Patterns of Geographic Variation of Mortality by Causes of Death for Small Areas in Brazil, 2010

Queiroz, Bernardo Lanza; Freire, Flávio Henrique Miranda de Araújo; Lima, Everton Emanuel Campos de; Gonzaga, Marcos Roberto; Baptista, Emerson Augusto

doi:10.1007/978-3-030-57069-9_20

Cited by 5 publications

(7 citation statements)

References 44 publications

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“…Figure 2 shows the spatial distribution of infant (1q0) and adult (45q15) male mortality probabilities for Brazilian municipalities. Both mortality indicators show the heterogeneity in mortality risk across macro-regions, as observed by others [26,51,51,54]. The lower map shows a higher adult mortality risk in the proximity of the state capitals, especially in the northeast macro-region.…”

Section: Resultssupporting

confidence: 67%

“…In other words, in addition to measuring uncertainties in rates by age, our approach also adjusts the estimated rates correcting for the under-registration of death records. In São Paulo, the largest municipality in Brazil, where death records are almost complete [18,26,37], the estimated rates are very close to those observed. In fact, according to Figure S1 (see supplementary information), the completeness of death estimates in almost all small areas in the south and some areas in the southeast or central-west macro-regions have complete death records (completeness of death records estimates close to 1) and, therefore, the only source of uncertainty in the estimated mortality rates in these areas is due to the small number of events.…”

Section: Resultssupporting

confidence: 65%

“…Municipal level mortality estimates in 2010, as expressed by life expectancy at birth, infant mortality (1q0), and adult mortality probabilities (45q15), were significantly different across and within Brazil's macro-regions. We observed an increased mortality risk among adults in the proximity of the state capitals, especially in the northeast macro-region, possibly related to mortality by external causes such as homicide and transport accidents [26,50,51,55,56]. In addition, we observed the highest infant mortality rates in the north and northeast macroregions compared to the rest of Brazil.…”

Section: Discussionmentioning

confidence: 60%

“…However, in Brazil, mortality rates are affected due to the incompleteness of vital records [17,19,21]. Despite significant improvements in vital register quality at the national level in the last few decades, the lack of complete death records remains a considerable challenge in most of Brazil's less developed areas, particularly the north and northeast macro-regions [21,26].…”

Section: Introductionmentioning

confidence: 99%

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Estimation and projection of probabilistic age- and sex-specific mortality rates across Brazilian municipalities between 2010 and 2030

Gonzaga¹,

Queiroz²,

Silva³

et al. 2022

Preprint

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Background: Small area age- and sex-specific mortality rates are useful measures for population projections, health, economic, and social planning. Mortality rate estimation in small areas can be difficult due the low number of events/exposure. If a country’s mortality registration has problems, such as incomplete information, then estimating mortality rates can be even more difficult. Previous studies in Brazil have combined demographic and statistical methods to overcome these issues. These approaches depend on a gold standard for age-specific mortality rates and do not estimate uncertainties. We estimated age- and sex-specific mortality rates for all 5,565 Brazilian municipalities in 2010, and forecasted mortality rates between 2010 and 2030. Methods: We used the Tool for Projecting Age-Specific Rates Using Linear Splines (TOPALS) and a Bayesian model to estimate age- and sex-specific mortality rates in all Brazilian municipalities in 2010 while incorporating two types of uncertainties: low exposure and incomplete coverage of death counts. We adapted the Lee-Carter model to forecast age- and sex-specific mortality rates between 2010 and 2030 for all municipalities. Results: The proposed methodology was robust in adjusting for the mortality age profile and in estimating mortality rate uncertainties at the municipal level. The forecasted mortality rates indicated a convergence in life expectancy at birth, and variability of age at death across Brazil’s municipalities, with a persistent sex differential. Conclusion: We estimated and forecasted mortality rates in small areas with limited and incomplete death counts, and high mortality heterogeneity. The methodological approach applied could be useful for countries with death data quality problems similar to Brazil. Our results incorporated the main sources of uncertainty in estimating age- and sex-specific mortality rates and could be used as an important input for policy planning at the municipal level.

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Section: Resultssupporting

confidence: 67%

Section: Resultssupporting

confidence: 65%

Section: Discussionmentioning

confidence: 60%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Estimation and projection of probabilistic age- and sex-specific mortality rates across Brazilian municipalities between 2010 and 2030

Gonzaga¹,

Queiroz²,

Silva³

et al. 2022

Preprint

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“…As addressed by other studies 20 , we examined the changes in death profiles, from five ICD-10 chapters, that mainly affect the country namely: infectious and parasitic diseases, cardiovascular diseases, neoplasms, respiratory infections, and external causes, using yearly data from 2000 to 2016. Our aim was to determine if there are spatial clusters of patterns in mortality from each of these causes of death overtime and to ascertain if the clusters are consistent over the years in specific municipalities.…”

Section: Introductionmentioning

confidence: 99%

A spatio-temporal analysis of cause-specific mortality in São Paulo State, Brazil

Gayawan

Lima

2022

Ciênc. saúde coletiva

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Using five cause-specific mortality data sourced by the Brazilian Ministry of Health, and over 17 years period, we applied Bayesian spatio-temporal models on 644 municipalities of the state of São Paulo, using logistic model to the binary outcome that specifies whether or not the death was from a specific cause. We modeled the temporal mortality effects using B-splines, while the spatial components were considered through Gaussian and Markov random field, and inference was based on Markov chain Monte Carlo simulation. The results demonstrate consistent downward trend in mortality from infectious and parasitic diseases and external causes, while those from neoplasms and respiratory are rising. Cardiovascular is the only cause-specific death that is kept constant in time. All the causes of death considered show heterogeneous spatial and temporal variations among the municipalities, which sometimes change considerably within successive years. Mortality from infectious diseases clustered around the Northwestern municipalities in 2000, but changes to the Southeastern part in 2016, a similar development as external death causes. The study identifies areas with increased and decreased odds mortality and could be useful in disease monitoring, especially if we consider small spatial units.

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Estimation and probabilistic projection of age- and sex-specific mortality rates across Brazilian municipalities between 2010 and 2030

Gonzaga,

Queiroz,

Freire

et al. 2024

Popul Health Metrics

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Background Mortality rate estimation in small areas can be difficult due the low number of events/exposure (i.e. stochastic error). If the death records are not completed, it adds a systematic uncertainty on the mortality estimates. Previous studies in Brazil have combined demographic and statistical methods to partially overcome these issues. We estimated age- and sex-specific mortality rates for all 5,565 Brazilian municipalities in 2010 and forecasted probabilistic mortality rates and life expectancy between 2010 and 2030. Methods We used a combination of the Tool for Projecting Age-Specific Rates Using Linear Splines (TOPALS), Bayesian Model, Spatial Smoothing Model and an ad-hoc procedure to estimate age- and sex-specific mortality rates for all Brazilian municipalities for 2010. Then we adapted the Lee-Carter model to forecast mortality rates by age and sex in all municipalities between 2010 and 2030. Results The adjusted sex- and age-specific mortality rates for all Brazilian municipalities in 2010 reveal a distinct regional pattern, showcasing a decrease in life expectancy in less socioeconomically developed municipalities when compared to estimates without adjustments. The forecasted mortality rates indicate varying regional improvements, leading to a convergence in life expectancy at birth among small areas in Brazil. Consequently, a reduction in the variability of age at death across Brazil’s municipalities was observed, with a persistent sex differential. Conclusion Mortality rates at a small-area level were successfully estimated and forecasted, with associated uncertainty estimates also generated for future life tables. Our approach could be applied across countries with data quality issues to improve public policy planning.

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Patterns of Geographic Variation of Mortality by Causes of Death for Small Areas in Brazil, 2010

Cited by 5 publications

References 44 publications

Estimation and projection of probabilistic age- and sex-specific mortality rates across Brazilian municipalities between 2010 and 2030

Estimation and projection of probabilistic age- and sex-specific mortality rates across Brazilian municipalities between 2010 and 2030

A spatio-temporal analysis of cause-specific mortality in São Paulo State, Brazil

Estimation and probabilistic projection of age- and sex-specific mortality rates across Brazilian municipalities between 2010 and 2030

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