Spatial analysis of paediatric swimming pool submersions by housing type

Inj Prev. 2015 Aug;21(4):245-53. doi: 10.1136/injuryprev-2014-041397. Epub 2015 Jan 9.


Objective: Drowning is a major cause of unintentional childhood death. The relationship between childhood swimming pool submersions, neighbourhood sociodemographics, housing type and swimming pool location was examined in Harris County, Texas.

Study design and setting: Childhood pool submersion incidents were examined for spatial clustering using the Nearest Neighbor Hierarchical Cluster (Nnh) algorithm. To relate submersions to predictive factors, an Markov Chain Monte Carlo (MCMC) Poisson-Lognormal-Conditional Autoregressive (CAR) spatial regression model was tested at the census tract level.

Results: There were 260 submersions; 49 were fatal. Forty-two per cent occurred at single-family residences and 36% at multifamily residential buildings. The risk of a submersion was 2.7 times higher for a child at a multifamily than a single-family residence and 28 times more likely in a multifamily swimming pool than a single family pool. However, multifamily submersions were clustered because of the concentration of such buildings with pools. Spatial clustering did not occur in single-family residences. At the tract level, submersions in single-family and multifamily residences were best predicted by the number of pools by housing type and the number of children aged 0-17 by housing type.

Conclusions: Paediatric swimming pool submersions in multifamily buildings are spatially clustered. The likelihood of submersions is higher for children who live in multifamily buildings with pools than those who live in single-family homes with pools.

MeSH terms

  • Adolescent
  • Child
  • Child, Preschool
  • Drowning / epidemiology*
  • Drowning / prevention & control
  • Female
  • Housing / statistics & numerical data*
  • Humans
  • Male
  • Markov Chains
  • Monte Carlo Method
  • Near Drowning / epidemiology
  • Poisson Distribution
  • Regression Analysis
  • Residence Characteristics
  • Retrospective Studies
  • Spatial Analysis*
  • Swimming Pools / statistics & numerical data*
  • Texas / epidemiology