Literature DB >> 25575965

Spatial analysis of paediatric swimming pool submersions by housing type.

Rohit P Shenoi1, Ned Levine2, Jennifer L Jones1, Mary H Frost3, Christine E Koerner4, John J Fraser5.   

Abstract

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. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

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Year:  2015        PMID: 25575965     DOI: 10.1136/injuryprev-2014-041397

Source DB:  PubMed          Journal:  Inj Prev        ISSN: 1353-8047            Impact factor:   2.399


  3 in total

Review 1.  An overview of geospatial methods used in unintentional injury epidemiology.

Authors:  Himalaya Singh; Lauren V Fortington; Helen Thompson; Caroline F Finch
Journal:  Inj Epidemiol       Date:  2016-12-26

2.  A randomized controlled trial to evaluate the impact of a geo-specific poster compared to a general poster for effecting change in perceived threat and intention to avoid drowning 'hotspots' among children of migrant workers: evidence from Ningbo, China.

Authors:  Yinchao Zhu; Xiaoqi Feng; Hui Li; Yaqin Huang; Jieping Chen; Guozhang Xu
Journal:  BMC Public Health       Date:  2017-05-30       Impact factor: 3.295

3.  Where children and adolescents drown in Queensland: a population-based study.

Authors:  Belinda A Wallis; Kerrianne Watt; Richard C Franklin; James W Nixon; Roy M Kimble
Journal:  BMJ Open       Date:  2015-11-26       Impact factor: 2.692

  3 in total

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