TY - JOUR
T1 - Impact of redistributing deaths by ill-defined causes in oral and oropharyngeal cancer mortality in Brazil
AU - Da Cunha, Amanda Ramos
AU - Bigoni, Alessandro
AU - Antunes, José Leopoldo Ferreira
AU - Hugo, Fernando Neves
N1 - Publisher Copyright:
© 2022,Communications in Number Theory and Physics. All Rights Reserved.
PY - 2022
Y1 - 2022
N2 - Less-than-optimal reliability of mortality information systems regarding the underlying cause of death can mask the reality of oral (OC) and oropharyngeal cancer (OPC) mortality. This study aimed to assess the impact on the magnitude and temporal trends of OC and OPC mortality in Brazil of two statistical approaches to redistribute deaths with ill-defined underlying causes. We analyzed deaths with ill-defined causes in Brazil by macro-region, between 1996-2018. The Mortality Information System provided official information on deaths. Two correction methods were applied: the EF method, which proportionally reallocates deaths classified as R00-R99 in the ICD-10 to the remaining specific causes of death according to the proportion of deaths with certified causes; and the GBD method, which considers the concept of garbage codes, redistributing deaths from several ICD-10 chapters according to previously established coefficients. For the trend analysis of mortality (certified and redistributed), the Prais-Winsten method was carried out. The OC and OPC death rates had an evident increase after the redistribution by the two techniques in all regions of the country; the increase was higher using the GBD method. In the Northeast and North regions, this method more than doubled the certified death rates. The redistribution methods also changed time series trends. In epidemiological studies of mortality from OC and OPC, it is necessary to redistribute deaths from ill-defined causes when analyzing data from less-than-optimal information systems. The choice of the correction method is critical; epidemiological studies must manage it as a methodological decision that has significant impacts on results.
AB - Less-than-optimal reliability of mortality information systems regarding the underlying cause of death can mask the reality of oral (OC) and oropharyngeal cancer (OPC) mortality. This study aimed to assess the impact on the magnitude and temporal trends of OC and OPC mortality in Brazil of two statistical approaches to redistribute deaths with ill-defined underlying causes. We analyzed deaths with ill-defined causes in Brazil by macro-region, between 1996-2018. The Mortality Information System provided official information on deaths. Two correction methods were applied: the EF method, which proportionally reallocates deaths classified as R00-R99 in the ICD-10 to the remaining specific causes of death according to the proportion of deaths with certified causes; and the GBD method, which considers the concept of garbage codes, redistributing deaths from several ICD-10 chapters according to previously established coefficients. For the trend analysis of mortality (certified and redistributed), the Prais-Winsten method was carried out. The OC and OPC death rates had an evident increase after the redistribution by the two techniques in all regions of the country; the increase was higher using the GBD method. In the Northeast and North regions, this method more than doubled the certified death rates. The redistribution methods also changed time series trends. In epidemiological studies of mortality from OC and OPC, it is necessary to redistribute deaths from ill-defined causes when analyzing data from less-than-optimal information systems. The choice of the correction method is critical; epidemiological studies must manage it as a methodological decision that has significant impacts on results.
KW - Health information systems
KW - Mortality
KW - Mouth neoplasms
KW - Oropharyngeal neoplasms
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U2 - 10.1590/1807-3107bor-2022.vol36.0117
DO - 10.1590/1807-3107bor-2022.vol36.0117
M3 - Article
C2 - 36287428
AN - SCOPUS:85140621878
SN - 1806-8324
VL - 36
JO - Brazilian Oral Research
JF - Brazilian Oral Research
M1 - e117
ER -