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BMC Public Health ; 24(1): 1269, 2024 May 09.
Article in English | MEDLINE | ID: mdl-38725017

ABSTRACT

BACKGROUND: Over the past three decades, China has experienced significant changes in urban-rural, gender, and age-specific suicide mortality patterns. This study aimed to investigate the long-term trends in suicide mortality in China from 1987 to 2020. METHODS: Suicide mortality data were obtained from China's National Health Commission. Joinpoint regression analysis was used to examine changes in trends and age-period-cohort modeling to estimate age, period, and cohort effects on suicide mortality from 1987 to 2020. Net drift, local drift, longitudinal age curves, and period relative risks were also calculated. RESULTS: Crude and age-standardized suicide mortality in China showed continuing downward trends from 1987 to 2020, with a more pronounced decrease in rural areas (net drift = -7.07%, p<0.01) compared to urban areas (net drift = -3.41%, p<0.01). The decline curve of urban areas could be divided into three substages. Period and cohort effects were more prominent in rural areas. Suicide risk was highest among individuals aged 20-24 and gradually increased after age 60. Females, particularly those of childbearing age, had higher suicide risk than males, with a reversal observed after age 50. This gender reversal showed distinct patterns in urban and rural areas, with a widening gap in urban areas and a relatively stable gap in rural areas. CONCLUSIONS: Suicide mortality in China has consistently declined over the past three decades. However, disparities in age, gender, and urban-rural settings persist, with new patterns emerging. Targeted suicide prevention programs are urgently needed for high-risk groups, including females of childbearing age and the elderly, and to address the slower decrease and reversing urban-rural gender trends.


Subject(s)
Rural Population , Suicide , Urban Population , Humans , China/epidemiology , Male , Female , Middle Aged , Adult , Suicide/trends , Suicide/statistics & numerical data , Young Adult , Rural Population/statistics & numerical data , Urban Population/statistics & numerical data , Adolescent , Aged , Mortality/trends , Health Status Disparities
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