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Child injury: using national emergency department monitoring systems to identify temporal and demographic risk factors. / Hughes, Karen; McHale, Philip; Wyke, Sacha et al.
In: Injury Prevention, Vol. 20, No. 2, 04.2014, p. 74-80.

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Hughes K, McHale P, Wyke S, Lowey H, Bellis MA. Child injury: using national emergency department monitoring systems to identify temporal and demographic risk factors. Injury Prevention. 2014 Apr;20(2):74-80. doi: 10.1136/injuryprev-2013-040816, 10.1136/injuryprev-2013-040816

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Hughes, Karen ; McHale, Philip ; Wyke, Sacha et al. / Child injury : using national emergency department monitoring systems to identify temporal and demographic risk factors. In: Injury Prevention. 2014 ; Vol. 20, No. 2. pp. 74-80.

RIS

TY - JOUR

T1 - Child injury

T2 - using national emergency department monitoring systems to identify temporal and demographic risk factors

AU - Hughes, Karen

AU - McHale, Philip

AU - Wyke, Sacha

AU - Lowey, Helen

AU - Bellis, Mark A

PY - 2014/4

Y1 - 2014/4

N2 - Background Injury is a leading cause of death in children. Emergency department (ED) data offer a potentially rich source of data on child injury. This study uses an emerging national ED data collection system to examine sociodemographics and temporal trends in child injury attendances in England. Methods Cross sectional examination of ED attendances for key injury types made by children aged 0–14 years between April 2010 and March 2011 (road traffic injury (RTI) n=21 670; assault n=9529; deliberate self harm (DSH) n=3066; sports injury n=88 250; burns n=22 222; poisoning n=12 446). Multivariate analyses examined the impact of demographics (age, gender, residential deprivation) and temporal events (day, month, school and public holidays) on risk of attendance for different injury types. Results For most injury types, attendance increased with deprivation. The attendance ratio between children from the poorest and richest deprivation quintiles was greatest for assaults (4.21:1). Conversely, sports injury attendance decreased with deprivation. Males made more attendances than females for all but DSH. Age and temporal profiles varied by injury type. Assault attendances reduced at weekends while burns attendances increased. RTI and sports injury attendances were increased during school term times. Conclusions ED data can provide a major epidemiological resource for examining both temporal and demographic risks of child injury. Emerging systems, such as the one analysed here, can already inform the targeting of prevention, and with improved data coding and use, their utility would be greatly strengthened.

AB - Background Injury is a leading cause of death in children. Emergency department (ED) data offer a potentially rich source of data on child injury. This study uses an emerging national ED data collection system to examine sociodemographics and temporal trends in child injury attendances in England. Methods Cross sectional examination of ED attendances for key injury types made by children aged 0–14 years between April 2010 and March 2011 (road traffic injury (RTI) n=21 670; assault n=9529; deliberate self harm (DSH) n=3066; sports injury n=88 250; burns n=22 222; poisoning n=12 446). Multivariate analyses examined the impact of demographics (age, gender, residential deprivation) and temporal events (day, month, school and public holidays) on risk of attendance for different injury types. Results For most injury types, attendance increased with deprivation. The attendance ratio between children from the poorest and richest deprivation quintiles was greatest for assaults (4.21:1). Conversely, sports injury attendance decreased with deprivation. Males made more attendances than females for all but DSH. Age and temporal profiles varied by injury type. Assault attendances reduced at weekends while burns attendances increased. RTI and sports injury attendances were increased during school term times. Conclusions ED data can provide a major epidemiological resource for examining both temporal and demographic risks of child injury. Emerging systems, such as the one analysed here, can already inform the targeting of prevention, and with improved data coding and use, their utility would be greatly strengthened.

KW - Accidents

KW - Adolescent

KW - Age Distribution

KW - Athletic Injuries

KW - Child

KW - Child Abuse

KW - Child Welfare

KW - Child, Preschool

KW - Cross-Sectional Studies

KW - Emergency Service, Hospital

KW - England

KW - Female

KW - Health Services Misuse

KW - Humans

KW - Infant

KW - Infant, Newborn

KW - Male

KW - Population Dynamics

KW - Population Surveillance

KW - Public Health

KW - Risk Factors

KW - Sex Distribution

KW - Socioeconomic Factors

KW - Wounds and Injuries

KW - Journal Article

KW - Research Support, Non-U.S. Gov't

U2 - 10.1136/injuryprev-2013-040816

DO - 10.1136/injuryprev-2013-040816

M3 - Article

C2 - 23842803

VL - 20

SP - 74

EP - 80

JO - Injury Prevention

JF - Injury Prevention

SN - 1475-5785

IS - 2

ER -