Persisting social disadvantage and intercensal social mobility in Northern Ireland: an examination of morbidity and all-cause mortality using three waves of the Northern Ireland Longitudinal Study (NILS).

Abstract

Objective and Approach Using census returns from three waves of NILS (1991, 2001, 2011) linked with mortality data, we examined morbidity/mortality outcomes by socio-economic disadvantage over time (using an individual-level deprivation index derived from educational attainment, social class, housing tenure and household car availability at each census). These were combined to generate two indicators of Intercensal social mobility: measuring no change, and upward/downward mobility between censuses. The relationship between mobility (2001-2011) and (separately) self-reported mental ill-health (MIH) at the 2011 Census and all-cause mortality (2011-2015) were examined using logistic regression and Cox PH modelling respectively. Results Population comprised 288,262 individuals aged 25-74 in 2011, recording 19,318 deaths (2011-2015) and 23,959 (8.3%) reporting MIH. MIH: those with no intercensal mobility followed the standard pathway associated with persisting disadvantage (comparing with the most advantaged the least advantaged recorded OR=16.13:95%CI=13.50,19.28); and while both the upwardly and downwardly mobile generally recorded higher ORs than those consistently most advantaged, the magnitude of ORs increased with social distance traversed; and ORs for downward mobility were consistently higher than with upward mobility. Patterns associated with all-cause mortality were similar. Conclusions This suggests: upward mobility retains something of the social patterning pertaining in social disadvantage levels left behind; downward mobility may be connected to ongoing health issues. Poor health outcomes remain strongly associated with socio-economic circumstance. Implications Research focusing on relationship between social mobility, disadvantage and health outcomes in NI is limited: access to more precise administrative data will enhance possibilities associated with evidence-based policy formation.