HEADS DATA Report

Investigation of Maternal Mortality in the Central and Western European Region between 2000 and 2019 - an analysis of the Global Burden of Disease 2019

Methods

Data Source

The primary data utilized in this study was obtained from the Global Burden of Disease Study 2019 (GBD 2019). The specific data extraction was conducted using the GBD Results Tool, an interface allowing comprehensive download of the full GBD results in CSV format.

Methods

Data Source:

The primary data utilized in this study was derived from the Global Burden of Disease Study 2019 (GBD 2019). We extracted specific datasets using the GBD Results Tool, a platform allowing for the comprehensive download of the complete GBD results in CSV format.

Citation for the data source: > Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD 2019) Results. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2020.

Query Tool Characteristics:

We tailored our data query from the GBD Results Tool as follows:

  • GBD Estimate: Cause of death or injury
  • Measures:
    • Deaths
    • Years of life lost (YLLs)
    • Maternal mortality ratio (MMR)
  • Metrics:
    • Number
    • Rate
    • Percent
  • Cause: Our investigation considered several maternal health causes, including:
    • Ectopic pregnancy
    • Indirect maternal deaths
    • Late maternal deaths
    • Maternal abortion and miscarriage
    • Maternal deaths aggravated by HIV/AIDS
    • Maternal disorders
    • Maternal hemorrhage
    • Maternal hypertensive disorders
    • Maternal obstructed labor and uterine rupture
    • Maternal sepsis and other maternal infections
    • Other maternal disorders
  • Time Span: Data from 1990-2019, with annual results for all measures considered.
  • Age Groups: The study focused on the following age groups:
    • 15-19
    • 20-24
    • 25-29
    • 30-34
    • 35-39
    • 40-44
    • 45-49
    • 50-54
    • 55-59
  • Sexes: Only data pertaining to females was considered.
  • Locations: Our geographical focus included the following countries and regions from Central and Western Europe:
    • Central Europe
    • Western Europe
    • Andorra
    • Norway
    • Austria
    • Portugal
    • Albania
    • Bosnia and Herzegovina
    • Belgium
    • Malta
    • Monaco
    • Slovakia
    • Bulgaria
    • Cyprus
    • Israel
    • Slovenia
    • Spain
    • Sweden
    • Netherlands
    • Italy
    • Denmark
    • Luxembourg
    • Switzerland
    • Finland
    • Czechia
    • Croatia
    • United Kingdom
    • San Marino
    • Iceland
    • Hungary
    • Romania
    • Serbia
    • France
    • Montenegro
    • Germany
    • North Macedonia
    • Greece
    • Ireland
    • Poland

Note on Geographical Representation:

Within our selected locations, “Central Europe” and “Western Europe” represent broader regions that encompass several individual countries. It’s essential to highlight that these broader regions might introduce data overlap with specific countries listed. We were attentive to this during our data analysis, ensuring that any interpretations or visualizations generated accounted for this overlap to prevent any duplication or skewing of results.

Statistical Analysis

The code was developed in R (version 4.2.3), using the integrated development environment (IDE) R Studio (version 2023.3.1.446, Cherry Blossom). (R Core Team, 2021 and RStudio Team, 2021)

Results

General Description of the Dataset

The dataset dataset.csv features:

  • 480480 rows (corresponding to observations)
  • 9 columns (corresponding to attributes)