Field Epidemiology Training Programme, National Infection Service, Public Health England, Birmingham, UK
Health Services Division, Warwick Medical School, University of Warwick, Coventry, UK.
BMJ Open. 2020 Dec 4;10(12):e036724. doi: 10.1136/bmjopen-2019-036724.
To identify key predictors of general practitioner (GP) consultations for allergic rhinitis (AR) using meteorological and environmental data.
A retrospective, time series analysis of GP consultations for AR.
A large GP surveillance network of GP practices in the London area.
The study population was all persons who presented to general practices in London that report to the Public Health England GP in-hours syndromic surveillance system during the study period (3 April 2012 to 11 August 2014).
Consultations for AR (numbers of consultations).
During the study period there were 186 401 GP consultations for AR. High grass and nettle pollen counts (combined) were associated with the highest increases in consultations (for the category 216-270 grains/m, relative risk (RR) 3.33, 95% CI 2.69 to 4.12) followed by high tree (oak, birch and plane combined) pollen counts (for the category 260-325 grains/m, RR 1.69, 95% CI 1.32 to 2.15) and average daily temperatures between 15°C and 20°C (RR 1.47, 95% CI 1.20 to 1.81). Higher levels of nitrogen dioxide (NO) appeared to be associated with increased consultations (for the category 70-85 µg/m, RR 1.33, 95% CI 1.03 to 1.71), but a significant effect was not found with ozone. Higher daily rainfall was associated with fewer consultations (15-20 mm/day; RR 0.812, 95% CI 0.674 to 0.980).
Changes in grass, nettle or tree pollen counts, temperatures between 15°C and 20°C, and (to a lesser extent) NO concentrations were found to be associated with increased consultations for AR. Rainfall has a negative effect. In the context of climate change and continued exposures to environmental air pollution, intelligent use of these data will aid targeting public health messages and plan healthcare demand.
利用气象和环境数据确定全科医生(GP)治疗过敏性鼻炎(AR)的主要预测因素。
AR 全科医生就诊的回顾性时间序列分析。
伦敦地区大型全科医生监测网络中的全科医生实践。
研究人群为在研究期间(2012 年 4 月 3 日至 2014 年 8 月 11 日)向英国公共卫生英格兰(Public Health England)门诊时间综合征监测系统报告的伦敦所有向全科医生诊所就诊的患者。
AR 就诊(就诊次数)。
在研究期间,有 186401 例 AR 全科医生就诊。高草和荨麻花粉计数(合并)与就诊人数增加最高相关(对于 216-270 粒/ m 类别,相对风险(RR)为 3.33,95%置信区间(CI)为 2.69 至 4.12),其次是高浓度树木(橡树、桦树和飞机混合)花粉计数(对于 260-325 粒/ m 类别,RR 为 1.69,95%CI 为 1.32 至 2.15)和 15°C 至 20°C 之间的平均日温度(RR 为 1.47,95%CI 为 1.20 至 1.81)。较高水平的二氧化氮(NO)似乎与就诊人数增加相关(对于 70-85μg/m 类别,RR 为 1.33,95%CI 为 1.03 至 1.71),但未发现臭氧有显著影响。每日降雨量增加与就诊人数减少相关(15-20mm/天;RR 为 0.812,95%CI 为 0.674 至 0.980)。
草、荨麻或树木花粉计数、15°C 至 20°C 之间的温度以及(在较小程度上)NO 浓度的变化与 AR 就诊人数增加有关。降雨有负面影响。在气候变化和持续暴露于环境空气污染的背景下,明智地利用这些数据将有助于针对公众健康信息和计划医疗保健需求。