Article(id=1153433639393157200, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153433633999282214, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20240918001, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1726588800000, receivedDateStr=2024-09-18, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1752929609391, onlineDateStr=2025-07-19, pubDate=1742832000000, pubDateStr=2025-03-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752929609391, onlineIssueDateStr=2025-07-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752929609391, creator=13701087609, updateTime=1752929609391, updator=13701087609, issue=Issue{id=1153433633999282214, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='6', 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=0, createTime=1752929608105, creator=13701087609, updateTime=1758086445549, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1175062977960096080, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153433633999282214, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1175062977960096081, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153433633999282214, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=76, endPage=82, ext={EN=ArticleExt(id=1153433640013914203, articleId=1153433639393157200, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Assessment of the health risks from dietary exposure to lead in Guangzhou in 2023, 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 extent of lead contamination in commercial foods and assess the health risk from dietary lead intake of the residents in Guangzhou in 2023. Methods In 2023, the 310 samples were collected from 3 food categories in 11 districts of Guangzhou, China. Lead was measured in the samples using inductively coupled plasma mass spectrometry. Dietary exposure to lead was calculated based on the food consumption survey of Guangzhou residents in 2011, and the health risk of the population was evaluated using the margin of exposure (MOE) method. Results Lead was detected in 83.23% of the overall samples, and the over-standard rate was 0%, with an average lead content of 0.040 mg/kg. The highest lead level was found in bivalves, 0.205 mg/kg. The average daily dietary lead exposure of the whole population and all age groups (3-6 years old, 7-17 years old, 18-59 years old, and 60 years old and above) in Guangzhou and the consumers with high dietary exposure of all age groups (95th percentile P95) were: 0.082, 0.120, 0.097, 0.078, 0.081 μg/(kg·d) and 0.225, 0.330, 0.268, 0.206, 0.226 μg/(kg·d). The contribution of rice and rice products, brassica vegetables, and leafy vegetables to dietary lead exposure was relatively significant. The MOE values for lead in residents of all age groups were greater than 1, with the MOE values for minors being lower than those for adults, particularly among high dietary exposure populations. Conclusion In 2023, there is a certain degree of lead contamination in the food items under close watch in the Guangzhou market. The average dietary lead exposure of residents of all age groups is within the acceptable range. However, it is still necessary to pay attention to key food items and take measures to reduce the dietary lead exposure risk for residents in Guangzhou.

, correspAuthors=Shao-Fang SONG, 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=Shao-Fang SONG, Yan LI, Wei-Wei ZHANG, Jin-Heng ZENG, Chen-Jia LI), CN=ArticleExt(id=1153433640299126889, articleId=1153433639393157200, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=2023年广州市售食品中铅污染状况及健康风险评估, columnId=1152687438456603210, journalTitle=食品安全质量检测学报, columnName=本期专题:食品安全风险评估与风险监测, runingTitle=null, highlight=null, articleAbstract=

目的 了解2023年广州市售食品中铅的污染程度, 并评估当地居民膳食铅摄入的健康风险。方法 2023年在广州市11个区采集了3类重点食品的310份样本并采用电感耦合等离子体质谱法进行铅检测。结合2011年广州市居民食物消费量数据, 计算膳食中铅的暴露量, 并采用暴露边际比(margin of exposure, MOE)对人群健康风险进行评估。结果 铅的总体检出率为83.23%, 超标率为0%, 铅含量平均值为0.040 mg/kg。其中双壳类食品的铅检测均值最高, 为0.205 mg/kg。广州市全人群及各年龄段(3~6岁、7~17岁、18~59岁和60岁及以上)每日膳食铅暴露量的平均值和各年龄段膳食高暴露消费者(第95百分位数P95)分别为: 0.082、0.120、0.097、0.078、0.081 μg/(kg·d)和0.225、0.330、0.268、0.206、0.226 μg/(kg·d)。米及米制品、芸薹类和叶菜类蔬菜对膳食铅暴露贡献比较大。各年龄段居民铅MOE值均大于1, 未成年人尤其膳食高暴露人群铅的MOE值小于成年人,。结论 2023年广州市市售重点关注食品存在一定的铅污染。各年龄段居民平均膳食铅暴露量在可接受范围内。但仍需要关注重点食品并采取措施减少广州市居民铅膳食暴露风险。

, correspAuthors=宋韶芳, authorNote=null, correspAuthorsNote=
* 宋韶芳(1977—), 女, 主任医师, 主要研究方向为食品安全风险评估。E-mail:
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Environmental and Occupational Medicine, 2018, 35(1): 73-77., articleTitle=Effects of combined exposure to lead and other heavy metals on neurodevelopment in children, refAbstract=null)], funds=[Fund(id=1175086594894737447, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433639393157200, awardId=2023A03J0450, language=CN, fundingSource=广州市科技计划项目(2023A03J0450), fundOrder=null, country=null), Fund(id=1175086595003789357, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433639393157200, awardId=20231A011068, language=CN, fundingSource=广州市卫生健康科技项目(20231A011068), fundOrder=null, country=null), Fund(id=1175086595100258349, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433639393157200, awardId=20251A011059, language=CN, fundingSource=广州市卫生健康科技项目(20251A011059), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1175086590528467913, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433639393157200, xref=null, ext=[AuthorCompanyExt(id=1175086590545245130, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433639393157200, companyId=1175086590528467913, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. Guangzhou Center for Disease Control and Prevention, Guangzhou 510440, China), AuthorCompanyExt(id=1175086590557828043, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433639393157200, companyId=1175086590528467913, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.广州市疾病预防控制中心, 广州 510440)]), AuthorCompany(id=1175086590629131212, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433639393157200, xref=null, ext=[AuthorCompanyExt(id=1175086590637519821, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433639393157200, companyId=1175086590629131212, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2. School of Public Health, Guangdong Medical University, Dongguan 523808, China), AuthorCompanyExt(id=1175086590645908430, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433639393157200, companyId=1175086590629131212, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.广东医科大学公共卫生学院, 东莞 523808)])], figs=[ArticleFig(id=1175086593846161422, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433639393157200, language=EN, label=Table 1, caption=

Monitoring of lead in food sold in Guangzhou in 2023

, figureFileSmall=null, figureFileBig=null, tableContent=
食品种类 食品类别 食品名称 标准限量/(mg/kg) 样品数
/份
检出值范围
/(mg/kg)
均值
/(mg/kg)
P50
/(mg/kg)
P95
/(mg/kg)
检出率
/%(检出数)
超标率
/%(超标数)
谷物及其制品 谷物碾磨
加工品
米及米制品 ≤0.2 110 ND~0.044 0.021 0.028 0.038 88.18 (97) 0 (0)
水产品及其
制品
甲壳类 淡水虾 ≤0.5 50 ND~0.046 0.011 0.009 0.028 60.00 (30) 0 (0)
淡水蟹 ≤0.5 30 0.017~0.142 0.044 0.042 0.100. 100.00 (30) 0 (0)
海水蟹 ≤0.5 30 0.009~0.174 0.045 0.040 0.094 96.67 (29) 0 (0)
软体类 双壳类 ≤1.5 30 0.003~0.690 0.205 0.145 0.519 100.00 (30) 0 (0)
腹足类 ≤1.0 30 0.003~0.037 0.014 0.012 0.024 100.00 (30) 0 (0)
蔬菜及其制品 新鲜蔬菜 芸薹类和叶菜类 ≤0.3 19 ND~0.018 0.006 0.004 0.015 57.89 (11) 0 (0)
茄果、瓜
菜类
≤0.1 11 ND~0.019 0.004 - 0.011 9.09 (1) 0 (0)
合计 310 ND~0.690 0.040 0.019 0.158 83.23 (258) 0 (0)
), ArticleFig(id=1175086593959407633, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433639393157200, language=CN, label=表1, caption=

2023年广州市售食品中铅的监测情况

, figureFileSmall=null, figureFileBig=null, tableContent=
食品种类 食品类别 食品名称 标准限量/(mg/kg) 样品数
/份
检出值范围
/(mg/kg)
均值
/(mg/kg)
P50
/(mg/kg)
P95
/(mg/kg)
检出率
/%(检出数)
超标率
/%(超标数)
谷物及其制品 谷物碾磨
加工品
米及米制品 ≤0.2 110 ND~0.044 0.021 0.028 0.038 88.18 (97) 0 (0)
水产品及其
制品
甲壳类 淡水虾 ≤0.5 50 ND~0.046 0.011 0.009 0.028 60.00 (30) 0 (0)
淡水蟹 ≤0.5 30 0.017~0.142 0.044 0.042 0.100. 100.00 (30) 0 (0)
海水蟹 ≤0.5 30 0.009~0.174 0.045 0.040 0.094 96.67 (29) 0 (0)
软体类 双壳类 ≤1.5 30 0.003~0.690 0.205 0.145 0.519 100.00 (30) 0 (0)
腹足类 ≤1.0 30 0.003~0.037 0.014 0.012 0.024 100.00 (30) 0 (0)
蔬菜及其制品 新鲜蔬菜 芸薹类和叶菜类 ≤0.3 19 ND~0.018 0.006 0.004 0.015 57.89 (11) 0 (0)
茄果、瓜
菜类
≤0.1 11 ND~0.019 0.004 - 0.011 9.09 (1) 0 (0)
合计 310 ND~0.690 0.040 0.019 0.158 83.23 (258) 0 (0)
), ArticleFig(id=1175086594081042451, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433639393157200, language=EN, label=Table 2, caption=

Estimated dietary exposure of lead (mean and P95) and constituent ratio in different age groups in Guangzhou in 2023

, figureFileSmall=null, figureFileBig=null, tableContent=
食品类别 3~6岁 7~17岁 18~59岁 ≥60岁 全人群
均值 P95 贡献率 均值 P95 贡献率 均值 P95 贡献率 均值 P95 贡献率 均值 P95 贡献率
米及米制品 0.083 0.177 68.56 0.064 0.140 65.85 0.051 0.108 65.70 0.052 0.102 64.50 0.054 0.117 65.84
甲壳类 0.005 0.040 3.74 0.004 0.025 3.80 0.003 0.020 4.04 0.003 0.022 4.16 0.003 0.021 3.95
软体类 0.004 0.037 3.66 0.005 0.046 5.40 0.004 0.031 5.17 0.004 0.048 5.01 0.004 0.035 5.08
芸薹类和叶菜类 0.019 0.050 16.05 0.016 0.038 17.03 0.013 0.030 16.85 0.014 0.035 17.94 0.014 0.034 16.93
茄果、瓜菜类 0.010 0.026 7.99 0.008 0.020 7.92 0.006 0.017 8.25 0.007 0.019 8.40 0.007 0.018 8.20
合计 0.120 0.330 100.00 0.097 0.268 100.00 0.078 0.206 100.00 0.081 0.226 100.00 0.082 0.225 100.00
), ArticleFig(id=1175086594492084252, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433639393157200, language=CN, label=表2, caption=

2023年广州不同年龄人群每日膳食中铅暴露(均值和P95)及各类食品的贡献率

, figureFileSmall=null, figureFileBig=null, tableContent=
食品类别 3~6岁 7~17岁 18~59岁 ≥60岁 全人群
均值 P95 贡献率 均值 P95 贡献率 均值 P95 贡献率 均值 P95 贡献率 均值 P95 贡献率
米及米制品 0.083 0.177 68.56 0.064 0.140 65.85 0.051 0.108 65.70 0.052 0.102 64.50 0.054 0.117 65.84
甲壳类 0.005 0.040 3.74 0.004 0.025 3.80 0.003 0.020 4.04 0.003 0.022 4.16 0.003 0.021 3.95
软体类 0.004 0.037 3.66 0.005 0.046 5.40 0.004 0.031 5.17 0.004 0.048 5.01 0.004 0.035 5.08
芸薹类和叶菜类 0.019 0.050 16.05 0.016 0.038 17.03 0.013 0.030 16.85 0.014 0.035 17.94 0.014 0.034 16.93
茄果、瓜菜类 0.010 0.026 7.99 0.008 0.020 7.92 0.006 0.017 8.25 0.007 0.019 8.40 0.007 0.018 8.20
合计 0.120 0.330 100.00 0.097 0.268 100.00 0.078 0.206 100.00 0.081 0.226 100.00 0.082 0.225 100.00
), ArticleFig(id=1175086594626301982, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433639393157200, language=EN, label=Table 3, caption=

MOE based risk characterization of dietary lead exposure residents at varying ages in Guangzhou in 2023

, figureFileSmall=null, figureFileBig=null, tableContent=
食品类别 3~6岁 7~17岁 18~59岁 60岁及以上 全人群
均值 P95 均值 P95 均值 P95 均值 P95 均值 P95
米及米制品 7.27 3.39 9.42 4.30 23.40 11.10 23.09 11.72 22.13 10.25
甲壳类 133.33 14.98 163.27 24.02 380.95 60.00 358.21 54.92 369.12 57.49
软体类 136.36 16.28 114.83 13.06 297.52 38.73 297.52 25.17 286.91 34.36
芸薹类和叶菜类 31.06 12.00 36.43 16.00 91.25 39.89 82.99 34.29 86.09 35.30
茄果、瓜菜类 62.37 23.49 78.33 29.96 186.34 72.14 177.34 63.20 177.70 66.67
合计 4.98 1.82 6.20 2.24 15.38 5.83 14.89 5.31 14.57 5.34
), ArticleFig(id=1175086594756325411, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433639393157200, language=CN, label=表3, caption=

2023年广州市各年龄段居民膳食铅暴露的MOE

, figureFileSmall=null, figureFileBig=null, tableContent=
食品类别 3~6岁 7~17岁 18~59岁 60岁及以上 全人群
均值 P95 均值 P95 均值 P95 均值 P95 均值 P95
米及米制品 7.27 3.39 9.42 4.30 23.40 11.10 23.09 11.72 22.13 10.25
甲壳类 133.33 14.98 163.27 24.02 380.95 60.00 358.21 54.92 369.12 57.49
软体类 136.36 16.28 114.83 13.06 297.52 38.73 297.52 25.17 286.91 34.36
芸薹类和叶菜类 31.06 12.00 36.43 16.00 91.25 39.89 82.99 34.29 86.09 35.30
茄果、瓜菜类 62.37 23.49 78.33 29.96 186.34 72.14 177.34 63.20 177.70 66.67
合计 4.98 1.82 6.20 2.24 15.38 5.83 14.89 5.31 14.57 5.34
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2023年广州市售食品中铅污染状况及健康风险评估
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宋韶芳 1, * , 李燕 1 , 张维蔚 1 , 曾锦衡 1 , 李陈佳 2
食品安全质量检测学报 | 本期专题:食品安全风险评估与风险监测 2025,16(6): 76-82
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食品安全质量检测学报 | 本期专题:食品安全风险评估与风险监测 2025, 16(6): 76-82
2023年广州市售食品中铅污染状况及健康风险评估
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宋韶芳1, * , 李燕1, 张维蔚1, 曾锦衡1, 李陈佳2
作者信息
  • 1.广州市疾病预防控制中心, 广州 510440
  • 2.广东医科大学公共卫生学院, 东莞 523808

通讯作者:

* 宋韶芳(1977—), 女, 主任医师, 主要研究方向为食品安全风险评估。E-mail:
Assessment of the health risks from dietary exposure to lead in Guangzhou in 2023
Shao-Fang SONG1, * , Yan LI1, Wei-Wei ZHANG1, Jin-Heng ZENG1, Chen-Jia LI2
Affiliations
  • 1. Guangzhou Center for Disease Control and Prevention, Guangzhou 510440, China
  • 2. School of Public Health, Guangdong Medical University, Dongguan 523808, China
出版时间: 2025-03-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20240918001
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目的 了解2023年广州市售食品中铅的污染程度, 并评估当地居民膳食铅摄入的健康风险。方法 2023年在广州市11个区采集了3类重点食品的310份样本并采用电感耦合等离子体质谱法进行铅检测。结合2011年广州市居民食物消费量数据, 计算膳食中铅的暴露量, 并采用暴露边际比(margin of exposure, MOE)对人群健康风险进行评估。结果 铅的总体检出率为83.23%, 超标率为0%, 铅含量平均值为0.040 mg/kg。其中双壳类食品的铅检测均值最高, 为0.205 mg/kg。广州市全人群及各年龄段(3~6岁、7~17岁、18~59岁和60岁及以上)每日膳食铅暴露量的平均值和各年龄段膳食高暴露消费者(第95百分位数P95)分别为: 0.082、0.120、0.097、0.078、0.081 μg/(kg·d)和0.225、0.330、0.268、0.206、0.226 μg/(kg·d)。米及米制品、芸薹类和叶菜类蔬菜对膳食铅暴露贡献比较大。各年龄段居民铅MOE值均大于1, 未成年人尤其膳食高暴露人群铅的MOE值小于成年人,。结论 2023年广州市市售重点关注食品存在一定的铅污染。各年龄段居民平均膳食铅暴露量在可接受范围内。但仍需要关注重点食品并采取措施减少广州市居民铅膳食暴露风险。

铅  /  膳食暴露  /  暴露边际比  /  风险评估

Objective To investigate the extent of lead contamination in commercial foods and assess the health risk from dietary lead intake of the residents in Guangzhou in 2023. Methods In 2023, the 310 samples were collected from 3 food categories in 11 districts of Guangzhou, China. Lead was measured in the samples using inductively coupled plasma mass spectrometry. Dietary exposure to lead was calculated based on the food consumption survey of Guangzhou residents in 2011, and the health risk of the population was evaluated using the margin of exposure (MOE) method. Results Lead was detected in 83.23% of the overall samples, and the over-standard rate was 0%, with an average lead content of 0.040 mg/kg. The highest lead level was found in bivalves, 0.205 mg/kg. The average daily dietary lead exposure of the whole population and all age groups (3-6 years old, 7-17 years old, 18-59 years old, and 60 years old and above) in Guangzhou and the consumers with high dietary exposure of all age groups (95th percentile P95) were: 0.082, 0.120, 0.097, 0.078, 0.081 μg/(kg·d) and 0.225, 0.330, 0.268, 0.206, 0.226 μg/(kg·d). The contribution of rice and rice products, brassica vegetables, and leafy vegetables to dietary lead exposure was relatively significant. The MOE values for lead in residents of all age groups were greater than 1, with the MOE values for minors being lower than those for adults, particularly among high dietary exposure populations. Conclusion In 2023, there is a certain degree of lead contamination in the food items under close watch in the Guangzhou market. The average dietary lead exposure of residents of all age groups is within the acceptable range. However, it is still necessary to pay attention to key food items and take measures to reduce the dietary lead exposure risk for residents in Guangzhou.

lead  /  dietary exposure  /  margin of exposure  /  risk assessment
宋韶芳, 李燕, 张维蔚, 曾锦衡, 李陈佳. 2023年广州市售食品中铅污染状况及健康风险评估. 食品安全质量检测学报, 2025 , 16 (6) : 76 -82 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20240918001
Shao-Fang SONG, Yan LI, Wei-Wei ZHANG, Jin-Heng ZENG, Chen-Jia LI. Assessment of the health risks from dietary exposure to lead in Guangzhou in 2023[J]. Journal of Food Safety & Quality, 2025 , 16 (6) : 76 -82 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20240918001
铅是一种在自然界中广泛分布的重金属, 它可以通过人为活动如采矿、冶金、印刷等, 以各种形式排放到环境中。铅通过直接吸入、皮肤接触和饮食等途径进入人体, 其中食物摄入是非职业暴露个体慢性暴露的主要途径[1]。铅在人体中具有蓄积性, 半衰期长达10到30年, 长期铅暴露可对神经、心血管和肾脏等系统造成累积危害[2-3], 对儿童的神经发育尤其有害[4], 且由铅带来的神经损伤导致的行为影响具有不可逆性[5-6]。铅通过受污染的土壤、水、空气及食品生产过程中使用的金属设备、食品包装材料和含铅食品添加剂导致食品铅污染[7], 铅的膳食暴露一直是研究热点。李明璐等[8]收集2012—2021年中国19个省份的31008份膳食铅含量数据发现, 铅浓度排名前3的食物为食用菌类(0.13 mg/kg), 蛋类(0.11 mg/kg), 鱼虾蟹贝类(0.08 mg/kg); 中国成人膳食铅的70%以上是来源于谷物及其制品[0.39 μg/(kg·d)], 蔬菜类[0.22 μg/(kg·d)], 畜禽肉类[0.08 μg/(kg·d)]; 中国成人平均暴露量为1.05 μg/(kg·d)。2017年巴基斯坦的蔬菜、水果和谷类作物中潜在有毒金属的水平和健康风险评估[9]结果显示, 该成人人群的每日铅摄入量为1.65 μg/(kg·d), 高于中国成人人群。MARCELLA等[10]收集意大利2016—2017年908份食品样品检测铅含量, 含铅量最高的食物包括叶类(39.0 μg/kg)和其他蔬菜(42.2 μg/kg), 以及甲壳类和软体动物(39.0 μg/kg); 人群平均铅摄入量为0.155 μg/(kg·d)。蔡文华等[11]在2007—2014年采集广东市售的谷物及其制品、蔬菜、水产品等5640份食品样品铅的暴露情况进行分析评价, 铅的超标率为5.7%, 均值为0.104 mg/kg。采用暴露边界比(margin of exposure, MOE)方法来评估铅膳食暴露风险发现叶菜、芸薹类蔬菜、软体类水产品、大米及其制品的MOE值比较低, 分别为2.46、3.80、4.01。WANG等[12]在2014—2017年收集广州市售食品6339份, 铅的检出率是71.6%, 铅含量均值为0.0433 mg/kg, 米及米制品、叶菜类蔬菜对广州市居民铅暴露贡献率最大, 贡献率分别为21.42%, 20.01%。并发现其对幼儿和铅的膳食高暴露者构成高风险(MOE值小于1)。张玉华等[13]对2017—2019年广州市售食品3130份进行铅含量分析发现, 铅的检出率是82.11%, 超标率为0.13%, 铅含量均值为0.031 mg/kg, 双壳类水产品的铅含量均值最高为0.156 mg/kg; 芸薹类和叶菜蔬菜、米及米制品对广州市居民铅暴露贡献率最大, 贡献率分别为21.07%、19.90%。对未成年人膳食高暴露者构成高风险(MOE值小于1)。
鉴于近年来广州市市售食品中铅的检出情况[12-13]及铅对膳食高暴露人群的健康风险, 有必要持续开展重点食物中铅污染监测工作。2023年本中心开展与居民最密切相关的谷物及其制品、水产品及其制品、蔬菜及其制品共3类重点食品的监测工作, 结合查阅文献[14], 本研究将对2023年广州市重点食品中铅的暴露情况进行分析, 结合广州市各年龄段居民食物消费量数据, 对广州市居民膳食铅暴露进行健康风险评估, 以期为监督部门制定措施减少食品中铅的污染, 降低居民铅膳食暴露风险提供科学依据。
采用分层抽样的方法, 在广州市11个行政区分别随机抽取3条街道, 按街道类型进行分层, 共有33条街道(22条中心街道和11条外围街道)被确定为食品采样点。以消费者购买的方式采集市售食品样品, 采样场所覆盖农贸市场、批发市场、超市、零售店和餐饮单位等, 样品包括米及米制品; 淡水虾、淡水蟹、海水蟹、双壳类、腹足类等水产品; 芸薹类和叶菜类、茄果、瓜菜类等新鲜蔬菜, 共采集310份样品。样品采集后迅速冷藏半小时内运至实验室, 表面清洗, 在-20 ℃的冰柜内保存待检测。
国家一级标准铅材料(GBW10035)、小麦粉中铅标准物质[(1630±30) µg/kg](中国地理科学研究院); 纯水(杭州娃哈哈公司); 硝酸(纯度69%, 北京化学试剂研究所有限责任公司)。
Sartorius BSA224S电子分析天平(精度0.1 mg, 德国Sartorius集团); ETHOS ONE微波消解仪(意大利MILESTONE公司); ICP-MS 7700电感耦合等离子质谱仪(美国Agilent Technologies公司)。
根据GB 5009.268—2016《食品安全国家标准 食品中多元素的测定》, 本研究采用电感耦合等离子体质谱法测定样品中的铅含量, 铅的检出限为0.003 mg/kg。实验采用标准样品、空白试验、平行双样测定、加标回收等方法进行质控。检测结果根据GB 2762—2022《食品安全国家标准 食品中污染物限量》进行评价。
采用2011年广州市居民食物消费状况调查数据[12,15], 从中选取不同年龄段人群各类食品的消费数据进行膳食暴露量计算。
根据广州市售食品中铅含量数据和不同年龄段居民各类食品的消费量数据, 计算得出各年龄段居民每日每公斤体重的铅暴露量(Dig), 计算公式[16]如公式(1):
Dig=Ci×DC/BW
式中: Dig为铅经口途径的单位体重日均暴露量, μg/(kg·d); Ci为第i种食品中铅检测值, mg/kg, 取检测值的均值; DC为对应的食品标准人每日消费量, g/d, BW为体重, kg, 3~6岁、7~17岁、18~59岁和60岁及以上人群分别以体重20、40、62、60 kg计。膳食高暴露消费者P95的DC取值为膳食摄取量的P95
某类食品的膳食贡献率计算如公式(2)。
某类食品贡献率/%=(某类食品中铅暴露量/各类食品铅暴露量之和)×100%
2010年, 联合国粮农组织/世界卫生组织(Food and Agriculture Organization of the United Nations/World Health Organization, FAO/WHO)食品添加剂联合专家委员会(Joint Expert Committee on Food Additives, JECFA)撤销了之前制定的铅的健康指导值暂定每周耐受摄入量(provisional tolerable weekly intake, PTWI) 25 μg/kg, 目前尚无法确定一个不会带来有害影响的铅暴露水平[17]。由于铅没有健康指导值, 本研究采用暴露边界比MOE方法[17]来评估铅膳食暴露风险, 它既考虑了铅的膳食暴露, 也考虑了剂量-反应的关系, 是一种合理并且实用的健康风险评估方法。
MOE计算如公式(3):
MOE=基准剂量下限值/暴露量
式中: 基准剂量下限值(benchmark dose lower confidence limit, BMDL)为剂量-反应曲线上的参考点。以儿童智商(intelligence quotient, IQ)降低和成年人收缩压升高作为效应终点, 对于儿童, 当铅暴露量为0.6 μg/kg时, IQ将降低1分; 对于成人, 当暴露量为1.2 μg/kg时, 收缩压将上升1 mmHg[18]。因此认为铅暴露不良效应的儿童BMDL为0.6 μg/kg, 成人为1.2 μg/kg。MOE值越大, 表示健康风险越低。当MOE>1时, 健康风险相对较低; 当MOE≤1时, 存在一定的健康风险。
将样品信息和检测数据录入Excel 2010, 利用SPSS 22.0进行统计分析, 采用均值对各类食品中的铅检测数据进行统计描述, 并计算检出率和超标率。比较铅检测值在不同种类的食品的差别有无统计学意义采用Mann-Whitney检验, 以P<0.05为差异有统计学意义。
对于低于检出限(limit of detection, LOD)的数据, 当铅含量低于LOD且未检出率<60%时, 采用WHO推荐的替代法进行处理, 将未检出值用1/2 LOD值进行替换[19]
2023年共监测重点关注食品: 谷物及其制品、水产品及其制品、蔬菜及其制品310份食品样品, 铅的总体检出率为83.23% (258/310), 超标率为0%, 铅检测值均值为0.040 mg/kg。水产品的铅检出率为87.64% (149/170); 米及米制品的铅检出率为88.18% (97/170); 蔬菜的铅检出率为40.00% (12/30)。这3大类食品中水产品的铅检测值最高, 其均值为0.057 mg/kg; 其次是米及米制品, 铅检测均值为0.021 mg/kg; 再次是蔬菜, 铅检测均值为0.005 mg/kg, 这3大类食品中铅的检出率和检测值是有差别的。各类食品中铅检测均值最高的是双壳类0.205 mg/kg, 其次是海水蟹0.045 mg/kg, 再次是淡水蟹0.044 mg/kg。双壳类铅的检出值与其他水产品有差别, 而海水蟹和谈水蟹铅的检出值基本没差别, 详见表1
与广州市往年的监测报告[12-13]相比, 广州市市售食品中的铅检测值有下降趋势, 也低于广东省2007—2014年[11]和深圳市2009—2015年[20]监测结果, 这下降趋势反映了政府为减少铅暴露和食品污染所采取的一系列措施的成功, 例如使用无铅汽油, 污水处理等。
各类食品中, 双壳类铅的检出率100.00%, 并且铅的检测均值最高, 这和之前的监测报告的结果是一致的[13]。在水产品中, 双壳类动物或螃蟹等底栖生物的铅检测值较高[12,21]。可能是由于废弃物往江河海洋倾倒和沉积, 导致水域生态系统受到持续的重金属污染[21]。双壳类的铅检测值较高, 还可能与双壳类滤食特性, 蓄积重金属污染物的能力较强有关[22]
根据重点食品中铅的平均检测值和广州市不同年龄段居民各类食物消费量的均数及P95, 计算不同年龄段人群膳食铅暴露量。铅摄入量的P95反映了膳食高暴露消费者的铅暴露水平[13]。结果显示, 广州市全人群平均膳食铅暴露量和膳食高暴露消费者暴露量分别是0.082 μg/(kg·d)、0.225 μg/(kg·d)。3~6岁、7~17岁、18~59岁和60岁及以上人群每日通过膳食摄入铅的平均暴露量分别为0.120、0.097、0.078、0.081 μg/(kg·d), 各年龄段居民的膳食铅日均暴露量有随年龄增大下降的趋势。各年龄段膳食高暴露消费者通过重点食品对铅的暴露量分别为0.330、0.268、0.206和0.226 μg/(kg·d)。各年龄段高暴露消费者对铅的暴露量有随年龄增大下降的趋势。米及米制品、芸薹类和叶菜类对全人群的铅暴露量献率较大, 详见表2
广州市居民铅日均暴露量低于我国成人膳食铅日均暴露量1.05 μg/kg[8]。这一结果, 可能与广州市食品中铅本底含量较低、污染相对较轻或膳食数据差异性有关。米及米制品对广州市居民膳食铅暴露的贡献率大于芸薹类和叶菜类, 与陕西[23]、厦门[24]等地的结果相似。但与惠州[25]、上海[26]研究结果稍有出入, 这些城市的铅膳食暴露主要来源于蔬菜、粮谷和水产类, 但蔬菜的贡献率要大于粮谷类, 这可能与不同地区的膳食结构差异有关。
根据儿童和成人的BMDL和各年龄段铅摄入量的均值和高暴露消费者铅摄入量进行广州市居民重点食品的膳食铅暴露评估, 计算出各年龄段膳食铅暴露的MOE值。3~6岁、7~17岁、18~59岁和60岁及以上人群膳食铅暴露的MOE均值均大于1, 并且MOE值有随着年龄的增长而增大的趋势; 3~6岁、7~17岁、18~59岁和60岁及以上高膳食暴露人群的铅暴露MOE值均大于1, 并且MOE值有随着年龄的增长而增大的趋势, 详见表3。说明广州市居民膳食铅暴露的健康风险在可接受范围内, 风险有随年龄增大而下降的趋势, 膳食高暴露人群的铅暴露风险要比平均水平高, 尤其是3~6岁和7~17岁高暴露消费者。其原因可能是3~6岁和7~17岁这两个年龄段人群由于体重较轻, 以及相对较高的膳食摄入量, 导致膳食风险高于其他年龄段人群。
MAO等[27]在中国成年人群中进行的膳食铅暴露评估报告了平均膳食铅暴露的MOE值为2.41。陕西成人铅暴露的MOE值为1.89[23]。惠州成年居民铅暴露的MOE值为3.52[25]。杭州成人铅暴露的MOE值为7.46[28]。成年意大利人的铅暴露MOE值为7.7[10]。由于较高的MOE值表明暴露的健康风险较低, 因此广州成人在重点关注食品的铅暴露的健康风险总体上低于上述城市的平均水平。张玉华等[13]报道的2017—2019年广州市居民各年龄组铅MOE值高于WANG等[12]报道的2014—2017年广州市居民各年龄组铅MOE值, 在本研究中, 所有年龄组的MOE值都高于上述研究, 说明这是有可能是由于食品中的铅含量下降引起的广州市居民膳食铅摄入的健康风险的下降趋势; 也有可能是本次研究只关注了广州市重点食品, 未包括所有含铅的食品, 从某种程度上低估了人群的铅摄入导致铅膳食暴露风险评估不够全面。
2023年广州市重点关注食品中铅的检出率是83.23%, 含量均值为0.040 mg/kg, 超标率为0%。各类食品中, 水产品铅的检测值比较高, 尤其双壳类食品铅的检出率为100.00%, 检测均值最高, 为0.205 mg/kg, 并且铅检测值最高为0.690 mg/kg。由于广州属于沿海城市, 水产养殖业发达, 当地居民容易获得丰富的水产品, 对这部分食品的消费量不容小觑, 铅在该类食品中的残留量需要引起重视。部分大米、蔬菜等农作物检测出一定量的铅, 可能是肥料、农药、灌溉或周围环境受到了污染; 芸薹类和叶菜类蔬菜, 由于叶子宽大, 易集聚空气中的微小颗粒, 铅的检出率和检测值会比茄果、瓜菜类高。
广州市居民铅日均暴露量为0.225 μg/(kg·d), 重点食品中, 对各年龄段膳食铅暴露贡献较大的是米及米制品、芸薹类和叶菜类。由于当地居民对食物的选择受到当地食品生产、食品加工和贸易、饮食习惯和其他因素的影响[29]。而中国南方盛产水稻, 广州市居民更容易获得大米作为主食, 米及米制品位居广州市居民膳食消费的首位。广州市居民膳食富有岭南特色, 比较喜好进食绿色叶菜, 芸薹类和叶菜类的每日消费量仅次于大米[12,20]。膳食铅的暴露不仅取决于食品中的铅含量, 也和食品消费量有关。由于米及米制品、芸薹类和叶菜类在广州居民膳食消费较大, 故铅膳食暴露也比较大。因此, 不同食物类别对膳食铅风险的贡献因地区而异[30-31]。因此, 加强重点食品监管, 控制其铅含量, 可显著减少广州市居民膳食铅暴露量。
基于MOE评价标准表明, 广州市居民对重点关注食品的铅暴露健康风险在可接受范围内, 风险有随年龄增大而下降的趋势, 膳食高暴露人群的铅暴露风险要比平均水平高, 尤其是未成年人的膳食高暴露者健康风险比较高。常吃受铅污染的食品, 铅能通过食品进入人体, 具有蓄积性, 较难除去; 较低浓度也具有毒性, 可造成多个器官的损害[2-3], 从而危害人体健康, 尤其中枢神经系统, 特别是正在发育中的大脑, 是人类铅毒性最突出和最敏感的靶标系统[32]。而未成年人的神经系统处于发育阶段, 对铅等重金属的神经毒性更为敏感, 且可能与其他重金属产生交互效应, 对神经行为产生不良影响[33], 需引起重点关注。因此广州市膳食铅暴露问题不容忽视, 相关部门应该积极行动起来, 加强重点食物监管力度, 减少食物铅污染, 防止铅超标食品流入市场。
本研究采用了“点评估”的方法和MOE值对广州市重点食品进行铅暴露风险评估, 未包括所有含铅的食品, 也未考虑由空气、皮肤、吸入等其他途径摄入的铅, 从某种程度上低估了人群的铅摄入。此外, 本研究所采用的消费量数据来自2011年广州市居民食物消费状况调查, 当今居民的饮食结构和2011年相比可能有变化, 因此评估具有不确定性。
广州市市售重点关注食品存在一定的铅污染, 其中双壳类食品铅检测均值最高。米及米制品、芸薹类和叶菜类蔬菜铅膳食暴露贡献比较大。采用MOE法进行风险评估, 各年龄段居民铅膳食暴露风险比较低, 在可接受范围内。未成年人铅膳食暴露风险比成年人高, 尤其膳食高暴露人群。仍需重点关注食品中铅污染, 并采取措施以降低广州市居民铅膳食暴露风险。
  • 广州市科技计划项目(2023A03J0450)
  • 广州市卫生健康科技项目(20231A011068)
  • 广州市卫生健康科技项目(20251A011059)
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20240918001
  • 接收时间:2024-09-18
  • 首发时间:2025-07-19
  • 出版时间:2025-03-25
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  • 收稿日期:2024-09-18
基金
广州市科技计划项目(2023A03J0450)
广州市卫生健康科技项目(20231A011068)
广州市卫生健康科技项目(20251A011059)
作者信息
    1.广州市疾病预防控制中心, 广州 510440
    2.广东医科大学公共卫生学院, 东莞 523808

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* 宋韶芳(1977—), 女, 主任医师, 主要研究方向为食品安全风险评估。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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