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The geography of arthritis-attributable pain outcomes: a county-level spatial analysis. | LitMetric

The geography of arthritis-attributable pain outcomes: a county-level spatial analysis.

Pain

Department of Sociology, University at Buffalo, State University of New York, Buffalo, NY, United States.

Published: July 2024

Research on the geographic distribution of pain and arthritis outcomes, especially at the county level, is limited. This is a high-priority topic, however, given the heterogeneity of subnational and substate regions and the importance of county-level governments in shaping population health. Our study provides the most fine-grained picture to date of the geography of pain in the United States. Combining 2011 Behavioral Risk Factor Surveillance System data with county-level data from the Census and other sources, we examined arthritis and arthritis-attributable joint pain, severe joint pain, and activity limitations in US counties. We used small area estimation to estimate county-level prevalences and spatial analyses to visualize and model these outcomes. Models considering spatial structures show superiority over nonspatial models. Counties with higher prevalences of arthritis and arthritis-related outcomes are mostly clustered in the Deep South and Appalachia, while severe consequences of arthritis are particularly common in counties in the Southwest, Pacific Northwest, Georgia, Florida, and Maine. Net of arthritis, county-level percentages of racial/ethnic minority groups are negatively associated with joint pain prevalence, but positively associated with severe joint pain prevalence. Severe joint pain is also more common in counties with more female individuals, separated or divorced residents, more high school noncompleters, fewer chiropractors, and higher opioid prescribing rates. Activity limitations are more common in counties with higher percentages of uninsured people. Our findings show that different spatial processes shape the distribution of different arthritis-related pain outcomes, which may inform local policies and programs to reduce the risk of arthritis and its consequences.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11190894PMC
http://dx.doi.org/10.1097/j.pain.0000000000003155DOI Listing

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