Pain Trends Among American Adults, 2002-2018: Patterns, Disparities, and Correlates

Abstract

Determining long-term trends in chronic pain prevalence is critical for evaluating and shaping U.S. health policies, but little research has examined such trends. This study (1) provides estimates of pain trends among U.S. adults across major population groups; (2) tests whether sociodemographic disparities in pain have widened or narrowed over time; and (3) examines socioeconomic, behavioral, psychological, and medical correlates of pain trends. Regression and decomposition analyses of joint, low back, neck, facial/jaw pain, and headache/migraine using the 2002-2018 National Health Interview Survey for adults aged 25-84 (N = 441,707) assess the trends and their correlates. We find extensive escalation of pain prevalence in all population subgroups: overall, reports of pain in at least one site increased by 10%, representing an additional 10.5 million adults experiencing pain. Socioeconomic disparities in pain are widening over time, and psychological distress and health behaviors are among the salient correlates of the trends. This study thus comprehensively documents rising pain prevalence among Americans across the adult life span and highlights socioeconomic, behavioral, and psychological factors as important correlates of the trends. Chronic pain is an important dimension of population health, and demographic research should include it when studying health and health disparities.

Keywords: Chronic pain; Health disparities; Socioeconomic; Trend; U.S. adults.

Fig. 1

Pain trends 2002–2018 for U.S. adults ages 25–84. Results from a semiparametric age- and sex-stratified, demographics-adjusted logistic model of “any pain.”

Fig. 2

Contribution of changes in composition, by age group. The figure shows coefficients and their 95% confidence intervals (CIs) estimating the contribution of compositional differences between 2002–2004 and 2016–2018 populations to pain prevalence differences. For several estimates, the standard errors are small enough that the plotted CI is not clearly visible around the point estimate.