兰州市沙尘天气与痤疮门诊量的时间序列

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摘要

研究沙尘天气、非沙尘天气下颗粒物（PM_2.5、PM_C、PM₁₀）对痤疮门诊量的影响，并进行性别、年龄分层研究，筛选敏感人群.收集了2013~2017年兰州市沙尘期与非沙尘期3家三甲医院痤疮门诊量资料、大气颗粒物及气象数据，采用基于泊松分布的分布滞后非线性模型（DLNM），控制气象因素、季节性和长期趋势、星期几效应等混杂因素，分析沙尘期与非沙尘期颗粒物对痤疮门诊量的影响及滞后效应.结果表明：沙尘期时，兰州市3家三甲医院痤疮日均门诊量为26人次，范围3~54人次.非沙尘期时痤疮日均门诊量为37人次，范围1~89人次；单污染物模型显示，PM_2.5、PM_C、PM₁₀均在滞后第6d （lag6）时效应量达到最大值，其浓度每增加10μg/m³，痤疮门诊量的超额危险度（ER）及95%可信区间（95% CI）分别为1.065（95% CI：0.260~1.877）、0.355（95% CI：0.018~0.693）、0.310（95% CI：0.054~0.567），PM_2.5对痤疮门诊量的影响最为显著；性别及年龄分层发现，性别分层中PM_2.5对女性的影响有统计学意义，其浓度每增加10μg/m³，痤疮门诊量增加1.077（95% CI：0.124~2.039）；年龄分层中，0~18岁组受PM_C、PM₁₀影响显著，19~24岁组受PM_2.5、PM₁₀影响显著，各颗粒物对25~34岁组及≥35岁组效应无统计学意义.在非沙尘期时，PM_2.5、PM_C、PM₁₀不引起痤疮门诊量增加.双/多污染物模型显示，分别调整其他污染物后，PM_2.5、PM_C、PM₁₀对痤疮门诊量的影响与单污染物模型类似，仍具有统计学意义.兰州市沙尘天气下大气颗粒物（PM_2.5、PM_C、PM₁₀）可使痤疮门诊量增加，对女性及青少年影响显著.

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	孙倩倩
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	何苑
	白瑶
	潘亚娟
	骆志成
	郗群
	尹沫涵

关键词 ：沙尘天气, 大气颗粒物, 痤疮, 时间序列, 分布滞后非线性模型

Abstract：

The effects of particulate matters (PM_2.5, PM_C, PM₁₀) on the number of outpatient visits due to acne were studied during dust weather and non-dust weather, as well as to filter out the sensitive population by gender and age stratification. By collecting data on the concentration of particulate matters, i.e., PM_2.5, PM_C, PM₁₀, as well as the corresponding meteorological data and the outpatient data of visits due to acne at 3 first-class grade three hospitals during dust weather and non-dust weather in Lanzhou between 2013 to 2017, the relationship between particulate matters concentration and daily outpatient visits due to acne and its lagging effect were analyzed using distributed lag non-linear model (DLNM) based on Poisson distribution to constrain meteorological factors, seasonal and long-term trends, the day of week effect and other confounding factors. During the dust weather, the average daily outpatient visits due to acne at 3 first-class grade-three hospitals in Lanzhou were 26 person-times, ranging from 3 to 54 person-times; during non-dust weather, the daily outpatient visits due to acne were 37person-times, ranging from 1to 89person-times. According to the results of the single-pollutant model, the effects of PM_2.5, PM_C and PM₁₀ all peaked on lag6; for every 10μg/m³ increase in their concentration, the excess risk (ER) and 95% confidence interval (95%CI) of visits for acne were 1.065 (95%CI:0.260~1.877), 0.355 (95%CI:0.018~0.693), and 0.310 (95%CI:0.054~0.567) respectively, and PM_2.5 presented the most significant effect on the outpatient visits for acne. Analysis of different gender and age indicated that, PM_2.5 has a statistically significant effect on women, and for every 10μg/m³ increase in the concentration, the visits due to acne increased by 1.077 (95%CI:0.124~2.039); the 0-18-year-old group was significantly affected by PM_C and PM₁₀, the 19-24-year-old group was significantly affected by PM_2.5 and PM₁₀, while no statistical significance was found in the effect of particulate matters on the 25-34-year-old group as well as the ³35-year-old group. During non-dust weather, PM_2.5, PM_C and PM₁₀ did not increase the outpatient visits for acne. The double/multi-pollutant model demonstrated that after adjusting other pollutants, PM_2.5, PM_C and PM₁₀ had the similar effects on the outpatient visits for acne as the single-pollutant model, which were still statistically significant. Hence, it can be concluded that, the increments in particulate matters (PM_2.5, PM_C, PM₁₀) are likely to increase the risk of acne during dust weather in Lanzhou and have a significant effect on women and adolescents.

Key words： sand dust weather particulate matter acne vulgaris time-series DLNM

收稿日期: 2020-03-12

PACS:

X503.1

基金资助:

甘肃省自然科学基金项目（18JR3RA337）

通讯作者: 石春蕊,副教授,stone7207@126.com E-mail: stone7207@126.com

作者简介: 孙倩倩(1993-),女,甘肃庆阳人,兰州大学第一临床医学院专业型硕士研究生,主要从事环境因素对皮肤疾病影响的相关性研究.

引用本文:

孙倩倩, 石春蕊, 何苑, 白瑶, 潘亚娟, 骆志成, 郗群, 尹沫涵. 兰州市沙尘天气与痤疮门诊量的时间序列[J]. 中国环境科学, 2020, 40(11): 5063-5070. SUN Qian-qian, SHI Chun-rui, HE Yuan, BAI Yao, PAN Ya-juan, LUO Zhi-cheng, XI Qun, YIN Mo-han. Time-series study on the effect of particulate matters and acne during dust weather in Lanzhou. CHINA ENVIRONMENTAL SCIENCECE, 2020, 40(11): 5063-5070.

链接本文:

http://www.zghjkx.com.cn/CN/ 或 http://www.zghjkx.com.cn/CN/Y2020/V40/I11/5063

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