2022
DOI: 10.3389/fcvm.2022.941917
|View full text |Cite
|
Sign up to set email alerts
|

The projections of global and regional rheumatic heart disease burden from 2020 to 2030

Abstract: BackgroundRheumatic heart disease (RHD) remains the leading cause of preventable death and disability in children and young adults, killing an estimated 320,000 individuals worldwide yearly.Materials and methodsWe utilized the Bayesian age-period cohort (BAPC) model to project the change in disease burden from 2020 to 2030 using the data from the Global Burden of Disease (GBD) Study 2019. Then we described the projected epidemiological characteristics of RHD by region, sex, and age.ResultsThe global age-standa… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
11
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
8
1
1

Relationship

0
10

Authors

Journals

citations
Cited by 17 publications
(12 citation statements)
references
References 56 publications
0
11
0
Order By: Relevance
“…Finally, the Bayesian age-period-cohort analysis (BAPC) model with integrated nested Laplace approximation (INLA) was also used to predict the cataract prevalence trend from 2020 to 2030 in China and globally. 15,16…”
Section: Discussionmentioning
confidence: 99%
“…Finally, the Bayesian age-period-cohort analysis (BAPC) model with integrated nested Laplace approximation (INLA) was also used to predict the cataract prevalence trend from 2020 to 2030 in China and globally. 15,16…”
Section: Discussionmentioning
confidence: 99%
“…Our methodology comprised two primary steps: Firstly, we collected data on mortality and DALYs rates for colorectal cancer attributable to diet high in red meat across all age brackets (categorized in 5-year intervals) globally and regionally from 1990 to 2019. Subsequently, by applying a specific formula—the ratio of mortality (or DALYs) cases to the corresponding rate for all age groups in the same year—we recalibrated the annual total populations ( 36 ). Following this, we utilized the Bayesian Age-Period-Cohort (BAPC) model to project the disease burden from 2020 to 2030.…”
Section: Methodsmentioning
confidence: 99%
“…Our methodology involved two key steps: Initially, we gathered data on the incidence and Years Lived with Disability (YLD) for spinal cord injuries across all age brackets (segmented in 5-year intervals) at both global and regional scales for the years 1990 to 2019. Subsequently, applying a specific formula – the ratio of incidence (or YLD) cases to the corresponding rate for all age groups in the same year – we recalculated the corresponding annual total populations ( 38 ). Following this, we employed the Bayesian Age-Period-Cohort (BAPC) model to project the disease burden from 2020 to 2030.…”
Section: Methodsmentioning
confidence: 99%