An application of matching algorithms to generalize small-area estimates of chronic pain prevalence to neighbourhoods across England.

ABSTRACT:

Background

Local decision-makers lack granular data on the prevalence of chronic pain in their populations. We applied matching methods to generalize estimates from one local survey in England to other neighborhoods across the country with a similar sociodemographic composition.

Methods

We used propensity score matching to match lower-layer super output areas (LSOA) across England with 230 surveyed LSOAs in North Staffordshire by age, sex, ethnicity, deprivation, and rurality. LSOA-specific crude prevalence of chronic pain and high-impact chronic pain in adults aged 35+ years were estimated and mapped for matched LSOAs.

Results

Satisfactory matching was achieved for 24 871 of 31 580 LSOAs (79%). The 6709 LSOAs identified as either "off common support" or unmatched wer

SUBMITTER: Quinn L 

PROVIDER: S-EPMC12123305 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature