大气颗粒污染物与原发性高血压患者血压变异及昼夜节律的关联研究

刘杰; 王菲; 刘亚恬; 李新蕊; 李丹; 王静; 唐龙妹; 胡舜英

doi:10.12435/j.issn.2095-5227.25101602

大气颗粒污染物与原发性高血压患者血压变异及昼夜节律的关联研究

Association of particulate matter with blood pressure variability and circadian rhythm in essential hypertension

摘要

摘要: 背景　既往研究显示大气颗粒污染物与血压升高有关，但鲜有大气颗粒物与血压变异及昼夜节律关系的研究。目的　探讨大气颗粒污染物短期暴露与原发性高血压患者血压变异及昼夜节律的相关性。方法　本研究纳入解放军总医院第一医学中心心内科2019 年1 月1 日至2022 年12 月31 日入院诊断为原发性高血压的患者。以研究对象入院当日的大气颗粒物24 h 平均浓度作为污染物暴露指标，采用分布式滞后非线性模型分析细颗粒物(PM2.5)、可吸入颗粒物(PM10)短期暴露对原发性高血压患者血压变异性指标——标准差(standard deviation，SD)和变异系数(coefficient of variation，CV)的滞后效应，并进一步分析PM2.5、PM10与非杓型或反杓型血压节律之间的滞后关联。结果　在控制了年龄、性别、节假日等潜在的混杂因素后，单日滞后结果显示，PM2.5 每增加10 μg/m³对日间收缩压标准差(day time systolic blood pressure standard deviation，dSBPSD)、日间收缩压变异系数(daytime systolic blood pressure coefficient of variation，dSBPCV)滞后效应的最大效应值在滞后2(lag2)天，分别增加1.42(95% CI：0.67 ~ 2.17) mmHg，0.93(95% CI：0.34 ~ 1.53)%，对日间舒张压标准差(daytime diastolic blood pressure standard deviation，dDBPSD)滞后效应的最大效应值在lag0 天，增加2.27(95% CI：0.31 ~ 4.23) mmHg。PM10每增加10 μg/m³对dDBPSD 滞后效应的最大效应值在lag0 天，增加2.09(95% CI：0.84 ~ 3.34) mmHg，夜间舒张压变异系数(night time diastolic blood pressure standard deviation，nDBPCV)滞后效应的最大效应值在lag2 天，增加1.68(95% CI：0.04 ~ 3.29)%。PM2.5对非杓型及反杓型组昼夜收缩压差值(SBP dipping)与舒张压差值(DBP dipping)累积滞后效应，呈上升趋势，最大值在lag0_6，分别增加4.95(95% CI：0.82 ~ 9.10) mmHg，5.16(95% CI：1.15 ~ 9.17) mmHg；PM10对SBP的累积滞后效应在lag_5，血压增加18.13(95% CI：1.05 ~ 35.20) mmHg，SBP dipping，DBP dipping 呈上升趋势，最大值在lag_6，分别增加6.94(95% CI：0.75 ~ 13.13) mmHg，8.72(95% CI：0.08 ~ 17.37) mmHg。结论　大气颗粒物(PM2.5、PM10)短期暴露与原发性高血压患者的血压变异存在滞后性，PM2.5、PM10颗粒物浓度的升高可能与非杓型或反杓型血压节律有关。

Abstract: Background　Short-term exposure to air pollutants has been associated with elevated blood pressure. However, few studies have examined the relationship between particulate matter, blood pressure variability (BPV), and circadian rhythms. Objective　To investigate the effects of air pollutant levels on BPV and blood pressure circadian rhythm in patients with essential
hypertension.Methods　Patients admitted to the Department of Cardiology, the First Medical Center of PLA General Hospital from January 2019 to January 2022 and diagnosed with essential hypertension were included. BPV indicators and pollutant data, including particulate matter 2.5 (PM2.5) and particulate matter 10 (PM10), were collected. Standard deviation (SD) and coefficient of variation (CV) were used to evaluate the ambulatory BPV. A distributed lag model with median regression was constructed to assess lag effects and associations between air pollution components, BPV, and circadian rhythm. Results　After adjusting for potential
confounders such as age, sex, and holidays, for every 10-μg/m³ increase in PM2.5, the maximum lag effect on daytime systolic blood pressure (dSBP) SD and dSBP CV was observed at lag 2, with increments of 1.42 (95% CI: 0.67 - 2.17) mmHg and 0.93 (95% CI: 0.34 - 1.53)%, respectively. For every 10- μg/m³ increase in PM2.5, the maximum lag effect on daytime diastolic blood pressure (dDBP) SD was observed at lag 0, with an increment of 2.27 (95% CI: 0.31 - 4.23) mmHg. For every 10-μg/m³ increase in PM10, the maximum lag effect on dDBP SD was observed at lag 0, with an increment of 2.09 (95% CI: 0.84 - 3.34) mmHg, while the maximum lag effect on nighttime diastolic blood pressure CV was observed at lag 2, with an increment of 1.68 (95% CI: 0.04 - 3.29) %. PM2.5 exerted the maximum cumulative effect on SBP dipping and DBP dipping at lag 06, with increments of 4.95 (95% CI: 0.82 - 9.10) mmHg and 5.16 (95% CI: 1.15 - 9.17) mmHg, respectively. The maximum cumulative lag effect of PM10 on SBP was observed at lag 05, with an increment of 18.13 (95% CI: 1.05 - 35.20) mmHg. The maximum cumulative lag effect of PM10 on SBP dipping and nDBP dipping was observed at lag 06, with increments of 6.94 (95% CI: 0.75 - 13.13) mmHg and 8.72 (95% CI: 0.08 - 17.37) mmHg, respectively.Conclusion　A lag effect is observed between PM exposure and BPV. PM may be associated with non-dipping and reverse-dipping circadian rhythm patterns in patients with essential hypertension.

HTML全文

参考文献(0)

施引文献

资源附件(0)