Published August 24, 2026 | Version 2.0

Analysis code for: Industrialization and low back pain among two traditionally small-scale subsistence societies

Authors/Creators

  • 1. Harvard University

Description

R code for the analyses of low back pain prevalence and risk factors across four populations (Orang Asli, Turkana, Tsimané, Rarámuri). Descriptive prevalence estimation uses binomial GAMs with sex-specific penalised splines of age and marginal standardisation. Causal effect estimation uses covariate balancing weights (optimisation-based balancing weights and energy balancing via WeightIt) with G-computation to produce average exposure-response functions (AERFs) and average marginal effect functions (AMEFs), and parametric simulation (clarify) for between-population contrasts. Version 2.0 reorganises the code, fixes three run-time defects present in v1.0 (none affecting published estimates), corrects method descriptions in comments, and adds an renv lockfile pinning the software versions stated in the paper.

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stevenworthington/low-back-pain-industrialization-v2.0.zip

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References
Dataset: 10.5281/zenodo.19740939 (DOI)