Characteristics of hospitalised unintentional poisoning in preschool aged Aboriginal and non-Aboriginal children in New South Wales: a population data linkage study Caroline Lee Supervisors Prof. Louisa Jorm, Assoc. Prof. Sue Woolfenden, Dr Mark Hanly Investigators Assoc. Prof Karen Zwi, Ms Natasha Larter
• Poisoning is a leading cause of childhood injury 1 Background • Preschool children (0-4 years) are developmentally at risk 2,3
Risk factors include • Child factors (age, male, previous poisoning) 1-4 Background • Parent factors (younger, perinatal depression, alcohol use, supervision) 5,6 • Environmental factors (storage) 1 • Geographic remoteness 7 , low socioeconomic status 5,6
AIHW: Pointer S 2016. Hospitalised injury in Aboriginal and Torres Strait Islander children and young people 2011 – 13. Injury research and statistics series no. 96. Cat. no. INJCAT 172. Canberra: AIHW.
Rationale Research gap • 0-4 year old group • Risk factors • Mechanism: Individual poisoning agents • Clinical outcomes No studies characterising poisoning amongst Aboriginal children
Research Questions Are the demographic risk factors of sex, socioeconomic 1. status and remoteness similar for Aboriginal and non- Aboriginal children? Which agents cause poisoning for Aboriginal and non- 2. Aboriginal children? Do Aboriginal children have more severe clinical 3. outcomes ?
Methods • Study design: retrospective whole of population cohort using linked hospital and mortality data • Data sources: Admitted Patient Data Collection (APDC) & NSW Register of Births Deaths and Marriages • Participants : all children born in NSW hospitals between 2000- 2009. Preschool age (0-4 yrs) • Aboriginality: from hospital record, “ever - identified” algorithm 12,13
Methods Define birth cohort Identify poisoning cases Poisoning No poisoning Principle diagnosis of injury Clearzone 14 ICD-10-AM (T36-65) Included : pharmaceuticals & non-pharmaceuticals Excluded : heavy metals, carbon monoxide, snake/insects, plant/animal toxins
Methods Define birth cohort Identify poisoning cases Poisoning No poisoning Logistic regression Binary outcome Odds of poisoning by demographic factors • Poisoning (1) • No poisoning (0) Non-Aboriginal Aboriginal children children
Methods Define birth cohort Identify poisoning cases Poisoning No poisoning Predictor variables Logistic regression • Sex • Socioeconomic Odds of poisoning by demographic factors disadvantage (IRSAD) Non-Aboriginal • Remoteness Aboriginal children children (ARIA)
Methods Define birth cohort Identify poisoning cases Poisoning Characteristics Age of admission Poisoning agents Clinical outcomes
Results: Study population 3,436 poisoning admissions 3,385 individual children 3,003 Non-Aboriginal 382 Aboriginal (11%) (89%)
Results - Demographics Aboriginal Variables Aboriginal (n=28,528) Non Aboriginal (n=738,591) non-Aboriginal OR (95% CI) aOR (95% CI) OR (95% CI) aOR (95% CI) Sex Female 1 1 1 1 Male 1.26 (1.03-1.54) 1.27 (1.03-1.56) 1.17 (1.09-1.26) 1.17 (1.09-1.26) Area-level disadvantage 1 (Least disadvantaged) 1 1 1 1 2 1.88 (1.11-3.19) 1.84 (1.07-3.15) 1.44 (1.31-1.59) 1.34 (1.21-1.48) 3 (Most disadvantaged) 1.83 (1.10-3.03) 1.57 (0.92-2.69) 1.96 (1.79-2.15) 1.64 (1.48-1.81) Remoteness Major Cities 1 1 1 1 Inner Regional 1.13 (0.88-1.47) 1.06 (0.82-1.39) 1.43 (1.32-1.56) 1.33 (1.22-1.44) Outer Regional 1.39 (1.06-1.82) 1.39 (1.02-1.88) 2.13 (1.91-2.37) 1.66 (1.47-1.87) Remote/Very Remote 1.18 (0.80-1.74) 1.18 (0.78-1.79) 2.54 (1.89-3.42) 1.97 (1.46-2.66) 0.5 1 2 Adjusted Odds Ratio Adjusted for sex, area-level disadvantage and remoteness
Results - Agents • Mostly pharmaceutical agents (2859/3436, 83%) Most common classes Nonopioid analgesics (n=493, 14%) Antiepileptics/sedative-hypnotics (n=492, 14%) Psychotropic drugs (n=394, 11%) Cardiovascular drugs (n=382, 11%) Systemic and haematological agents (n=286, 8%)
Results – Agents Most common classes Most common individual agents Nonopioid analgesics (n=493, 14%) Paracetamol (n=374, 11%) Antiepileptics/sedative-hypnotics (n=492, 14%) Benzodiazepines (n=370, 11%) Psychotropic drugs (n=394, 11%) Other and unspecified antidepressants (n=149, 4%) Cardiovascular drugs (n=382, 11%) Other antihypertensives (n=211, 6%) Systemic and haematological agents (n=286, 8%) Antiallergic and anti-emetic drugs (n=150, 4%(
Results – Clinical Outcomes • One death from poisoning during study period • Few repeat admissions (n=51, 1% all poisoning admissions) • Most ( 90% ) children had short length of stay (<1 or 1 day) Aboriginal & non-Aboriginal • Few children had procedures (10% all poisoning admissions) • Social worker only recorded for 8% of poisoning admissions
Limitations • Administrative data – limited data items for risk factors/clinical outcomes • Only hospitalised poisonings • Rural hospitals have a higher propensity to admit patients • Small numbers of Aboriginal children
Implications Child resistant is NOT child proof! 15
Implications Prevention • S afe storage (locked away, out of reach) • Education to parents about medication toxicity • Hospital as a “teachable moment” for secondary prevention • Social determinants – poor housing
Conclusion • Aboriginal children had around 3x higher rates of hospitalised poisoning than non-Aboriginal children • Similar agents and clinical outcomes for Aboriginal and non- Aboriginal children • Commonly used prescription & over-the-counter medications • Nothing is 100% childproof and safe storage is important
Thank you! Centre for Big Data Research in Health • Prof Nick Buckley • Prof Louisa Jorm • Prof Sallie Pearson • Dr Mark Hanly • Prof Rebecca Ivers • Dr Holger Moller • Prof Kathleen Clapham • Mr Sanjay Farshid (UNSW Medicine) Sydney Children’s Hospital Network • A/Prof Sue Woolfenden • A/Prof Karen Zwi • Ms Natasha Larter
References World Health Organization (WHO). (2008). World report on child injury prevention : World Health Organization. 1. Schmertmann, M., Williamson, A., & Black, D. (2008). Stable age pattern supports role of development in unintentional childhood poisoning. Inj Prev, 2. 14 (1), 30-33. doi:10.1136/ip.2007.016253 Schmertmann, M., Williamson, A., & Black, D. (2014). Unintentional poisoning in young children: does developmental stage predict the type of 3. substance accessed and ingested? Child Care Health Dev, 40 (1), 50-59. doi:10.1111/j.1365-2214.2012.01424.x Petridou, E., Kouri, N., Polychronopoulou, A., Siafas, K., Stoikidou, M., & Trichopoulos, D. (1996). Risk factors for childhood poisoning: a case-control 4. study in Greece. Inj Prev, 2 (3), 208-211. Tyrrell, E. G., Orton, E., Tata, L. J., & Kendrick, D. (2012). Children at risk of medicinal and non-medicinal poisoning: a population-based case-control 5. study in general practice. Br J Gen Pract, 62 (605), e827-833. doi:10.3399/bjgp12X659303 Orton, E., Kendrick, D., West, J., & Tata, L. J. (2012). Independent risk factors for injury in pre-school children: three population-based nested case- 6. control studies using routine primary care data. PLoS One, 7 (4), e35193. doi:10.1371/journal.pone.0035193 Lam, L. T. (2003). Childhood and adolescence poisoning in NSW, Australia: an analysis of age, sex, geographic, and poison types. Injury Prevention, 7. 9 (4), 338-342. AIHW: Pointer S 2016. Hospitalised injury in Aboriginal and Torres Strait Islander children and young people 2011 – 13. Injury research and statistics 8. series no. 96. Cat. no. INJCAT 172. Canberra: AIHW. Moller, H., Falster, K., Ivers, R., Falster, M., Randall, D., Clapham, K., & Jorm, L. (2016). Inequalities in Hospitalized Unintentional Injury Between 9. Aboriginal and Non-Aboriginal Children in New South Wales, Australia. American journal of public health, 106 (5), 899-905.
References 10. Moller, H., Falster, K., Ivers, R., Falster, M. O., Clapham, K., & Jorm, L. (2017). Closing the Aboriginal child injury gap: targets for injury prevention. Australian and New Zealand Journal of Public Health, 41 (1), 8-14. doi:http://dx.doi.org/10.1111/1753-6405.12591 11. Walter, S. (2010). Mortality and hospitalisation due to injury in the Aboriginal population of New South Wales. North Sydney, Australia: New South Wales Department of Health . 12. Australian Institute of Health and Welfare (AIHW). (2013). Indigenous identification in hospital separations data: quality report (AIHW) (978-1-74249- 420-3; Cat. no. IHW 90; 32pp.; $10). Retrieved from Canberra: http://www.aihw.gov.au/publication-detail/?id=60129543215 13. Gialamas, A., Pilkington, R., Berry, J., Scalzi, D., Gibson, O., Brown, A., & Lynch, J. (2016). Identification of Aboriginal children using linked administrative data: Consequences for measuring inequalities. J Paediatr Child Health, 52 (5), 534-540. doi:10.1111/jpc.13132 14. Lestina, D. C., Miller, T. R., & Smith, G. S. (1998). Creating injury episodes using medical claims data. Journal of Trauma and Acute Care Surgery, 45 (3), 565-569. 15. Department of Health Therapeutic Goods Administration. (2008). Guidance on Therapeutic Goods Order No. 80 Child-resistant packaging requirements for medicines. https://www.tga.gov.au/guidance-therapeutic-goods-order-no-80-child-resistant-packaging-requirements- medicines#sch1
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