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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

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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

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  • Poisoning is a leading cause of

childhood injury 1

  • Preschool children (0-4 years)

are developmentally at risk 2,3

Background

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Risk factors include

  • Child factors (age, male, previous

poisoning) 1-4

  • Parent factors (younger, perinatal

depression, alcohol use, supervision) 5,6

  • Environmental factors (storage) 1
  • Geographic remoteness 7, low

socioeconomic status 5,6

Background

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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.

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Rationale

Research gap

  • 0-4 year old group
  • Risk factors
  • Mechanism: Individual poisoning agents
  • Clinical outcomes

No studies characterising poisoning amongst Aboriginal children

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Research Questions

1.

Are the demographic risk factors of sex, socioeconomic status and remoteness similar for Aboriginal and non- Aboriginal children?

2.

Which agents cause poisoning for Aboriginal and non- Aboriginal children?

3.

Do Aboriginal children have more severe clinical

  • utcomes?
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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
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Methods

Define birth cohort Identify poisoning cases Poisoning No poisoning Principle diagnosis of injury ICD-10-AM (T36-65) Excluded: heavy metals, carbon monoxide, snake/insects, plant/animal toxins Included: pharmaceuticals & non-pharmaceuticals Clearzone14

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Methods

Define birth cohort Logistic regression Odds of poisoning by demographic factors Aboriginal children Non-Aboriginal children Poisoning Identify poisoning cases No poisoning

Binary outcome

  • Poisoning (1)
  • No poisoning (0)
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Methods

Define birth cohort Logistic regression Odds of poisoning by demographic factors Aboriginal children Non-Aboriginal children Poisoning Identify poisoning cases No poisoning

Predictor variables

  • Sex
  • Socioeconomic

disadvantage (IRSAD)

  • Remoteness

(ARIA)

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Methods

Define birth cohort Age of admission Poisoning agents Clinical outcomes Characteristics Identify poisoning cases Poisoning

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Results: Study population

3,436 poisoning admissions 382 Aboriginal (11%) 3,003 Non-Aboriginal (89%) 3,385 individual children

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Results - Demographics

Adjusted for sex, area-level disadvantage and remoteness

Variables Sex Area-level disadvantage Remoteness

Female Male 1 (Least disadvantaged) 2 3 (Most disadvantaged) Major Cities Inner Regional Outer Regional Remote/Very Remote

Aboriginal (n=28,528)

OR (95% CI)

1 1.26 (1.03-1.54) 1 1.88 (1.11-3.19) 1.83 (1.10-3.03) 1 1.13 (0.88-1.47) 1.39 (1.06-1.82) 1.18 (0.80-1.74)

aOR (95% CI)

1 1.27 (1.03-1.56) 1 1.84 (1.07-3.15) 1.57 (0.92-2.69) 1 1.06 (0.82-1.39) 1.39 (1.02-1.88) 1.18 (0.78-1.79)

Non Aboriginal (n=738,591)

OR (95% CI)

1 1.17 (1.09-1.26) 1 1.44 (1.31-1.59) 1.96 (1.79-2.15) 1 1.43 (1.32-1.56) 2.13 (1.91-2.37) 2.54 (1.89-3.42)

aOR (95% CI)

1 1.17 (1.09-1.26) 1 1.34 (1.21-1.48) 1.64 (1.48-1.81) 1 1.33 (1.22-1.44) 1.66 (1.47-1.87) 1.97 (1.46-2.66)

Adjusted Odds Ratio

0.5 1 2

Aboriginal non-Aboriginal

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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%)

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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 –Agents

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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)
  • Few children had procedures (10% all poisoning admissions)
  • Social worker only recorded for 8% of poisoning admissions

Aboriginal & non-Aboriginal

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Limitations

  • Administrative data – limited data items for risk factors/clinical
  • utcomes
  • Only hospitalised poisonings
  • Rural hospitals have a higher propensity to admit patients
  • Small numbers of Aboriginal children
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Implications

Child resistant is NOT child proof! 15

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Implications

Prevention

  • Safe storage (locked away, out of reach)
  • Education to parents about medication toxicity
  • Hospital as a “teachable moment” for secondary

prevention

  • Social determinants – poor housing
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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
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Thank you!

Centre for Big Data Research in Health

  • Prof Louisa Jorm
  • Dr Mark Hanly
  • Dr Holger Moller
  • Mr Sanjay Farshid (UNSW Medicine)

Sydney Children’s Hospital Network

  • A/Prof Sue Woolfenden
  • A/Prof Karen Zwi
  • Ms Natasha Larter
  • Prof Nick Buckley
  • Prof Sallie Pearson
  • Prof Rebecca Ivers
  • Prof Kathleen Clapham
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References

1.

World Health Organization (WHO). (2008). World report on child injury prevention: World Health Organization.

2.

Schmertmann, M., Williamson, A., & Black, D. (2008). Stable age pattern supports role of development in unintentional childhood poisoning. Inj Prev, 14(1), 30-33. doi:10.1136/ip.2007.016253

3.

Schmertmann, M., Williamson, A., & Black, D. (2014). Unintentional poisoning in young children: does developmental stage predict the type of substance accessed and ingested? Child Care Health Dev, 40(1), 50-59. doi:10.1111/j.1365-2214.2012.01424.x

4.

Petridou, E., Kouri, N., Polychronopoulou, A., Siafas, K., Stoikidou, M., & Trichopoulos, D. (1996). Risk factors for childhood poisoning: a case-control study in Greece. Inj Prev, 2(3), 208-211.

5.

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 study in general practice. Br J Gen Pract, 62(605), e827-833. doi:10.3399/bjgp12X659303

6.

Orton, E., Kendrick, D., West, J., & Tata, L. J. (2012). Independent risk factors for injury in pre-school children: three population-based nested case- control studies using routine primary care data. PLoS One, 7(4), e35193. doi:10.1371/journal.pone.0035193

7.

Lam, L. T. (2003). Childhood and adolescence poisoning in NSW, Australia: an analysis of age, sex, geographic, and poison types. Injury Prevention, 9(4), 338-342.

8.

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.

9.

Moller, H., Falster, K., Ivers, R., Falster, M., Randall, D., Clapham, K., & Jorm, L. (2016). Inequalities in Hospitalized Unintentional Injury Between Aboriginal and Non-Aboriginal Children in New South Wales, Australia. American journal of public health, 106(5), 899-905.

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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