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Applying burden of disease methods in developing countries: a case study from Pakistan.
1Department of International Health, School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA. ahyder@jhsph.edu
Assessing disease burden in Pakistan using the Healthy Life-Year (HeaLY) indicator revealed childhood and infectious diseases as major contributors. This method offers a framework for national health assessment, though data quality remains a challenge in developing nations.
Area of Science:
- Global Health
- Epidemiology
- Public Health Indicators
Background:
- Composite indicators like Disability-Adjusted Life-Year (DALY) and Healthy Life-Year (HeaLY) measure disease burden by integrating mortality and morbidity.
- These indicators are crucial for understanding health loss in national contexts, particularly in resource-poor settings.
Purpose of the Study:
- To evaluate the application of HeaLY and DALY in a developing country (Pakistan).
- To assess the loss of healthy life from prevalent conditions in Pakistan.
- To explore the utility of these composite indicators in resource-limited national health systems.
Main Methods:
- A comprehensive dataset for Pakistan was compiled from 180 sources, covering population and disease parameters.
- The Healthy Life-Year (HeaLY) approach was employed to quantify the loss of healthy life due to premature mortality and disability in 1990.
- Data were categorized by 58 distinct health conditions.
Main Results:
- Childhood and infectious diseases accounted for two-thirds of the total disease burden in Pakistan.
- Chronic diseases and injuries were identified among the top 10 causes of HeaLY loss.
- Disease trends in Pakistan showed consistency with regional estimates for both communicable and non-communicable diseases.
Conclusions:
- Composite indicators, such as HeaLY, are effective for assessing disease burden in developing countries like Pakistan.
- The HeaLY method provides a structured approach for national health information assessment.
- Acquiring high-quality, disease- and population-specific data presents the primary challenge for implementing such health assessment methods in developing regions.
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