Common Mental Disorder across Standard Occupational Classifications in Northern Ireland: an administrative data study

Abstract

Background While employment in general promotes positive health and wellbeing, a number of studies show disparities in mental health across occupational groupings (Bell et al., 2014; Stansfield et al. 2011). However, definitive studies to allow estimation of prevalence and risk across a range of occupation types require large population sub-groups and common measures of mental health. Aim We hypothesise: (1) we will detect differences in the prevalence of Common Mental Disorder (CMD) across occupational groupings; and (2) risk of CMD across occupation types is moderated by family demands. Methods Using linked administrative data we examine CMD among the Northern Ireland (NI) adult population across Standard Occupational Classifications (SOCs). We also examine the influence of socio-demographic, socio-economic and health-related variables. Data is accessed through the Administrative Data Research Centre NI (ADRC-NI) and comprises the individual and household 2011 Census; Land and Properties Services data; Enhanced Prescribing Database and Multiple Deprivation Measures. Results Examination of nine major SOC groups shows the prevalence of any self-reported (SR) mental health condition was highest among ‘elementary trades and related occupations’ (24.63%) followed by ‘process, plant and machine operatives’ (23.65%). The risk of mental ill health among these groups remained elevated for both men and women after controlling for age, sex, marital status and educational attainment. Analyses based on the 90 sub-minor SOC groups shows that ‘textiles and garments trades’ workers had the highest prevalence of a SR mental health condition (36.15%). Logistic regression analyses shows that individuals with dependent children and informal caregiving responsibilities had lower risk of a SR mental health condition (OR=0.75, CI=0.73, 0.76 and OR=0.81, CI=0.79, 0.82 respectively). Conclusion Results presented in this abstract are based on preliminary analyses using self-reported mental health. Further analyses based on mental health prescription data will subsequently be undertaken and presented at the ADR conference.