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空气污染和天气作为哮喘急性发作的决定因素:时空方法。

Air pollution and weather as the determinants of acute attacks of asthma: Spatiotemporal approach.

机构信息

Director Professor, University College of Medical Sciences, University of Delhi, Delhi, India.

Insurance Medical Officer, ESI Dispensary, Dwarka, Delhi, India.

出版信息

Indian J Public Health. 2020 Apr-Jun;64(2):124-129. doi: 10.4103/ijph.IJPH_135_19.

Abstract

BACKGROUND

Although air pollution and weather changes have been identified as putative risk factors that precipitate acute attacks of bronchial asthma, so far there have been no studies that could conclusively establisha clear association.

OBJECTIVES

This study was carried out to investigate the effect of the concentrations of NO, SO, and particulate matter on exacerbation of bronchial asthma.

METHODS

A longitudinal study was conducted during February 2014-January 2015. Sixty-one known cases of asthma were recruited from the outpatient department of a chest hospital. Data regarding weather parameter (temperature, rainfall, and relative humidity) and environmental pollution (SOand NO) and respirable suspended particulate matter were procured from the Indian Meteorological Department and Delhi Pollution Control Committee, respectively. Association was examined using the generalized estimation equation (GEE).

RESULTS

Separate models were developed for weather parameter and pollution parameters. This study could not find a significant association between any of the weather parameters and occurrence of asthmatic attacks. In the GEE model, where average values of SO, NO, and PM were used, the PM was found to be significantly associated with asthmatic attacks.

CONCLUSION

PM was found to increase the risk of exacerbation of asthma three folds.

摘要

背景

尽管空气污染和天气变化已被确定为可能导致支气管哮喘急性发作的因素,但迄今为止,尚无研究能明确确定两者之间的关联。

目的

本研究旨在探讨 NO、SO 和颗粒物浓度对支气管哮喘恶化的影响。

方法

2014 年 2 月至 2015 年 1 月进行了一项纵向研究。从胸科医院的门诊部门招募了 61 例已知哮喘病例。天气参数(温度、降雨量和相对湿度)和环境污染(SO 和 NO)及可吸入悬浮颗粒物的数据分别从印度气象部门和德里污染控制委员会获得。使用广义估计方程(GEE)来检查相关性。

结果

分别为天气参数和污染参数建立了模型。本研究未发现任何天气参数与哮喘发作之间存在显著关联。在使用 SO、NO 和 PM 的平均值的 GEE 模型中,发现 PM 与哮喘发作显著相关。

结论

PM 被发现使哮喘恶化的风险增加了三倍。

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