Time trends, geographical, socio-economic, and gender disparities in neonatal mortality in Burundi: evidence from the demographic and health surveys, 2010-2016.
Burundi
DHS
Global health
Inequality
Magnitude
Neonatal mortality
Time trends
Journal
Archives of public health = Archives belges de sante publique
ISSN: 0778-7367
Titre abrégé: Arch Public Health
Pays: England
ID NLM: 9208826
Informations de publication
Date de publication:
12 Nov 2020
12 Nov 2020
Historique:
received:
24
04
2020
accepted:
05
11
2020
entrez:
9
12
2020
pubmed:
10
12
2020
medline:
10
12
2020
Statut:
epublish
Résumé
Programmatic and research agendas surrounding neonatal mortality are important to help countries attain the child health related 2030 Sustainable Development Goal (SDG). In Burundi, the Neonatal Mortality Rate (NMR) is 25 per 1000 live births. However, high quality evidence on the over time evolution of inequality in NMR is lacking. This study aims to address the knowledge gap by systematically and comprehensively investigating inequalities in NMR in Burundi with the intent to help the country attain SDG 3.2 which aims to reduce neonatal mortality to at least as low as 12 per 1000 live births by 2030. The Burundi Demographic and Health Survey (BDHS) data for the periods of 2010 and 2016 were used for the analyses. The analyses were carried out using the WHO's HEAT version 3.1 software. Five equity stratifiers: economic status, education, residence, sex and subnational region were used as benchmark for measuring NMR inequality with time over 6 years. To understand inequalities from a broader perspective, absolute and relative inequality measures, namely Difference, Population Attributable Risk (PAR), Ratio, and Population Attributable Fraction (PAF) were calculated. Statistical significance was measured by computing corresponding 95% Confidence Intervals (CIs). NMR in Burundi in 2010 and 2016 were 36.7 and 25.0 deaths per 1000 live births, respectively. We recorded large wealth-driven (PAR = -3.99, 95% CI; - 5.11, - 2.87, PAF = -15.95, 95% CI; - 20.42, - 11.48), education related (PAF = -6.64, 95% CI; - 13.27, - 0.02), sex based (PAR = -1.74, 95% CI; - 2.27, - 1.21, PAF = -6.97, 95% CI; - 9.09, - 4.86), urban-rural (D = 15.44, 95% CI; 7.59, 23.29, PAF = -38.78, 95% CI; - 45.24, - 32.32) and regional (PAR = -12.60, 95% CI; - 14.30, - 10.90, R = 3.05, 95% CI; 1.30, 4.80) disparity in NMR in both survey years, except that urban-rural disparity was not detected in 2016. We found both absolute and relative inequalities and significant reduction in these inequalities over time - except at the regional level, where the disparity remained constant during the study period. Large survival advantage remains to neonates of women who are rich, educated, residents of urban areas and some regions. Females had higher chance of surviving their 28th birthday than male neonates. More extensive work is required to battle the NMR gap between different subgroups in the country.
Sections du résumé
BACKGROUND
BACKGROUND
Programmatic and research agendas surrounding neonatal mortality are important to help countries attain the child health related 2030 Sustainable Development Goal (SDG). In Burundi, the Neonatal Mortality Rate (NMR) is 25 per 1000 live births. However, high quality evidence on the over time evolution of inequality in NMR is lacking. This study aims to address the knowledge gap by systematically and comprehensively investigating inequalities in NMR in Burundi with the intent to help the country attain SDG 3.2 which aims to reduce neonatal mortality to at least as low as 12 per 1000 live births by 2030.
METHODS
METHODS
The Burundi Demographic and Health Survey (BDHS) data for the periods of 2010 and 2016 were used for the analyses. The analyses were carried out using the WHO's HEAT version 3.1 software. Five equity stratifiers: economic status, education, residence, sex and subnational region were used as benchmark for measuring NMR inequality with time over 6 years. To understand inequalities from a broader perspective, absolute and relative inequality measures, namely Difference, Population Attributable Risk (PAR), Ratio, and Population Attributable Fraction (PAF) were calculated. Statistical significance was measured by computing corresponding 95% Confidence Intervals (CIs).
RESULTS
RESULTS
NMR in Burundi in 2010 and 2016 were 36.7 and 25.0 deaths per 1000 live births, respectively. We recorded large wealth-driven (PAR = -3.99, 95% CI; - 5.11, - 2.87, PAF = -15.95, 95% CI; - 20.42, - 11.48), education related (PAF = -6.64, 95% CI; - 13.27, - 0.02), sex based (PAR = -1.74, 95% CI; - 2.27, - 1.21, PAF = -6.97, 95% CI; - 9.09, - 4.86), urban-rural (D = 15.44, 95% CI; 7.59, 23.29, PAF = -38.78, 95% CI; - 45.24, - 32.32) and regional (PAR = -12.60, 95% CI; - 14.30, - 10.90, R = 3.05, 95% CI; 1.30, 4.80) disparity in NMR in both survey years, except that urban-rural disparity was not detected in 2016. We found both absolute and relative inequalities and significant reduction in these inequalities over time - except at the regional level, where the disparity remained constant during the study period.
CONCLUSION
CONCLUSIONS
Large survival advantage remains to neonates of women who are rich, educated, residents of urban areas and some regions. Females had higher chance of surviving their 28th birthday than male neonates. More extensive work is required to battle the NMR gap between different subgroups in the country.
Identifiants
pubmed: 33292519
doi: 10.1186/s13690-020-00501-3
pii: 10.1186/s13690-020-00501-3
pmc: PMC7663869
doi:
Types de publication
Journal Article
Langues
eng
Pagination
115Références
Birth Defects Res A Clin Mol Teratol. 2009 Sep;85(9):764-72
pubmed: 19358286
BMJ. 2015 Sep 14;351:h4119
pubmed: 26371214
Lancet. 2014 Oct 25;384(9953):1491-2
pubmed: 25390565
J Public Health (Oxf). 2012 Mar;34 Suppl 1:i1-2
pubmed: 22363025
Psychol Bull. 2002 Mar;128(2):295-329
pubmed: 11931521
Lancet. 2008 Nov 8;372(9650):1661-9
pubmed: 18994664
Lancet Glob Health. 2014 Mar;2(3):e165-73
pubmed: 25102849
Lancet Glob Health. 2014 Mar;2(3):e122-3
pubmed: 25102835
PLoS Med. 2014 Sep 22;11(9):e1001727
pubmed: 25243463
BMJ. 2011 Jul 19;343:d4306
pubmed: 21771825
Int J Equity Health. 2010 Sep 03;9:21
pubmed: 20815875
Children (Basel). 2018 Sep 08;5(9):
pubmed: 30205549
J Child Adolesc Subst Abuse. 2017;26(5):353-366
pubmed: 29204066
Child Youth Serv Rev. 2015 May;52:74-88
pubmed: 25825550
BMC Health Serv Res. 2012 Nov 13;12:389
pubmed: 23145945
PLoS One. 2013;8(1):e53696
pubmed: 23308278
Am J Epidemiol. 2008 Jan 15;167(2):145-54
pubmed: 17947220
Sci Rep. 2019 Jul 5;9(1):9786
pubmed: 31278283
PLoS One. 2017 Mar 21;12(3):e0173763
pubmed: 28323854
Glob Health Action. 2015 Sep 18;8:29034
pubmed: 26387506
Soc Sci Med. 1993 May;36(9):1207-27
pubmed: 8511650