Nitrate (NO3-) may be the key component driving insomnia risk elevation from short-term PM2.5 exposure: time-series-based public health evidence and refined management recommendations

LI Qianqian; FAN Yanni; FU Xianmei; WANG Kexue; LI Yuefei; WANG Yi; LIU Qiuqian; ZHOU Yumeng; CAI Tongjian

doi:10.16016/j.2097-0927.202603110-李倩倩

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Nitrate (NO₃^-) may be the key component driving insomnia risk elevation from short-term PM_2.5 exposure: time-series-based public health evidence and refined management recommendations

Think Tank for Public Health | 更新时间：2026-05-30

- Nitrate (NO₃^-) may be the key component driving insomnia risk elevation from short-term PM_2.5 exposure: time-series-based public health evidence and refined management recommendations
- Journal of Army Medical University Vol. 48, Issue 10, Pages: 1420-1432(2026)
- 作者机构：
  
  1.陆军军医大学（第三军医大学）大坪医院疾病预防控制科，创伤与化学中毒全国重点实验室，医院感染监测与控制重庆市高校重点实验室，重庆
  2.空军军医大学第二附属医院（唐都医院）信息科，陕西西安
- 作者简介：
  
  ZHOU Yumeng， E-mail： zhouyumeng@tmmu.edu.cn
  CAI Tongjian， E-mail： ctjcsl@netease.com
- 基金信息：
- DOI：10.16016/j.2097-0927.202603110-李倩倩
  CLC： R195;R741;X513
- Received：25 March 2026，
  
  Revised：2026-04-05，
  
  Accepted：08 April 2026，
  
  Published：30 May 2026
- 稿件说明：
移动端阅览
李倩倩，范艳妮，付宪梅，等.硝酸盐（NO₃^-）可能是PM_2.5短期暴露致失眠风险升高的关键组分：基于时间序列的公共卫生证据与精细化管理建议［J］.陆军军医大学学报，2026，48（10）：1420-1432.DOI：10.16016/j.2097-0927.202603110. DOI: 10.16016/j.2097-0927.202603110-李倩倩.

LI Q Q，FAN Y N，FU X M，et al.Nitrate （NO₃^-） may be the key component driving insomnia risk elevation from short-term PM_2.5 exposure： time-series-based public health evidence and refined management recommendations［J］.J Army Med Univ，2026，48（10）：1420-1432.DOI：10.16016/j.2097-0927.202603110. DOI: 10.16016/j.2097-0927.202603110-李倩倩.
李倩倩，范艳妮，付宪梅，等.硝酸盐（NO₃^-）可能是PM_2.5短期暴露致失眠风险升高的关键组分：基于时间序列的公共卫生证据与精细化管理建议［J］.陆军军医大学学报，2026，48（10）：1420-1432.DOI：10.16016/j.2097-0927.202603110. DOI: 10.16016/j.2097-0927.202603110-李倩倩. DOI：

LI Q Q，FAN Y N，FU X M，et al.Nitrate （NO₃^-） may be the key component driving insomnia risk elevation from short-term PM_2.5 exposure： time-series-based public health evidence and refined management recommendations［J］.J Army Med Univ，2026，48（10）：1420-1432.DOI：10.16016/j.2097-0927.202603110. DOI: 10.16016/j.2097-0927.202603110-李倩倩. DOI：

摘要

目的

随着城市空气污染加剧，细颗粒物（fine particulate matter， PM

2.5

）可能影响睡眠健康，但其组分对失眠风险的具体作用仍不明确。本研究旨在评估PM

2.5

及其主要组分短期暴露对失眠门诊就诊量的影响，以探究空气污染对睡眠健康的公共卫生意义。

方法

本研究为生态学时间序列研究，收集2015年1月1日至2019年12月31日于西安市空军军医大学第二附属医院（唐都医院）门诊系统中失眠门诊数据及中国大气成分近实时追踪数据集（Tracking Air Pollution in China， TAP）中PM

2.5

及硝酸盐（nitrate ion， NO

）、硫酸盐（sulfate ion， SO

）、铵盐（ammonium ion， NH

）、有机质（organic matter， OM）和黑碳（black carbon， BC）5种组分的浓度数据，构建广义相加模型（generalized additive models， GAM）评估单一PM

2.5

组分暴露与失眠门诊就诊风险的关联，进一步通过加权分位数和回归模型（weighted quantile sum， WQS）评估PM

2.5

组分混合暴露效应及其关键组分。

结果

2.5

及5种组分间存在显著的强相关（

=0.88~0.98）。在调整协变量后，暴露当日（lag0）各组分均与失眠风险呈显著正相关。单日滞后效应在lag3达峰值，NO

效应值最大（

IRR

=1.05，95%

：1.02~1.08）。累积滞后效应随时间呈递增趋势，在lag06达最大值，其中NO

（

IRR

=1.08，95%

：1.

04~1.12），NH

（

IRR

=1.07，95%

：1.03~1.11）和SO

（

IRR

=1.06，95%

：1.02~1.10）的效应值最大。分层分析结果显示，该效应在性别、年龄及季节上差异无统计学意义。WQS结果显示，PM

2.5

组分混合暴露与失眠就诊风险显著正相关（

=1.075，95%

：1.049~1.102，

0.01），NO

的相对权重占比最大（权重为0.841）。这一效应在不同年龄组和性别组中没有显著差异。

结论

2.5

组分短期暴露可显著增加失眠门诊就诊风险，且具有明显的滞后与累积效应。NO

是PM

2.5

组分混合暴露致失眠风险升高的关键组分。对策　在空气污染防控策略中，从以PM

2.5

质量浓度控制为主逐步向组分精细化管理转变，重点关注二次无机气溶胶（如NO

、SO

和NH

）的来源控制，为制定更具针对性的公共卫生干预措施提供依据。推动交通尾气、工业排放、燃煤及农业活动的精准减排措施，减少硝酸盐前体物的排放。

Abstract

Objective

With the intensification of urban air pollution

fine particulate matter (PM

2.5

) may affect sleep health

but the specific roles of its components in insomnia risk remain unclear. This study aims to evaluate the impacts of short-term exposure to PM

2.5

and its major components on the risk of outpatient visits for insomnia

thereby exploring the public health significance of air pollution on sleep health.

Methods

This study was a time‑series ecological study. Insomnia outpatient data from the Second Affiliated Hospital (Tangdu Hospital) of Air Force Medical University in Xi’an between January 1

2015

and December 31

2019 were collected. Concentrations of PM

2.5

and its 5 components

namely nitrate ion (NO

)

sulfate ion (SO

)

ammonium ion (NH

)

organic matter (OM)

and black carbon (BC)

were obtained from the Tracking Air Pollution in China (TAP) dataset. A generalized additive model (GAM) was constructed to evaluate the association between exposure to single PM

2.5

component and risk of insomn

ia outpatient visits. A weighted quantile sum (WQS) regression model was further applied to assess the mixed exposure effects of PM

2.5

components and to identify the key component.

Results

2.5

and the 5 components exhibited significant strong correlations (

=0.88 to 0.98). After adjusting for covariates

all components were significantly positively associated with insomnia risk on the exposure day (lag0). Single-day lag effects peaked at lag3

with NO₃⁻ showing the largest effect size (

IRR

=1.05

95%

: 1.02 to 1.08). Cumulative lag effects showed an increasing trend over time

reaching the maximum at lag06

with the largest effect sizes observed for NO

(

IRR

=1.08

95%

CI:

1.04

1.12)

(

IRR

=1.07

95%

: 1.03 to 1.11)

and SO

(

IRR

=1.06

95%

: 1.02

to 1.10). Stratified analyses revealed no significant differences across sex

age

or season. The WQS model showed that mixed exposure to PM

2.5

components was significantly positively associated with insomnia risk (

=1.075

95%

: 1.049 to 1.102

0.01)

with NO

accounting for the largest relative weight (weight=0.841). This effect did not differ significantly across age or sex groups.

Conclusion

Short-term exposure to PM

2.5

components significantly increases the risk of insomnia outpatient visits

with evident lag and cumulative effects. NO

is the key component driving insomnia risk elevation in mixed exposures to PM

2.5

components. Countermeasures In air pollution prevention and control strategies

the focus should gradually shift from controlling PM

2.5

mass concentration to refine

d component-based management

with particular attention to source control of secondary inorganic aerosols (NO

and NH

)

thereby providing a basis for developing more targeted public health interventions. Precision mitigation measures targeting traffic emissions

industrial exhaust

coal combustion

and agricultural activities should be promoted to reduce emissions of nitrate precursors.

关键词

Keywords

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