职业与健康 ›› 2026, Vol. 42 ›› Issue (5): 653-657.

• 论著 • 上一篇    下一篇

2006—2020年乌鲁木齐市0~<35岁人群水痘发病趋势分析

古丽加衣娜·艾肯1, 依木冉·凯赛尔2, 陈薇3, 周燚然1, 张宇航1, 卢耀勤1,3()   

  1. 1.新疆医科大学,新疆 乌鲁木齐 830054
    2.新疆医科大学第一附属医院,新疆 乌鲁木齐 830054
    3.乌鲁木齐市疾病预防控制中心(市卫生监督所),新疆 乌鲁木齐 830026
  • 收稿日期:2025-05-28 修回日期:2025-07-09 出版日期:2026-03-01 发布日期:2026-03-10
  • 通信作者: 卢耀勤,E-mail:lyq_superior@163.com
  • 作者简介:古丽加衣娜·艾肯,女,在读硕士研究生,研究方向为流行病与卫生统计学。
  • 基金资助:
    生物安全战略防御一体化建设创新团队(2022TSYCTD0015)

Analysis of the incidence trend of chickenpox in the people aged 0-<35 years in Urumqi City from 2006 to 2020

Gulijiayina Aiken1, Yimuran Kaisaier2, CHEN Wei3, ZHOU Yiran1, ZHANG Yuhang1, LU Yaoqin1,3()   

  1. 1. Xinjiang Medical University,Urumqi,Xinjiang 830054,China
    2. The First Affiliated Hospital of Xinjiang Medical University,Urumqi,Xinjiang 830054,China
    3. Urumqi Center for Disease Control and Prevention(Urumqi Institute of Health Supervision),Urumqi,Xinjiang 830026,China
  • Received:2025-05-28 Revised:2025-07-09 Online:2026-03-01 Published:2026-03-10
  • Contact: LU Yaoqin,E-mail:lyq_superior@163.com
  • About author:LU Yaoqin,E-mail:lyq_superior@163.com

摘要:

目的 分析乌鲁木齐市0~<35岁人群水痘发病情况及趋势,评估年龄、时期和队列对其长期趋势的影响。方法 利用2006—2020年乌鲁木齐市传染病监测数据,使用Joinpoint回归(joinpoint regression model,JRM)拟合水痘发病率变化趋势并通过年龄-时期-队列模型(age-period-cohort,APC)评估年龄、时期、队列效应。结果 2006—2020年乌鲁木齐市0~<35岁人群水痘报告39 483例,年均报告发病率为180.73/10万,男性发病率高于女性。病例主要集中在0~<15岁人群,5~<10岁人群发病率最高。2006—2020年无明显变化趋势,不同性别人群水痘发病率变化趋势差异均无统计学意义(均P>0.05)。年龄别发病率10~<15、15~<20、25~<30和30~<35岁均呈上升趋势(均P<0.05)。5~<10岁为高发年龄组,15~<20岁男性发病率更高,女性20~<35岁发病率高。时期效应以2011—2015年为参考组,从2006—2010年期间的0.786(95%CI:0.667~0.927)升至2016—2020年间的1.530(95%CI:1.315~1.781)。队列效应总体呈先上升后下降趋势,达到2004—2008年出生队列组的2.305(95%CI:1.794~2.963)之后开始下降。结论 2006—2020年乌鲁木齐市水痘发病率呈M型波动趋势,0~<15岁为高发人群,其中5~<10岁为高危人群,15~<20岁发病率显著上升。<20岁男性发病率高于女性。出生队列发病率呈先上升后下降趋势,时间靠后的队列发病风险较小。因此,水痘防控应聚焦高危年龄群体,强化疫苗接种;兼顾性别差异,实施差异化策略;持续关注出生队列变化,及时调整防控措施。

关键词: 水痘, Joinpoint回归模型, APC模型

Abstract:

Objective To analyze the incidence and trend of varicella in the population aged 0-<35 in Urumqi City,and evaluate the impact of age,period,and cohort on its long-term trend. Methods The surveillance data of infectious diseases in Urumqi City from 2006 to 2020 were used to fit the change trend of varicella incidence rate using the joinpoint regression model(JRM),and the age-period-cohort model(APC) was used to assess the age,period,and cohort effect. Results From 2006 to 2020,39 483 cases of varicella were reported among people aged 0-<35 years in Urumqi City,and the average annual reported incidence was 180.73/100 000,and the incidence in men was higher than that in women. The cases were mainly concentrated in people aged 0-<15 years,and the incidence was highest in people aged 5-<10 years. There was no significant change from 2006 to 2020,and the change trend of varicella incidence rate in different gender groups was not statistically significant(all P>0.05). The age-specific incidence rate showed an upward trend at 10-<15,15-<20,25-<30 and 30-<35 years old(all P<0.05). The high incidence age group was 5-<10 years old. The incidence rate was higher for men 15-<20 years old,and the incidence rate was higher for women 20-<35 years old. The period effect was taken as the reference group from 2011 to 2015,rising from 0.786(95%CI:0.667-0.927) from 2006 to 2010 to 1.530(95%CI:1.315-1.781) from 2016 and 2020. The overall cohort effect increased first and then decreased,reaching 2.305(95%CI:1.794-2.963) in the birth cohort group from 2004 to 2008 before starting to decline. Conclusion From 2006 to 2020,the incidence of chickenpox in Urumqi City shows a M-type fluctuation trend. The people aged 0-<15 years are the high incidence group,of which the people aged 5-<10 years are the high-risk group,and the incidence rate of varicella aged 15-<20 years increases significantly. The incidence of men <20 years old is higher than that of women. The incidence of birth cohort showed an upward trend first and then a downward trend,and the cohort with a later time had a lower incidence risk. Therefore,varicella prevention and control should focus on high-risk age groups,strengthen vaccination,take into account gender differences and implement differentiated strategies;continuously pay attention to the changes of birth cohort,and timely adjust the prevention and control measures.

Key words: Chickenpox, Joinpoint regression model, Age-period-cohort model

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