Trend of anxiety disorders in China from 1990 to 2019: An age-period-cohort analysis study

The incidence and prevalence of anxiety disorders in China showed a declining trend from 1990 to 2019. It is anticipated that the incidence and prevalence of anxiety disorders will rise from 2020 to 2040. The incidence and prevalence of anxiety disorders varies with age and gender.

Authors

Institutions

Publication Details

Journal
Public Health
Published
2025-02-06
DOI
https://doi.org/10.1016/j.puhe.2025.01.024
Citations
1
Primary Topic
Maternal Mental Health During Pregnancy and Postpartum
Type
article
Field-Weighted Citation Impact
1.88

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Trend of anxiety disorders in China from 1990 to 2019: An age-period-cohort analysis study

Li Ma, Yuheng He, Zhen Tang, Yan Cai et al.
1 citations
Public Health
Maternal Mental Health During Pregnancy and Postpartum
1.88
article

Trend of anxiety disorders in China from 1990 to 2019: An age-period-cohort analysis study

Li Ma, Yuheng He, Zhen Tang, Yan Cai, Yiyi Chen, Yongzhao Zhou
article en
1 citations

Abstract

The incidence and prevalence of anxiety disorders in China showed a declining trend from 1990 to 2019. It is anticipated that the incidence and prevalence of anxiety disorders will rise from 2020 to 2040. The incidence and prevalence of anxiety disorders varies with age and gender.

Public HealthVol. 240
Sichuan University (CN), West China Hospital of Sichuan University (CN)
Sichuan University
Openalex Percentile: Top 19%
Maternal Mental Health During Pregnancy and Postpartum
1.88
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.