GERD and Asthma Co-Burden Patterns Across Three Global Regions

Figshare hosts a dataset analyzing the co-occurrence and drivers of gastroesophageal reflux disease (GERD) and asthma across East Asia, Tropical Latin America, and High-income North America. It uses Global Burden of Disease 2023 estimates from 1994 to 2023, with forecasts to 2033, to examine regional trends, age-specific associations, and shared metabolic and lifestyle risk factors.

Use Cases

• Analyze regional trends in GERD and asthma age-standardised prevalence from 1994 to 2023 using Joinpoint regression-derived AAPC metrics.
• Model associations between disease burden and risk factors like diet high in red meat, high fasting plasma glucose, and sugar-sweetened beverages using negative binomial regression outputs.
• Investigate geographic heterogeneity in driver-disease relationships, such as the opposing association of fasting glucose with asthma across regions, via exposure × region interaction models.
• Forecast GERD and asthma burden for 2024–2033 using ETS/ARIMA methods applied to the historical time series.

Strengths

• Data is derived from the authoritative Global Burden of Disease (GBD) 2023 estimates.
• Analysis covers a 30-year time range from 1994 to 2023 and includes forecasts to 2033.
• Compares three distinct global regions: East Asia, Tropical Latin America, and High-income North America.
• Employs multiple analytical methods including Spearman correlation, Joinpoint regression, Random Forest with SHAP, and structural equation modelling.

Limitations

• The dataset is very small at 12.8 KB, indicating it likely contains summary or model results, not the underlying raw case-level data.
• Specific row count, column names, and sample data are unavailable, limiting understanding of the data's granular structure.
• Geographic coverage is limited to three specific regions, not a globally comprehensive sample.

Provenance

Source

Global Burden of Disease (GBD) 2023 estimates

Collection Method

Multi-method analysis including correlation, regression, forecasting, and machine learning screening applied to GBD estimates.

Time Range

1994–2023, with forecasts for 2024–2033

Freshness

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Geography

East Asia, Tropical Latin America, High-income North America