OP0316 ASSOCIATION BETWEEN INDIVIDUAL AND COUNTRY-LEVEL SOCIOECONOMIC FACTORS AND WORK PARTICIPATION IN PERIPHERAL AND AXIAL SPONDYLOARTHRITIS: ANALYSIS OF THE ASAS perSpA Study
Authors: Zhao S. S. , Nikiphorou E. , Boonen A. , López-Medina C. , Dougados M. , Ramiro S. 
Published: May 2021

Background:

Work outcomes in spondyloarthritis (SpA) have mostly been studied in axSpA, less in peripheral SpA (pSpA) or PsA. The ASAS-COMOSPA study showed that lower education, female gender and lower healthcare expenditures (HCE) are associated with lower odds of employment in SpA. However, it is unknown whether country-level factors or SpA phenotype (axSpA/pSpA/PsA) modify the effect of individual-level socioeconomic factors.

Objectives:

To examine whether associations between socioeconomic factors and work outcomes differ across SpA phenotype and whether associations for individual-level socioeconomic factors are modified by country-level factors.

Methods:

Working age patients (18-65 years) from the ASAS-perSpA (peripheral involvement in SpA) study were included. Associations between individual- (age, gender, education, marital status) and country-level socioeconomic factors (Human Development Index (HDI), HCE) with work outcomes (employment status (binary), absenteeism, presenteeism (tertiles)) were assessed using mixed-effects logistic and ordinal logistic models. Models were adjusted for confounders. Separate models for ASDAS, BASFI and BASDAI were created in turn due to collinearity. Effect modification by SpA phenotype and country-level factors was tested using interaction terms.

Results:

A total of 3835 patients (mean age 42 years, 61% males) from 23 countries worldwide were included (66% axSpA, 10% pSpA, 23% PsA). Being employed was associated with gender (male vs female OR 2.5; 95%CI 1.9-3.2), education (university vs primary OR 3.7; 2.9-4.7) and being married (vs single OR 1.3; 1.04-1.6) (Table 1). University (vs primary) education was associated with lower odds of absenteeism (OR 0.7; 0.5-0.7) and presenteeism (OR 0.5; 0.3-0.7). Associations were not statistically different across SpA phenotypes. HCE was significantly associated with all work outcomes: employment (OR 2.5; 1.5-4.1), absenteeism (OR 0.6; 0.4-0.9) and presenteeism (OR 0.6; 0.3-0.9). HDI results were similar. Gender discrepancy in odds of employment was greater in countries with lower socioeconomic development; eg, males had 3.5 higher odds of employment than females in countries with low HCE, whereas the difference was 1.8 fold in high HCE countries.

Table 1.

Effect of individual socio-economic factors on work outcomes.

Employment status
OR (95% CI)Absenteeism
OR (95% CI)Presenteeism
OR (95% CI)N378022182127Age1.43 (1.36,1.51)1.00 (0.99,1.01)1.00 (0.99,1.01)Age20.996 (0.995, 0.996)NS - uniNS - uniMale (vs female)2.48 (1.92,3.21)1.22 (0.96,1.56)0.97 (0.78,1.20)EducationPrimaryrefrefrefSecondary1.86 (1.48,2.35)0.69 (0.49,0.99)0.69 (0.49,0.99)University3.68 (2.87,4.72)0.67 (0.47,0.96)0.49 (0.34,0.69)Marital statusSinglerefrefrefMarried1.27 (1.04,1.56)0.95 (0.73,1.22)0.98 (0.78,1.22)Divorced or Widowed1.39 (0.98,1.97)1.39 (0.88,2.18)1.16 (0.74,1.82)ASDAS0.78 (0.72,0.84)1.51 (1.33,1.72)2.31 (2.04,2.61)FatigueNS - multi1.14 (1.09,1.21)1.30 (1.24,1.36)Depression0.70 (0.59,0.82)1.45 (1.15,1.82)1.95 (1.59,2.39)FibromyalgiaNS - multi1.62 (1.11,2.35)1.58 (1.03,2.41)BMINS - multi0.99 (0.97,1.02)NS - multiDactylitis1.41 (1.12,1.76)NS - uniNS - uniUveitisNS - multi0.62 (0.46,0.84)NS - uniNSAIDsNS - multi1.53 (1.18,1.99)1.32 (1.07,1.64)bDMARDsNS - multiNS - uni1.23 (1.01,1.51)

Models used ASDAS rather than BASDAI/BASFI, which are collinear. NS, not significant in the univariable or multivariable model.

Conclusion:

Individual- (lower education) and country-level socioeconomic factors (lower healthcare expenditure) were both associated with (lower) work participation, independently of SpA phenotype. The disadvantageous effect of female gender on employment is particularly strong in countries with lower socioeconomic development. This highlights the need for wider societal interventions, such as improving education and healthcare investment, to improve work outcomes.

Disclosure of Interests:

Sizheng Steven Zhao: None declared, Elena Nikiphorou Speakers bureau: Pfizer, Lilly, AbbVie, Annelies Boonen Consultant of: Yes, Grant/research support from: Yes, Clementina López-Medina: None declared, Maxime Dougados: None declared, Sofia Ramiro Speakers bureau: Lilly, MSD, Novartis, UCB, Consultant of: AbbVie, Lilly, MSD, Novartis, UCB, Sanofi, Grant/research support from: MSD.