Disability, Poverty, and Compounded Risk: Operationalizing Intersectionality to Examine Race, Gender, and Socioeconomic Status As Predictors of Frequent Chronic Musculoskeletal Pain

Background and Purpose: Chronic musculoskeletal pain disproportionately burdens marginalized populations, yet most existing research examines race, gender, and socioeconomic status as independent predictors rather than as mutually constitutive systems of inequality (Boerner et al., 2025). This methodological limitation obscures cumulative disadvantage. Intersectionality demands that social positions be examined jointly, not additively; realizing this in quantitative research requires explicit methodological choices. This study operationalized intersectionality through multiplicative interaction modeling to examine how race/ethnicity, gender, and poverty status were associated with frequent chronic musculoskeletal pain in a nationally representative U.S. adult sample, while also identifying disability as a structural predictor of exceptional magnitude, accurately characterizing who bears disproportionate pain burden.

Methods: Secondary data from the 2023 National Health Interview Survey (NHIS; n = 16,210; N = 137,081,129) were analyzed using binary logistic regression. The dependent variable was frequent chronic pain (most days or every day vs. some days). An intersectional identity variable was constructed representing the joint configuration of race/ethnicity, gender, and poverty status. Age, depression frequency, anxiety frequency, and disability status were included as controls. The person-level NHIS sampling weight was applied to produce population-representative estimates. Multiplicative interaction terms operationalized intersectionality.

Results: The final model was statistically significant (χ² = 18,879,329.040, df = 19, p < .001; Nagelkerke R² = .177) and correctly classified 70.7% of cases. Disability status emerged as the single strongest predictor in the model; adults with an indicated disability had more than three times the odds of frequent chronic pain compared with non-disabled adults (OR = 3.263, p < .001). This finding demands attention; disability's relationship with chronic pain is so structurally entangled that its effect exceeds that of every demographic and socioeconomic variable examined. Among the intersectional identity findings, Non-Hispanic White individuals below the poverty threshold had 1.452 times the odds of frequent pain compared with their above-poverty counterparts (OR = 1.452, p < .001), while adults from all other racial and ethnic groups above the poverty threshold showed substantially different odds (OR = 0.589, p < .001); additive models would have obscured this multiplicative pattern. Age demonstrated a strong monotonic gradient, with odds rising from OR = 1.395 (ages 31–40) to OR = 3.558 (ages 61–70) relative to adults aged 18–30. Daily anxiety (OR = 2.039) and monthly-to-daily depression (OR = 1.805) were also strong independent predictors.

Conclusions and Implications: The whole of intersectional disadvantage exceeds the sum of its parts; poverty's effect on chronic pain differs by race, and no single-axis analysis could have revealed that pattern. The disability finding calls on social work researchers to place disability at the center of chronic pain inquiry. Methodologically, this study demonstrates that quantitative intersectionality, implemented through multiplicative interaction terms in nationally representative data, is both feasible and necessary for accurate characterization of structural health inequities. These findings support insurance reform, anti-discrimination policy, and upstream investment in the social determinants driving pain disparities. Social work must lead this research agenda.