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Published on: October 23, 2020
A logistic regression model for estimating transport accident deaths using verbal autopsy data
Nuntaporn Klinjun1, Apiradee Lim2, Kanitta Bundhamcharoen3
1Prince of Songkla University, Muang, Thailand.
This study developed a model using verbal autopsy (VA) data to better estimate transport accident deaths in Thailand. The model found significantly more deaths than vital registration data suggests.
Area of Science:
- Public Health
- Epidemiology
- Biostatistics
Background:
- Accurate estimation of transport accident deaths is crucial for public health interventions.
- Vital registration data in Thailand may underestimate the true burden of transport accident fatalities.
- Verbal autopsy (VA) offers a method to assess causes of death in populations with limited medical certification.
Purpose of the Study:
- To develop and validate a statistical model using verbal autopsy (VA) data to estimate transport accident deaths in Thailand.
- To compare the model's estimates with existing vital registration data.
- To identify potential underestimation of transport accident mortality in official records.
Main Methods:
- Utilized a dataset of 9644 verbal autopsy (VA) deaths from Thailand.
- Employed logistic regression to model transport accident deaths based on demographic, geographic, and cause-of-death variables.
- Validated the model using receiver operating characteristic (ROC) curve analysis to determine sensitivity and false positive rates.
Main Results:
- Verbal autopsy (VA) identified 546 transport accident deaths (5.7%) within the sample.
- The developed model achieved a sensitivity of 73.8% and a false positive rate of 1.6%.
- Estimated transport accident deaths were 1.68 to 2.65 times higher than reported in vital registration data, varying by gender-age groups.
Conclusions:
- The verbal autopsy (VA) based model provides a more comprehensive estimation of transport accident deaths in Thailand.
- Vital registration data significantly underestimates transport accident mortality.
- The findings highlight the need for improved death registration and cause-of-death ascertainment for transport accidents.
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