Completeness Assessment of Neonatal Deaths in a Region of Brazil: Linkage and Imputing Missing Data
Neir Antunes Paes (),
Carlos Sérgio Araújo dos Santos () and
Tiê Dias de Farias Coutinho ()
Additional contact information
Neir Antunes Paes: Federal University of Paraíba, Health and Decision Modelling Postgraduate Course
Carlos Sérgio Araújo dos Santos: Federal University of Paraíba, Health and Decision Modelling Postgraduate Course
Tiê Dias de Farias Coutinho: Federal University of Paraíba, Health and Decision Modelling Postgraduate Course
Chapter Chapter 13 in Quantitative Methods in Demography, 2022, pp 207-217 from Springer
Abstract:
Abstract Although coverage of neonatal deaths in Brazil is considered high, the completeness of death declaration items for several regions is a problem of concern and uncertainty, which can compromise the maternal and child health planning. Data set linkage offers considerable potential to address an extensive range of research questions, such as identifying risk factors, and quantifying mortality, morbidity and healthcare for infant health as in the neonatal period. This technique added to imputing missing data techniques is a feasible and cost-efficient way to recover data. The main aim of this paper is to evaluate the completeness of information on neonatal death declarations in the regions of Paraíba State from 2009 to 2017. The quality of data on neonatal deaths declaration was studied in two stages: in the first, the Mortality Information System and Birth Information System from the Brazilian Ministry of Health databases were matched using the deterministic linkage; in the second, the multiple imputation for missing data was carry out. In total, 5149 neonatal deaths were computed. The following variables were investigated: gender, race/color, mother’s age, weeks of gestation, birth weight, mother’s educational level, number of live children, number of dead children, type of pregnancy and type of delivery. There was an important decrease in neonatal death records over time, approximately 19%. Except for the variable mother’s educational level (20.0%) and gender (0,8%), all variables presented percentages of incompleteness ranging from 6.7% to 15.3%. The percentage of matched records ranged from 50.0% to 58.8% in the period. After five multiple imputations, the missing data were recovered. The Relative Efficiency of the variables with missing observations recovered was verified, whose efficiency for all variables ranged from 96.7% to 99.9%. The conclusion was an excellent and reliable imputation of missing data. The tools used here proved to be very efficient and useful for use in regions with deficient data, such as those deaths registered for Paraíba in Brazil.
Keywords: Vital Statistics; Neonatal; Mortality; Brazil (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:ssdmcp:978-3-030-93005-9_13
Ordering information: This item can be ordered from
http://www.springer.com/9783030930059
DOI: 10.1007/978-3-030-93005-9_13
Access Statistics for this chapter
More chapters in The Springer Series on Demographic Methods and Population Analysis from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().