小麦与玉米组别数据存在显著性差异; 载荷图可看出各元素的相关性, 两个元素指标间夹角越大, 相关性越低, 夹角越小, 夹角接近0度, 相关性越强, 载荷图结果与图1中Spearman分析结果基本一致。具体结果见图2。
2.4 玉米面与小麦粉中各元素组间含量统计分析
除Hg和Li元素两类谷物样品中均未检出外, 其他24种金属多元素结果采用SPSS 22.0软件进行玉米粉与小麦粉组间Mann-Whittney U非参数检验。分析结果显示, Na、Ca、Fe、Zn、Cu、Se、Cr、Al、Mn、Sr、Ba、Rb、B、V、Cd、As和Ni这17种元素在玉米与小麦含量均存在显著性差异(P<0.05), Mg、K、Co、Mo、Sb、Sn和Pb这7种元素含量无显著差异。玉米与小麦中各元素含量与组间比对结果, 具体见图3。
2.5 谷物制品中重金属含量与污染物指数评价
由于GB 2762—2022中仅对Hg、Pb、Cd、Cr、As这5种元素进行了限值规定, 其余元素无限值要求, 因此仅讨论这5种重金属的超标情况。这51种谷物制品中, Hg、Pb、Cd、Cr、As重金属含量均未超标, 合格率100%。国标中各元素限量标准: Pb 0.2 mg/kg、Cd 0.1 mg/kg、Hg 0.02 mg/kg、As 0.5 mg/kg、Cr 1.0 mg/kg。将该限量标准作为内梅罗指数法中Si值进行计算Pi和Pc。计算结果显示谷物中的这五种重金属的Pi和Pc污染指数都处于安全水平, 玉米和小麦中均为Cr的污染指数最高, As的污染指数最低。具体见表6。
2.6 摄入量评估
根据谷物中所有元素的检出浓度的平均值, 计算人群的EDI水平, 已检出元素中 K元素的EDI最高, 为8.389 mg/(kg·d), Co的EDI最低为0.0224 μg/(kg·d)。具体见表7。
2.7 健康风险评估
根据THQ和HI公式计算金属的膳食摄入风险, 其中Cu的THQ最高为0.9892×10-3, 其次为Cr, THQ 0.4740×10-3, V的THQ最低, 谷物中HI值为2.675×10-3, 所有指数均远小于1, 说明谷物摄入对人群健康风险处于极安全水平。具体见表8。
2.8 致癌风险评估
根据公式(6)计算CR值, 分别为: As 5.91×10-5; Pb 9.69×10-7。风险值从大到小依次为: As>Pb, 说明谷物中致癌风险主要由As贡献, As的CR值表明谷物的饮食摄入量会导致一定的潜在癌症摄入风险, Pb的CR值处于安全水平。
2.9 膳食营养素摄入评估
根据公式(7)计算出每日通过谷物摄入的膳食营养素的占DRIs的比例, 从每100 g营养成分中可以看出, Ca、K、Na、Mg这4种必需常量元素中, 谷物中K、Mg含量较高, 每日摄入贡献率为27.0%和26.2%; Ca和Na的摄入贡献率较低, 不能作为这两种营养素的主要收入途径, 需要额外补充。必需的7种微量元素中, Cr的每日摄入量最高, 为适宜摄入量的3倍左右, 不需要再额外补充; Mo和Cu在平均需要量EAR中贡献率为88.5%和53.0%, 谷物提供了一半以上营养素; Fe、Se、Mn、Zn的营养素贡献率较低, 建议食用其他食品补充该类营养素。具体数值见表9。
3 讨论与结论
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本研究基于GB 5009.268—2016第一法ICP-MS法, 建立了谷物制品中多元素的检测方法, 26种金属多元素标准曲线相关系数r在0.9991~1.0000之间, 检出限与国标一致, 加标回收率范围在88.8%~103.5%, 有证标准物质测定值在有效区间, 方法线性良好, 回收率与准确率高, 可适用于检测谷物中多元素。检测结果显示, 谷物中26种金属多元素除Hg和Li无检出外, 其他24种元素均有检出。12种元素(Ba、Ca、K、Al、Mg、Mn、Mo、Ni、Sr、Fe、Cu、Cr)的检出率最高, 为100%; 9种元素(V、Cd、Co、Na、Pb、Se、Zn、As、Rb)的检出率较高, 大于50%, 3种元素(Sb、Sn和B)的检出率较低小于50%。常量元素的含量高低顺序为: K>Mg>Ca>Na。该结果与文献[21-22]中谷物中常量元素高低水平基本一致, 常量元素中Ca的平均含量为59.8 mg/kg, 与文献[23]中Ca平均含量(54.7~62.7 mg/kg)含量结果一致。结合营养素膳食评估结果, K和Mg的营养素贡献率分别为27.0%和26.2%, 说明谷物作为高钾低钠食品, 可作为需要控盐人群的良好食物来源。但谷物中Ca营养素贡献率较低(2.81%), 需要考虑额外补充钙质。5种国标规定有明确限值的重金属均未超出国家谷物中标准限值, 合格率100%, 检出率高低顺序为: Cr>Pb>As>Cd>Hg。该结果与北京市[24]和山东省[25]谷物制品重金属含量高低水平一致。这5种重金属的单因子污染指数和综合污染指数均为安全级别, 污染指数高低水平为Cr>Pb>Cd>Hg>As, 该结果与河南省洛阳市[26]谷物制品污染指数评估结果基本一致。说明邯郸地区谷物制品中污染物来源主要是Cr元素, Hg和As元素污染物程度较低。值得注意的是, 在营养素膳食评价中, 谷物制品中Cr摄入量超出了适宜摄入量, 是推荐值的3倍, 需要引起额外关注。靶标指数THQ评估19种有经口摄入计量的元素, 结果显示所有元素的THQ值均处于安全水平, 综合危害指数HI值也远小于1 (2.675×10-3), 说明谷物摄入对人群没有健康风险。两致癌元素As和Pb的CR值评估结果, Pb的CR值小于1×10-6, 处于安全水平, As的CR值为5.91×10-5, 说明谷物的饮食摄取量的As对人群会产生潜在致癌风险, 但考虑到本研究测定的是总As, 而无机As是导致癌症的风险的主要因素, 该评估结果可能会偏高。通过主成分分析和Spearman相关性分析, 玉米与小麦金属含量存在组间差异, 该结果与河南省[26]、山东省[27]、浙江省[28]谷物制品分析结果一致。
邯郸地区谷物类样品的健康饮食风险评估整体处于较为安全水平, 但需重点关注Cr元素和As元素的摄入。玉米与小麦作为邯郸地区消耗量较大谷物类食品, 本研究在常见的重金属污染物研究的基础上, 丰富了常量元素和其他多元素摄入的评估结果, 为邯郸市居民谷物的健康风险评估和监管部门政策制定提供了数据支持。由于本研究膳食评估主要基于点评估, 评估的结果与人群谷物的摄入量、人群的体重指数和检测样品中该元素含量有着密切的关系[29], 本研究谷物摄入量和人群体重均采用人群平均数据, 评估结果可能与实际饮食摄入现状有一定的偏差[30]。其次, 本研究没有通过确定暴露的生物指标来评估食物摄入后微量元素的吸收程度, 有研究表明[31], 通过饮食摄入的多元素不会被人体全部吸收, 特别是在存在吸收不良疾病的情况下, 这些可能也会使得实际摄入量低于评估值; 最后由于某些元素不同价态毒性不同[3], 如无机砷和有机砷、六价铬和三价铬、有机汞和无机汞等, 由于研究条件的限制, 检测的是金属元素的总价态, 评估时采用比较严格的风险评估模式(即全部按照有害价态评估), 可能会使得整体评估结果高于实际风险值。在后续的研究中, 建议持续关注不同地区、年龄和性别人群中的谷物摄入量、不同年份和多产地谷物的多元素含量, 同时考虑不同元素的吸收摄入程度、不同元素价态的分型检测, 构建本地区谷物样品的风险数据库, 得到更精确的金属多元素评估结果。
基金
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  • 邯郸市科学技术研究与发展计划项目(23422083170)
文献
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2025年第16卷第15期
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20250422005
  • 接收时间：2025-04-22
  • 首发时间：2026-01-09
  • 出版时间：2025-08-15
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  • 收稿日期：2025-04-22
基金
邯郸市科学技术研究与发展计划项目(23422083170)
作者信息
    邯郸市疾病预防控制中心, 邯郸 056002

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*李伟昊(1976—), 男, 博士, 主任技师, 主要研究方向为食品安全。E-mail:
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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