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1.
Sleep Med ; 121: 251-257, 2024 Sep.
Artículo en Inglés | MEDLINE | ID: mdl-39024779

RESUMEN

Poor sleep quality is a widespread concern. While the influence of particle exposure on sleep disturbances has received considerable attention, research exploring other dimensions of sleep quality and the chemical components of the particles remains limited. We employed a marginal structural model to explore the association of long-term exposure to PM2.5 and its chemical components with poor sleep quality. The odds ratio (95 % CI) for poor sleep quality was 1.335 (1.292-1.378), 1.097 (1.080-1.113), 1.137 (1.100-1.174), 1.197 (1.156-1.240), and 1.124 (1.107-1.140) per IQR increase in the concentration of PM2.5, SO42-, NO3-, NH4+, and BC, respectively. The score (and 95 % CI) of sleep latency, use of sleep medication, habitual sleep efficiency, subjective sleep quality, and daytime dysfunction were affected by PM2.5, with an increase of 0.059 (0.050-0.069), 0.054 (0.049-0.059), 0.011 (0.008-0.014), 0.011 (0.005-0.018), and 0.026 (0.018-0.034) per IQR increase in PM2.5 concentrations, respectively. This study supports the association of long-term exposure to PM2.5 and its chemical components with poor sleep quality.


Asunto(s)
Material Particulado , Calidad del Sueño , Humanos , Material Particulado/análisis , Material Particulado/efectos adversos , Masculino , Femenino , Exposición a Riesgos Ambientales/efectos adversos , Persona de Mediana Edad , Contaminantes Atmosféricos/análisis , Contaminantes Atmosféricos/efectos adversos , Adulto , Trastornos del Sueño-Vigilia
2.
Sci Bull (Beijing) ; 69(9): 1313-1322, 2024 May 15.
Artículo en Inglés | MEDLINE | ID: mdl-38556396

RESUMEN

Limited evidence exists on the effect of submicronic particulate matter (PM1) on hypertension hospitalization. Evidence based on causal inference and large cohorts is even more scarce. In 2015, 36,271 participants were enrolled in South China and followed up through 2020. Each participant was assigned single-year, lag0-1, and lag0-2 moving average concentration of PM1 and fine inhalable particulate matter (PM2.5) simulated based on satellite data at a 1-km resolution. We used an inverse probability weighting approach to balance confounders and utilized a marginal structural Cox model to evaluate the underlying causal links between PM1 exposure and hypertension hospitalization, with PM2.5-hypertension association for comparison. Several sensitivity studies and the analyses of effect modification were also conducted. We found that a higher hospitalization risk from both overall (HR: 1.13, 95% CI: 1.05-1.22) and essential hypertension (HR: 1.15, 95% CI: 1.06-1.25) was linked to each 1 µg/m3 increase in the yearly average PM1 concentration. At lag0-1 and lag0-2, we observed a 17%-21% higher risk of hypertension associated with PM1. The effect of PM1 was 6%-11% higher compared with PM2.5. Linear concentration-exposure associations between PM1 exposure and hypertension were identified, without safety thresholds. Women and participants that engaged in physical exercise exhibited higher susceptibility, with 4%-22% greater risk than their counterparts. This large cohort study identified a detrimental relationship between chronic PM1 exposure and hypertension hospitalization, which was more pronounced compared with PM2.5 and among certain groups.


Asunto(s)
Exposición a Riesgos Ambientales , Hospitalización , Hipertensión , Material Particulado , Humanos , Material Particulado/efectos adversos , Material Particulado/análisis , China/epidemiología , Femenino , Masculino , Hospitalización/estadística & datos numéricos , Persona de Mediana Edad , Hipertensión/epidemiología , Estudios de Cohortes , Exposición a Riesgos Ambientales/efectos adversos , Anciano , Adulto , Contaminantes Atmosféricos/efectos adversos , Contaminantes Atmosféricos/análisis , Contaminación del Aire/efectos adversos , Contaminación del Aire/análisis
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