Long-term trends in the incidence of endometriosis in China from 1990 to 2019: a joinpoint and age–period–cohort analysis

医学 子宫内膜异位症 入射(几何) 人口学 队列研究 队列 代群效应 妇科 内科学 光学 物理 社会学
作者
Jinhui Feng,Shitong Zhang,Jiadong Chen,Jie Yang,Jue Zhu
出处
期刊:Gynecological Endocrinology [Informa]
卷期号:37 (11): 1041-1045 被引量:7
标识
DOI:10.1080/09513590.2021.1975675
摘要

Trends in the incidence of endometriosis in China remain unknown. The purpose of this study was to examine the trends in the incidence of endometriosis and the effects of age, period, and cohort on them.Trends in endometriosis incidence were estimated using joinpoint regression. Age-period-cohort analysis was used to analyze the effects of age, period, and cohort on these trends. Endometriosis incidences in China (1990-2019) were retrieved from the Global Burden of Disease Study 2019. Annual percentage change and average annual percent change (AAPC) were analyzed by joinpoint regression, and relative risks were analyzed using an age-period-cohort model.Age-standardized incidence rates (ASIRs) declined between 1990 and 2019 in China, with an overall AAPC of -1.2% (95% CI: -1.20, -1.10). Compared to 1990, the ASIR in 2019 decreased by almost 30%. Moreover, the joinpoint regression analysis revealed that endometriosis ASIRs showed a downward trend across all age groups. A significant age-related effect was seen for endometriosis incidence among young women aged 15-24 years, which then decreased with advancing age. Consistently, the effect of the period on endometriosis incidence showed a declining trend, and the effect of birth cohort decreased by 0.53 (42.7%) from 1938-1942 to 1998-2002.Endometriosis ASIRs declined from 1990 to 2019. The effects of period and birth cohort on endometriosis incidence exhibited a declining trend across all age groups. The effect of age on endometriosis incidence showed an increasing trend before the age of 24, followed by a decreasing trend with subsequent advancing age.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
5秒前
5秒前
nbing发布了新的文献求助10
5秒前
orixero应助俏皮的豌豆采纳,获得10
6秒前
9秒前
10秒前
10秒前
颖仔完成签到,获得积分10
10秒前
企鹅发布了新的文献求助10
10秒前
巫雁发布了新的文献求助10
10秒前
Dpd发布了新的文献求助10
10秒前
傻芙芙的发布了新的文献求助10
10秒前
自信鞯完成签到,获得积分10
10秒前
夏木南生完成签到 ,获得积分10
11秒前
霄洒瞎客发布了新的文献求助10
13秒前
Liam发布了新的文献求助10
15秒前
英俊中心发布了新的文献求助10
15秒前
16秒前
朴实的代桃完成签到 ,获得积分10
16秒前
11发布了新的文献求助10
17秒前
烟花应助亻鱼采纳,获得10
17秒前
20秒前
星辰大海应助Aki采纳,获得10
23秒前
曾经的思山完成签到,获得积分10
23秒前
24秒前
25秒前
yyqx1128发布了新的文献求助10
26秒前
28秒前
胆大心细发布了新的文献求助10
28秒前
科研通AI2S应助科研通管家采纳,获得10
28秒前
完美世界应助科研通管家采纳,获得10
28秒前
28秒前
田様应助科研通管家采纳,获得10
28秒前
科研通AI2S应助科研通管家采纳,获得10
28秒前
29秒前
hgt发布了新的文献求助10
29秒前
31秒前
cyy完成签到,获得积分10
31秒前
所所应助香蕉闭月采纳,获得10
31秒前
高分求助中
Sustainability in Tides Chemistry 2000
Bayesian Models of Cognition:Reverse Engineering the Mind 800
Essentials of thematic analysis 700
A Dissection Guide & Atlas to the Rabbit 600
Very-high-order BVD Schemes Using β-variable THINC Method 568
Внешняя политика КНР: о сущности внешнеполитического курса современного китайского руководства 500
Revolution und Konterrevolution in China [by A. Losowsky] 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3124472
求助须知:如何正确求助?哪些是违规求助? 2774822
关于积分的说明 7723991
捐赠科研通 2430264
什么是DOI,文献DOI怎么找? 1290985
科研通“疑难数据库(出版商)”最低求助积分说明 622052
版权声明 600297