中国两省市空气细颗粒物暴露对小学生血脂异常的影响

朱元多; 韩盈盈; 李丹丹; 张经纬; 徐艳龙

doi:10.16835/j.cnki.1000-9817.2025032

中国两省市空气细颗粒物暴露对小学生血脂异常的影响

doi: 10.16835/j.cnki.1000-9817.2025032

1.
中国疾病预防控制中心环境与健康相关产品安全所环境流行病学室，北京 100050
2.
北京市丰台区疾病预防控制中心环境卫生科
3.
天津市疾病预防控制中心环境健康与公共卫生所
4.
安徽省疾病预防控制中心环境卫生科

基金项目:

国家自然科学基金项目 82103871

详细信息

作者简介:
朱元多(1989-)，女，安徽淮南人，博士，副研究员，主要研究方向为生命早期环境暴露对儿童发育的影响

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中图分类号: R179 R446.11⁺² R122.2
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出版历程
- 收稿日期: 2024-09-12
- 修回日期: 2024-12-03
- 刊出日期: 2025-01-25

Effect of fine particulate matter exposure in the air on dyslipidemia among primary school students in two provinces and cities of China

1.
Division of Environmental Epidemiology, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing (100050), China

摘要

摘要: 目的分析空气细颗粒物(PM_2.5)暴露与小学生血脂水平之间的关联，为儿童慢性病预防与控制提供证据支持。方法 2024年5—6月，采用随机抽样方法抽取安徽省和天津市2所小学625名小学生进行体格检查和生化检查。根据家庭住址，获取调查前3年、调查前2年及过去1年PM_2.5年平均暴露水平。采集空腹血用于总胆固醇、三酰甘油(TG)、高密度脂蛋白胆固醇、低密度脂蛋白胆固醇的检测。采用线性回归模型、二元Logisitic回归模型分析PM_2.5暴露与小学生血脂指标及血脂异常的关联性。结果小学生血脂异常检出率为14.72%。线性回归分析显示，调查前1年、调查前2年、调查前3年PM_2.5每增加1 μg/m³，小学生TG分别增加0.019(95%CI=0.012~0.025)，0.023(95%CI=0.016~0.030)，0.021(95%CI=0.014~0.027)mmol/L；二元Logisitic回归分析结果显示，小学生血脂异常发生风险与调查前1年、调查前2年、调查前3年PM_2.5质量浓度均呈正相关[OR值(95%CI)=1.06(1.02~1.11)，1.06(1.01~1.12)，1.06(1.01~1.11)](P值均 < 0.05)。结论 PM_2.5暴露与小学生血脂异常发生风险增加有关。应采取综合防治措施提升空气质量，以保护小学生的健康。
- 颗粒物 /
- 血脂异常 /
- 回归分析 /
- 学生
Abstract: Objective To analyze the association between fine particulate matter (PM_2.5) exposure in the air and dyslipidemia among primary school students, in order to provide the evidence-based support for the prevention and control of chronic diseases in children. Methods The random sampling method was used to select 625 students from two primary schools in Anhui Province and Tianjin City from May to June 2024. Based on the home address, the annual average exposure levels of PM_2.5 were obtained in 3 years before investigation, 2 years before investigation, and the past year before investigation. Fasting blood samples were collected for the detection of total cholesterol, triglycerides (TG), high-density lipoprotein cholesterol and low-density lipoprotein cholesterol. Linear regression modeling was used to analyze the association between PM_2.5 exposure and dyslipidemia among primary school students. Results The rate of dyslipidemia among primary school students was 14.72% in the present study. The results of linear regression analysis showed that the TG increased by 0.019(95%CI=0.012-0.025), 0.023(95%CI=0.016-0.030) and 0.021(95%CI=0.014-0.027) mmol/L for every 1 μg/m³ increase of PM_2.5 in the past year before investigation, 2 years before investigation and 3 years before investigation respectively (P < 0.05). The results of binary Logisitic analysis showed that the risks of dyslipidemia in primary school students were positively correlated with PM_2.5 mass concentration in the past year before investigation, 2 years before investigation, and 3 years before investigation [OR(95%CI)=1.06(1.02-1.11), 1.06(1.01-1.12), 1.06(1.01-1.11), P < 0.05]. Conclusions PM_2.5 exposure is associated with increased risk of dyslipidemia among primary school students. To protect the health of primary school students, effective measures should be taken to improve air quality.
- Particulate matter /
- Dyslipidemia /
- Regression analysis /
- Students
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表 1 PM_2.5暴露水平与小学生血脂水平关联的线性回归分析[β值(95%CI)，n=625]

Table 1. Linear regression analysis of associations between PM_2.5 exposure levels and serum lipid levels in primary students[β(95%CI), n=625]

模型	PM_2.5质量浓度	TC	TG	HDL-C	LDL-C
1	lag 1	0(-0.009~0.009)	0.020(0.014~0.026)^*	-0.003(-0.007~0.001)	-0.001(-0.008~0.007)
	lag 2	-0.007(-0.017~0.002)	0.025(0.018~0.032)^*	-0.003(-0.007~0.002)	-0.007(-0.015~0.001)
	lag 3	-0.004(-0.013~0.005)	0.022(0.016~0.029)^*	-0.002(-0.006~0.002)	-0.004(-0.011~0.003)
2	lag 1	0.001(-0.009~0.010)	0.019(0.012~0.025)^*	-0.003(-0.007~0.001)	0(-0.007~0.007)
	lag 2	-0.002(-0.012~0.009)	0.023(0.016~0.030)^*	-0.003(-0.007~0.002)	-0.002(-0.011~0.006)
	lag 3	0(-0.009~0.010)	0.021(0.014~0.027)^*	-0.002(-0.006~0.002)	-0.001(-0.008~0.007)
注：模型1未调整；模型2调整因素包括年龄、性别、民族、BMI、体力活动、家庭年均收入、被动吸烟、独生子女；^*P < 0.05。

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表 2 PM_2.5暴露水平与小学生血脂异常关联的二元Logistic回归分析[OR值(95%CI), n=625]

Table 2. Binary Logistic regression analysis of the association between PM_2.5 exposure levels and dyslipidemia in primary school students[OR值(95%CI), n=625]

模型	PM_2.5质量浓度	高TC血症	高TG血症	低HDL-C血症	高HDL-C血症	血脂异常
1	lag 1	1.01(0.95~1.07)	1.09(1.02~1.15)^*	1.10(1.02~1.18)^*	1.03(0.95~1.12)	1.06(1.02~1.10)^*
	lag 2	1.00(0.94~1.06)	1.10(1.03~1.18)^*	1.04(0.97~1.11)	1.00(0.91~1.09)	1.04(1.00~1.09)^*
	lag 3	1.01(0.95~1.07)	1.09(1.02~1.16)^*	1.04(0.97~1.10)	1.02(0.93~1.10)	1.04(1.00~1.08)^*
2	lag 1	1.02(0.96~1.08)	1.10(1.06~1.18)^*	1.10(1.02~1.18)^*	1.05(0.96~1.14)	1.06(1.02~1.11)^*
	lag 2	1.02(0.95~1.09)	1.13(1.04~1.22)^*	1.06(0.98~1.15)	1.04(0.93~1.14)	1.06(1.01~1.12)^*
	lag 3	1.02(0.96~1.09)	1.11(1.03~1.19)^*	1.06(0.98~1.13)	1.05(0.95~1.14)	1.06(1.01~1.11)^*
注：模型1未调整，模型2调整因素包括年龄、性别、民族、BMI、体力活动、家庭年均收入、被动吸烟、独生子女；^*P < 0.05。

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