A method for estimating infant mortality rate for Nepal

Area of Science:

• Demography
• Public Health
• Biostatistics

Background:

• Infant Mortality Rate (IMR) is a key indicator of a nation's health and development.
• Accurate IMR estimation is crucial for effective public health interventions in Nepal.
• Existing methods for IMR estimation may require extensive data not always available.

Purpose of the Study:

• To develop and validate a regression model for estimating Nepal's Infant Mortality Rate (IMR).
• To utilize minimal yet relevant demographic parameters: Life Expectancy at Birth (LEB) and Life Expectancy at Age One (LEAO).
• To provide a practical tool for IMR estimation when comprehensive data is limited.

Main Methods:

• A novel regression model was proposed to derive Life Expectancy at Age One (LEAO) estimates.
• Life Expectancy at Birth (LEB) data was sourced from various reliable databases.
• Model validity was assessed through historical data application, cross-source comparison, and statistical adequacy tests.

Main Results:

• The proposed regression model demonstrated satisfactory performance in estimating IMR for Nepal.
• The model yielded an IMR estimate of 70.6 per thousand live births for Nepal in 2003.
• This estimate closely aligned with figures reported by other reputable sources, confirming model accuracy.

Conclusions:

• The developed regression model is suitable for estimating Infant Mortality Rate (IMR) in Nepal.
• The model provides reliable IMR estimates when accurate Life Expectancy at Birth (LEB) and Life Expectancy at Age One (LEAO) data are available.
• This approach offers a valuable method for monitoring and addressing infant mortality in data-scarce settings.