| Literature DB >> 30675338 |
Davies Adeloye1, Kirsty Bowman1, Kit Yee Chan1, Smruti Patel1, Harry Campbell1, Igor Rudan1.
Abstract
BACKGROUND: Injuries result in substantial number of deaths among children globally. The burden across many settings is largely unknown. We estimated global and regional child deaths due to injuries from publicly available evidence.Entities:
Mesh:
Year: 2018 PMID: 30675338 PMCID: PMC6317703 DOI: 10.7189/jogh.08.021104
Source DB: PubMed Journal: J Glob Health ISSN: 2047-2978 Impact factor: 4.413
Quality assessment criteria
| Criteria | Assessment | Score |
|---|---|---|
| Study design
(At least 10 injury types reported and based on standard
definitions or ICD coding?) | Yes | 1 |
| No | 0 | |
| Sampling (was
it representative of target sub-national population or national
population?) | Nationally representative | 2 |
| Sub-nationally representative | 1 | |
| No | 0 | |
| Statistical
analysis (was it clear and appropriate for outcome
measure?) | Yes | 1 |
| Ambiguous | 0 | |
| Study
limitations (were potential sources of bias described) | Yes | 1 |
| No | 0 | |
| Final
assessment: High (4-5), Moderate (2-3), and low (0-1) | ||
Figure 1Flowchart of search strategy and study selection.
Figure 2Sources of data on child injury deaths by country.
Data distribution by injury type and WHO region
| Injury type | AFRO | EMRO | EURO | PAHO | SEARO | WPRO | Total |
|---|---|---|---|---|---|---|---|
| 4 | 1 | 2 | 5 | 1 | 14 | 27 | |
| 3 | 1 | 2 | 7 | 3 | 15 | 31 | |
| 2 | 1 | 2 | 6 | 3 | 17 | 31 | |
| 3 | 1 | 1 | 6 | 2 | 2 | 15 | |
| 1 | 0 | 1 | 4 | 2 | 13 | 21 | |
| 3 | 1 | 2 | 4 | 3 | 14 | 27 | |
| 1 | 1 | 2 | 2 | 1 | 15 | 22 | |
| 0 | 0 | 1 | 2 | 0 | 2 | 5 | |
| 0 | 0 | 1 | 2 | 1 | 2 | 6 | |
| 0 | 1 | 0 | 0 | 3 | 0 | 4 | |
| 1 | 0 | 0 | 1 | 1 | 0 | 3 | |
| 0 | 0 | 0 | 1 | 1 | 1 | 3 | |
| 1 | 1 | 1 | 0 | 0 | 1 | 4 | |
| 0 | 0 | 2 | 3 | 2 | 2 | 9 | |
| 1 | 0 | 1 | 7 | 1 | 5 | 15 | |
| 0 | 0 | 1 | 4 | 0 | 2 | 7 | |
AFRO – African region, EMRO – Eastern Mediterranean region, EURO – European region, PAHO – Pan-American Health Organization or American region, SEARO – South East Asia region, WPRO – Western Pacific region
Characteristics of selected studies
| First author | Study period | Country | Income category | Study design | Quality grading |
|---|---|---|---|---|---|
| 2000 | Mozambique | Low | Population based. Registered
deaths | Moderate | |
| 2015 | Nigeria | Lower middle | Cross-sectional
Verbal
autopsy results | Moderate | |
| 2000 | South Africa | Upper middle | Population based. Death
certificates | Moderate | |
| 2006 | Mozambique | Low | Cross-sectional survey. Verbal
autopsy results | Moderate | |
| 2005 | Iran | Upper middle | Population based. Death registration
data | Moderate | |
| 1992 | England & Wales | High | Population based. WHO European
detailed mortality database | High | |
| 1999-2012 | Poland | High | Population based. WHO European
detailed mortality database | High | |
| 1997 | Mexico | Upper middle | Population based. Death
certificates | High | |
| 1996-2002 | Brazil | Upper middle | Ecological model. Mortality data
from mortality information system | High | |
| 2007 | Colombia | Upper middle | Population based. Injury
surveillance system | High | |
| 1993 | USA | High | Population based. Injury
surveillance system | High | |
| 2003 | Brazil | Upper middle | Population based. Mortality data
from mortality information system | High | |
| 2009 | Colombia | Upper middle | Population based. Death
certificates | High | |
| 2009 | Canada | High | Population based. Injury
surveillance system | High | |
| 2012 | Canada | High | Population based. Injury
surveillance system | High | |
| 2005 | Bangladesh | Lower middle | Population based. Verbal autopsy
results | High | |
| 2003 | India | Lower middle | Cross-sectional. Verbal autopsy
results | High | |
| 2017 | Bangladesh | Lower middle | Population based. Injury
surveillance system | High | |
| 2004-2008 | China | Upper middle | Population based. Annual reports of
mortality data for maternal and child health | High | |
| 1993 | New Zealand | High | Population based. Injury
surveillance system | High | |
| 2009-2014 | China | Upper middle | Population based. Disease
surveillance information systems. | High | |
| 1994 | Australia | High | Population based. Child deaths
registry | High | |
| 2008 | Australia | High | Population based. Child deaths
registry | High | |
| 2000-2008 | China | Upper middle | Population based. Child deaths
obtained from Shenzhen Women and Child Health Surveillance
System for 2004-2008 | Moderate | |
| 2001 | China | Upper middle | Population based. Disease
surveillance information systems. | Moderate | |
| 1997-2012 | China | Upper middle | Population based. Child deaths
registry | Moderate | |
| 2004-2010 | China | Upper middle | Population based. Child deaths
registry | Moderate | |
| 2004-2008 | China | Upper middle | Population based. Child deaths
registry | Moderate | |
| 2002-2009 | New Zealand | High | Population based. Disease surveillance information systems. | Moderate | |
AFRO – African region, EMRO – Eastern Mediterranean region, EURO – European region, PAHO – Pan-American Health Organization or American region, SEARO – South East Asia region, WPRO – Western Pacific region
Figure 3A. Pooled crude child injury mortality rate by WHO region, 0-11 months. B. Pooled crude child injury mortality rate by type of injury, 0-11 months.
Figure 4A. Pooled crude child injury mortality rate by WHO region, 1-4 years. B. Pooled crude child injury mortality rate by type of injury, 1-4 years.
Figure 5A. Pooled crude child injury mortality rate by WHO region, 0-4 years. B. Pooled crude child injury mortality rate by type of injury, 0-4 years.
Meta-regression model statistics
| Under 5 injury mortality (per 100 000) | Coefficient | Standard error | t | Lower CI | Upper CI | |
|---|---|---|---|---|---|---|
| -62.72354 | 23.99989 | -2.61 | 0.017 | -112.7864 | -12.66065 | |
| -12.92205 | 41.31005 | -0.31 | 0.758 | -99.09331 | 73.24921 | |
| -90.3925 | 29.76 | -3.04 | 0.007 | -152.4708 | -28.31423 | |
| -65.96893 | 20.79313 | -3.17 | 0.005 | -109.3426 | -22.59521 | |
| -67.67915 | 37.58827 | -1.80 | 0.087 | -146.0869 | 10.72861 | |
| 1.197741 | 1.043791 | 1.15 | 0.265 | -.9795689 | 3.375052 | |
| -2299.962 | 2091.543 | -1.10 | 0.005 | -6662.844 | -2062.92 | |
AFRO – African region, EMRO – Eastern Mediterranean region, EURO – European region, PAHO – Pan-American Health Organization or American region, SEARO – South East Asia region, WPRO – Western Pacific region, Reg – dummy variables representing each WHO region, t – model probability, cons – model constant (equivalent to AFRO region from model), REML – residual maximum likelihood
Global and regional child deaths (0-4 y) by injury type in 2015*
| Injury
type | World | AFRO | EMRO | EURO | PAHO | SEARO | WPRO | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 21.99 | 142661 | 26.14 | 39110 | 20.24 | 13389 | 7.73 | 3689 | 12.44 | 9279 | 17.04 | 31630 | 10.17 | 12715 | |
| 19.00 | 123270 | 6.59 | 9866 | 6.25 | 4135 | 4.42 | 2108 | 7.31 | 5449 | 35.31 | 65533 | 18.09 | 22605 | |
| 10.89 | 70638 | 38.63 | 57784 | 6.85 | 4529 | 5.15 | 2459 | 10.67 | 7953 | 3.47 | 6440 | 1.98 | 2472 | |
| 10.25 | 66483 | 4.48 | 6695 | 5.95 | 3938 | 3.68 | 1756 | 12.44 | 9279 | 2.76 | 5114 | 7.06 | 8830 | |
| 5.34 | 34626 | 4.59 | 6871 | 4.17 | 2757 | 1.84 | 878 | 1.38 | 1031 | 14.69 | 27274 | 5.51 | 6888 | |
| 3.84 | 24931 | 1.18 | 1762 | 3.13 | 2067 | 1.47 | 703 | 1.78 | 1326 | 1.84 | 3409 | 3.81 | 4768 | |
| 6.62 | 42937 | 15.19 | 22726 | 2.23 | 1477 | 2.21 | 1054 | 6.52 | 4860 | 4.49 | 8334 | 2.26 | 2826 | |
| 2.56 | 16621 | 21.20 | 31711 | 1.49 | 985 | 1.10 | 527 | 2.76 | 2062 | 25.51 | 47350 | 1.41 | 1766 | |
AFRO – African region, EMRO – Eastern Mediterranean region, EURO – European region, PAHO - Pan-American Health Organization or American region, SEARO – South East Asia region, WPRO – Western Pacific region
*Estimates based on meta-regression model.
†Includes asphyxiation, firearms, cutting/piercing, venomous animal/plants, electrocution and medical procedures.