title: Sociodemographic disparities in chronic pain, based on 12-year longitudinal data.
abstract: Existing estimates of sociodemographic disparities in chronic pain in the United States are based on cross-sectional data, often treat pain as a binary construct, and rarely test for nonresponse or other types of bias. This study uses 7 biennial waves of national data from the Health and Retirement Study (1998-2010; n = 19,776) to describe long-term pain disparities among older (age 51+) American adults. It also investigates whether pain severity, reporting heterogeneity, survey nonresponse, and/or mortality selection might bias estimates of social disparities in pain. In the process, the article clarifies whether 2 unexpected patterns observed cross-sectionally-plateauing of pain above age 60, and lower pain among racial/ethnic minorities-are genuine or artefactual. Findings show high prevalence of chronic pain: 27.3% at baseline, increasing to 36.6% thereafter. Multivariate latent growth curve models reveal extremely large disparities in pain by sex, education, and wealth, which manifest primarily as differences in intercept. Net of these variables, there is no racial/ethnic minority disadvantage in pain scores, and indeed a black advantage vis-à-vis whites. Pain levels are predictive of subsequent death, even a decade in the future. No evidence of pain-related survey attrition is found, but surveys not accounting for pain severity and reporting heterogeneity are likely to underestimate socioeconomic disparities in pain. The lack of minority disadvantage (net of socioeconomic status) appears genuine. However, the age-related plateauing of pain observed cross-sectionally is not replicated longitudinally, and seems partially attributable to mortality selection, as well as to rising pain levels by birth cohort.
authors.affiliation: Department of Sociology, University at Buffalo, State University of New York, Buffalo, NY, USA.
authors.forename: Hanna
authors.initials: H
authors.lastname: Grol-Prokopczyk
mesh_terms: D017677:Age Distribution; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002908:Chronic Disease / Q000453:epidemiology* / Q000208:ethnology / Q000628:therapy*; D005006:Ethnicity; D005260:Female; D054625:Healthcare Disparities / Q000706:statistics & numerical data; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D012737:Sex Factors; D012923:Social Class