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Publications

Journal Article Epublish

PubMed: 42922795 DOI: 10.1590/S2237-96222026v35e20251137.en

Garbage codes as the underlying cause of death: a cross-sectional study, state of Rio de Janeiro, 1998-2023.

Epidemiol Serv Saude 35:e20251137

Authors: Luciana Freire de Carvalho

Affiliations

  • Universidade Federal do Rio de Janeiro Instituto de Ciências Médicas MacaéRJ Brazil Universidade Federal do Rio de Janeiro, Instituto de Ciências Médicas, Macaé, RJ, Brazil. Universidade Estácio de Sá Faculdade de Medicina Rio de JaneiroRJ Brazil Universidade Estácio de Sá, Faculdade de Medicina, Rio de Janeiro, RJ, Brazil.

Abstract

OBJECTIVES

To describe the temporal evolution and geographic distribution of deaths due to garbage codes, as well as to analyze the prevalence and characteristics associated with the occurrence of garbage codes as the underlying cause of death in the state of Rio de Janeiro between 1998 and 2023.

METHODS

Cross-sectional study of deaths among residents of the state obtained from the Brazilian Mortality Information System (Sistema de Informações sobre Mortalidade, SIM). Garbage codes were classified according to the methodology of the Global Burden of Disease Study. Descriptive analyses of temporal evolution and distribution by municipalities were conducted. The associations with sociodemographic variables, place of occurrence, and health region were analyzed using Poisson regression with robust variance and described using prevalence ratios (PR) and their respective 95% confidence intervals (95%CI).

RESULTS

Of the 3,399,380 deaths, 1,510,135 (44.4%) were classified as garbage codes. The proportion remained high, ranging from 48.0% (1998) to 46.3% (2023), with a transient reduction to 38.1% in 2021. Level 1 (worst quality) accounted for the highest proportion (22.9%). Higher prevalences were associated with unknown sex (PR 1.18; 95%CI 1.11; 1.23), Black (PR 1.17; 95%CI 1.16; 1.17) and Indigenous race/skin color (PR 1.16; 95%CI 1.10; 1.22), age group ≥80 years (PR 1.74; 95%CI 1.71; 1.75), and deaths with unknown place of occurrence (PR 1.30; 95%CI 1.25; 1.34).

CONCLUSION

Half of the deaths had the underlying cause recorded as a garbage code, with higher prevalence among unknown sex and place of occurrence, older adults, and Black and Indigenous race/skin color. Active investigation, algorithm-based redistribution, and database integration are promising for improving data quality.

MeSH

Skin, Cross-Sectional Studies, Garbage, Cause Of Death, Prevalence, Sex, Skin Pigmentation