Aims. There has recently been an increased interest in mental health indicators for the monitoring of population wellbeing, which is among the targets of Sustainable Development Goals adopted by the United Nations. Levels of subjective wellbeing and suicide rates have been proposed as indicators of population mental health, but prior research is limited.Methods. Data on individual happiness and life satisfaction were sourced from a population-based survey in Hong Kong (2011). Suicide data were extracted from Coroner's Court files (2005-2013). Area characteristic variables included local poverty rate and four factors derived from a factor analysis of 21 variables extracted from the 2011 census. The associations between mean happiness and life satisfaction scores and suicide rates were assessed using Pearson correlation coefficient at two area levels: 18 districts and 30 quantiles of large street blocks (LSBs; n = 1620). LSB is a small area unit with a higher level of within-unit homogeneity compared with districts. Partial correlations were used to control for area characteristics.Results. Happiness and life satisfaction demonstrated weak inverse associations with suicide rate at the district level (r =-0.32 and-0.36, respectively) but very strong associations at the LSB quantile level (r =-0.83 and-0.84, respectively). There were generally very weak or weak negative correlations across sex/age groups at the district level but generally moderate to strong correlations at the LSB quantile level. The associations were markedly attenuated or became null after controlling for area characteristics.Conclusions. Subjective wellbeing is strongly associated with suicide at a small area level; socioeconomic factors can largely explain this association. Socioeconomic factors could play an important role in determining the wellbeing of the population, and this could inform policies aimed at enhancing population wellbeing.
CITATION STYLE
Hsu, C. Y., Chang, S. S., & Yip, P. S. F. (2019). Subjective wellbeing, suicide and socioeconomic factors: An ecological analysis in Hong Kong. Epidemiology and Psychiatric Sciences, 28(1), 112–130. https://doi.org/10.1017/S2045796018000124
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