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Journal Article

Citation

Yeung CY, Men YV, Caine ED, Yip PSF. Soc. Sci. Med. 2022; 315: e115524.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.socscimed.2022.115524

PMID

36413859

Abstract

INTRODUCTION: Little research has conducted to examine the association between social deprivation and social fragmentation, overall and method-specific suicide risk, and how these associations may change over time. This study investigated the association between social deprivation and social fragmentation with overall and method-specific suicide in Hong Kong from 1999 to 2018.

METHODS: Suicide death data of each small tertiary planning unit (STPU) was obtained from the Census and Statistics Department of Hong Kong. Socio-economic characteristics in STPU level were obtained from Census and Bi-census. Exploratory principal component analysis was used to construct the social deprivation (SDI) and social fragmentation indices (SFI) based on the socio-economic characteristics. Bayesian hierarchical modelling was conducted to explore the association between SDI and SFI with overall and method-specific suicide over time, controlling for population density and male-to-female ratio.

RESULTS: Higher risk of suicide was generally observed around Kowloon Peninsula and some parts in the Northern, Northwestern and Southwestern areas depending on methods. The effect of SDI and SFI on suicide risk varied by years and methods. In 2014-2018, for every 10% increase in SDI, the suicide risk for overall, jumping, hanging, and charcoal burning elevated by 22% (95%Crl = 10%-37%), 26% (95%Crl = 12%-41%), 31% (95%Crl = 14%-51%), and 21% (95%Crl = 4%-42%) respectively.

CONCLUSION: Spatial variations and effects of SDI and SFI on overall and method-specific suicide risks varied by different periods. SDI was observed to be a stronger factor in the recent years. Situations should be monitored, and interventions should be implemented and adjusted accordingly to the changes.


Language: en

Keywords

Suicide; Spatial analysis; Principal component analysis; Bayesian hierarchical modelling; Social deprivation; Social fragmentation

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