Allergic diseases and risk of incident autoimmune diseases: phenotype-specific patterns and multimorbidity effects in a nationwide cohort

# Zenodo repository README ## Repository title Allergic diseases and risk of incident autoimmune diseases: phenotype-specific patterns and multimorbidity effects in a nationwide cohort ## Related manuscript This repository accompanies the Clinical & Experimental Allergy Research Letter: **Allergic diseases and risk of incident autoimmune diseases: phenotype-specific patterns and multimorbidity effects in a nationwide cohort** ## Repository purpose Clinical & Experimental Allergy Research Letters do not allow supplementary files in the journal submission system. This repository provides the extended materials needed to document the study methods and results transparently. ## Files included - `methods and materials.pdf` Detailed Materials and Methods for the Research Letter. - `supplementary data.pdf` Supplementary tables and figure legends for the deposited repository materials. - `STROBE_checklist.pdf` Completed STROBE checklist for cohort studies. - `NHIS_HEALS_AllergyAutoimmune_final_code.sas` SAS 9.4 analysis code used for cohort construction, outcome/exposure definition, regression analyses, sensitivity analyses, subgroup analyses, and export of analytic result tables. ## Study overview We used the Korean National Health Insurance Service–National Health Screening Cohort (NHIS-HEALS) to evaluate whether allergic rhinitis, asthma, and atopic dermatitis were associated with incident autoimmune diseases in adults aged 40 years or older. Participants were screened in 2004–2005, allergic exposures were ascertained during 2002–2005, and follow-up extended from 1 January 2006 to 31 December 2013. The primary autoimmune outcomes were: - rheumatoid arthritis - Hashimoto's thyroiditis - Graves' disease - ankylosing spondylitis - ulcerative colitis - Crohn's disease - systemic lupus erythematosus ## Analytic overview Primary analyses used Cox proportional hazards models with sequential adjustment: - Model 1: unadjusted - Model 2: age and sex adjusted - Model 3: fully adjusted primary model Additional deposited analyses include: - Model 3b: Model 3 plus baseline healthcare utilisation - 3-year washout analysis - Fine–Gray competing-risk analysis - control-censoring analysis for incident allergic disease during follow-up - stricter case-definition analyses - proportional-hazards diagnostics and time-split Cox analyses - stratified analyses by sex, age group, smoking, alcohol consumption, and physical activity ## Software - SAS version 9.4 - Python version 3.11 for tables and figures ## Reproducibility notes The SAS script contains user-specific paths in **BLOCK 0**: - `LIBNAME a` - `LIBNAME b` - `OUTDIR` These paths must be edited before execution in a new environment. The code requires access to NHIS-HEALS source tables and cannot be run without approved data access. ## Data availability and restrictions The individual-level NHIS-HEALS data are **not publicly available**. Access is restricted and may be requested from the Korean National Health Insurance Service, subject to institutional review board approval and a data-use agreement. NHIS access portal: https://nhiss.nhis.or.kr ## Ethics The study was approved by the Institutional Review Board of Korea University Guro Hospital (No. 2024GR0390). ## Recommended citation for the repository Please cite both: 1. the associated journal article, and 2. this Zenodo repository DOI. ## Contact Corresponding author: **Hwamin Lee, PhD** Department of Biomedical Informatics, Korea University College of Medicine, Seoul, Republic of Korea Email: [e-mail]