Dataset Information

Redistribution of garbage codes to underlying causes of death: a systematic analysis on Italy and a comparison with most populous Western European countries based on the Global Burden of Disease Study 2019.

ABSTRACT:

Background

The proportion of reported causes of death (CoDs) that are not underlying causes can be relevant even in high-income countries and seriously affect health planning. The Global Burden of Disease (GBD) study identifies these 'garbage codes' (GCs) and redistributes them to underlying causes using evidence-based algorithms. Planners relying on vital registration data will find discrepancies with GBD estimates. We analyse these discrepancies, through the analysis of GCs and their redistribution.

Methods

We explored the case of Italy, at national and regional level, and compared it to nine other Western European countries with similar population sizes. We analysed differences between official data and GBD 2019 estimates, for the period 1990-2017 for which we had vital registration data for most select countries.

Results

In Italy, in 2017, 33 000 deaths were attributed to unspecified type of stroke and 15 000 to unspecified type of diabetes, these making a fourth of the overall garbage. Significant heterogeneity exists on the overall proportion of GCs, type (unspecified or impossible underlying causes), and size of specific GCs among regions in Italy, and among the select countries. We found no pattern between level of garbage and relevance of specific GCs. Even locations performing below average show interesting lower levels for certain GCs if compared to better performing countries.

Conclusions

This systematic analysis suggests the heterogeneity in GC levels and causes, paired with a more detailed analysis of local practices, strengths and weaknesses, could be a positive element in a strategy for the reduction of GCs in Italy.

SUBMITTER: Monasta L

PROVIDER: S-EPMC9159332 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Publications

Redistribution of garbage codes to underlying causes of death: a systematic analysis on Italy and a comparison with most populous Western European countries based on the Global Burden of Disease Study 2019.

Monasta Lorenzo L Alicandro Gianfranco G Pasovic Maja M Cunningham Matthew M Armocida Benedetta B J L Murray Christopher C Ronfani Luca L Naghavi Mohsen M

European journal of public health 20220601 3

<h4>Background</h4>The proportion of reported causes of death (CoDs) that are not underlying causes can be relevant even in high-income countries and seriously affect health planning. The Global Burden of Disease (GBD) study identifies these 'garbage codes' (GCs) and redistributes them to underlying causes using evidence-based algorithms. Planners relying on vital registration data will find discrepancies with GBD estimates. We analyse these discrepancies, through the analysis of GCs and their r ...[more]

PMID: 35061890

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Project description:BackgroundReliable statistics on the underlying cause of death are essential for monitoring the health in a population. When there is insufficient information to identify the true underlying cause of death, the death will be classified using less informative codes, garbage codes. If many deaths are assigned a garbage code, the information value of the cause-of-death statistics is reduced. The aim of this study was to analyse the use of garbage codes in the Norwegian Cause of Death Registry (NCoDR).MethodsData from NCoDR on all deaths among Norwegian residents in the years 1996-2019 were used to describe the occurrence of garbage codes. We used logistic regression analyses to identify determinants for the use of garbage codes. Possible explanatory factors were year of death, sex, age of death, place of death and whether an autopsy was performed.ResultsA total of 29.0% (290,469/1,000,128) of the deaths were coded with a garbage code; 14.1% (140,804/1,000,128) with a major and 15.0% (149,665/1,000,128) with a minor garbage code. The five most common major garbage codes overall were ICD-10 codes I50 (heart failure), R96 (sudden death), R54 (senility), X59 (exposure to unspecified factor), and A41 (other sepsis). The most prevalent minor garbage codes were I64 (unspecified stroke), J18 (unspecified pneumonia), C80 (malignant neoplasm with unknown primary site), E14 (unspecified diabetes mellitus), and I69 (sequelae of cerebrovascular disease). The most important determinants for the use of garbage codes were the age of the deceased (OR 17.4 for age ≥ 90 vs age < 1) and death outside hospital (OR 2.08 for unknown place of death vs hospital).ConclusionOver a 24-year period, garbage codes were used in 29.0% of all deaths. The most important determinants of a death to be assigned a garbage code were advanced age and place of death outside hospital. Knowledge of the national epidemiological situation, as well as the rules and guidelines for mortality coding, is essential for understanding the prevalence and distribution of garbage codes, in order to rely on vital statistics.

Project description:BackgroundAmid shifting tobacco policies and escalating air pollution levels, Lung Cancer (LC) risk factors have changed notably. Continuous assessment of these risk factors is necessary. This study compares trends in tobacco, air pollution, and asbestos-associated Age-Standardized Mortality Rates (ASMR) from Trachea, Bronchus, and Lung (TBL) Cancer across the top ten most populated countries (2023 censuses) and globally.MethodsWe extracted overall and risk-factor-associated TBL cancer ASMR of the ten most populated countries for 1990-2019 from the Global Burden of Disease (GBD) database using the dedicated results tool (http://ghdx.healthdata.org/gbd-results-tool). GBD mapped the mortality data related to ICD codes (C33-C34, D02.1-D02.2, D38.1, 162-162.9, 231.1, 231.2, 231.8, 235.7 from ICD10 and B101 from ICD9). Tobacco, occupational exposure to asbestos and air pollution (ambient particulate matter and household air pollution) associated TBL cancer mortality data were extracted to evaluate the trends based on risk factors. We calculated relative changes in ASMRs between 1990 and 2019 for each sex in each country for each risk factor. Joinpoint regression analysis was performed to calculate the Estimated Annual Percentage Change (EAPC) and its corresponding 95% confidence interval (CI) for each line segment, allowing for trend assessment.FindingsGlobally, TBL Cancer mortality has decreased by 8%, with a decrease for males but an increase for females. Globally, both tobacco and air pollution-associated TBL cancer ASMR have decreased. While tobacco-associated ASMR has increased in China and Indonesia, air pollution-associated ASMR has also increased in China, India, Pakistan, and Nigeria. On stratification, while PM-associated mortality increased by 25% globally, household-associated TBL cancer ASMR decreased by 62%. China had the highest PM-associated TBL Cancer in 2019 (8.8/100,000), twice higher than the global average. Despite a decline in asbestos-associated TBL cancer ASMR from 8.91/100,000 to 6.0/100,000, the rate in the United States remained twice higher than the global average for the entire study period.InterpretationTobacco-associated TBL cancer mortality is declining but still predominant. Ambient particulate matter-associated TBL cancer mortality is rising, requiring policy and awareness efforts. Expanding access to preventive services and addressing underlying risk factors are essential steps required toward reducing lung cancer mortality at the global level.FundingThis study did not receive any funding support.

Project description:BackgroundRegistered causes in vital statistics classified as garbage codes (GC) are considered indicators of quality of cause-of-death data. Our aim was to describe temporal changes in this quality in Brazil, and the leading GCs according to levels assembled for the Global Burden of Disease (GBD) study. We also assessed socioeconomic differences in the burden of different levels of GCs at a regional level.MethodsWe extracted data from the Brazilian Mortality Information System from 1996 to 2016. All three- and four-digit ICD-10 codes considered GC were selected and classified into four categories, according to the GBD study proposal. GC levels 1 and 2 are the most damaging unusable codes, or major GCs. Proportionate distribution of deaths by GC levels according selected variables were performed. Age-standardized mortality rates after correction of underreporting of deaths were calculated to investigate temporal relationships as was the linear association adjusted for completeness between GC rates in states and the Sociodemographic Index (SDI) from the GBD study, for 1996-2005 and 2006-2016. We classified Brazilian states into three classes of development by applying tertiles cutoffs in the SDI state-level estimates.ResultsAge-standardized mortality rates due to GCs in Brazil decreased from 1996 to 2016, particularly level 1 GCs. The most important GC groups were ill-defined causes (level 1) in 1996, and pneumonia unspecified (level 4) in 2016. At state level, there was a significant inverse association between SDI and the rate of level 1-2 GCs in 1996-2005, but both SDI and completeness had a non-expected significant direct association with levels 3-4. In 2006-2016, states with higher SDIs tended to have lower rates of all types of GCs. Mortality rates due to major GCs decreased in all three SDI classes in 1996-2016, but GC levels 3-4 decreased only in the high SDI category. States classified in the low or medium SDI groups were responsible for the most important decline of major GCs.ConclusionOccurrence of major GCs are associated with socioeconomic determinants over time in Brazil. Their reduction with decreasing disparity in rates between socioeconomic groups indicates progress in reducing inequalities and strengthening cause-of-death statistics in the country.

Project description:BackgroundThis article presents the first detailed analysis of the prevalence and disability burden of Guillain-Barré syndrome (GBS) from 1990 to 2019 by cause, age, sex, and Socio-demographic Index (SDI) in 204 countries and territories.MethodsData from the Global Burden of Diseases Study (GBD) 2019 were used. GBD 2019 modelled the prevalence of GBS using hospital and claims data. Years lived with disability (YLDs) were estimated as the product of the GBS prevalence and the disability weight. This article also reported proportions in the age-standardised prevalence rate that were due to six underlying causes of GBS.ResultsIn 2019, there were 150,095 [95% uncertainty intervals (UI) 119,924 to 188,309] total cases of GBS worldwide, which resulted in 44,407 (95% UI 28,016 to 64,777) YLDs. Globally, there was a 6.4% (95% UI 3.6 to 9.5) increase in the age-standardised prevalence of GBS per 100,000 population between 1990 and 2019. High-income Asia Pacific [1.9 (95% UI: 1.5 to 2.4)] and East Asia [0.8 (95% UI: 0.6 to 1.0)] had the highest and lowest age-standardised prevalence rates (per 100,000), respectively, in 2019. Nationally, Japan [6.4 (95% UI: 5.3 to 7.7)] and China [0.8 (95% UI: 0.6 to 1.0)] had the highest and lowest age-standardised prevalence rates (per 100,000). The age-standardised burden of GBS increased with increasing age and was higher in males in all age groups. Furthermore, the age-standardised prevalence of GBS (per 100,000) had a positive association with the level of development, as measured by SDI, although this association was not strong. Upper respiratory infections and unknown causes accounted for the highest proportions of underlying causes.ConclusionsGlobally, the prevalence of GBS continues to increase. Geographical differences and strategies aimed at preventing infectious diseases should be considered in future health policy planning and decision-making processes. This study had several limitations, such as using the same disability weight for all causes and a reliance on hospital- and self-reported data, which should be addressed in future research.

Dataset Information

Redistribution of garbage codes to underlying causes of death: a systematic analysis on Italy and a comparison with most populous Western European countries based on the Global Burden of Disease Study 2019.

Background

Methods

Results

Conclusions

Publications

Redistribution of garbage codes to underlying causes of death: a systematic analysis on Italy and a comparison with most populous Western European countries based on the Global Burden of Disease Study 2019.

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