Population-level estimates of child restraint practices among children aged 0-12 years in NSW, Australia
- Brown, Julie, Hatfield, Julie, Du, Wei, Finch, Caroline, Bilston, Lynne
- Authors: Brown, Julie , Hatfield, Julie , Du, Wei , Finch, Caroline , Bilston, Lynne
- Date: 2010
- Type: Text , Journal article
- Relation: Accident Analysis and Prevention Vol. 42, no. 6 (2010), p. 2144-2148
- Relation: http://purl.org/au-research/grants/nhmrc/565900
- Full Text:
- Reviewed:
- Description: This cross-sectional study provides population-referenced data on the restraints used and the extent of incorrect restraint use, among child vehicle passengers aged 0-12 years in NSW, Australia. A multistage stratified cluster sampling plan was used to randomly select vehicles from baby/child health clinics, pre-schools/day care centres, and primary schools across NSW to undergo detailed inspection of restraints used by child occupants within those vehicles. Overall, there were very high restraint usage rates (>99% of sampled children) but fewer than one quarter of children were using the correct size-appropriate restraints. Incorrect use (51.4%) was as common as inappropriate use (51.2%). Incorrect use was highest among users of dedicated child restraint systems (OR 16.0, 95% CI 6.9-36.0), and was more likely among those using size-appropriate restraints than those using inappropriate restraints (OR 1.8 95% CI 1.1-3.2); and among convertible restraints than those designed for a single mode of use (OR 1.5 95% CI 1.2-1.7). As incorrect use substantially reduces the protection from injury that is offered by child restraints, it is important that future strategies to reduce casualties among child occupants target both inappropriate and incorrect use. © 2010 Elsevier Ltd. All rights reserved.
- Authors: Brown, Julie , Hatfield, Julie , Du, Wei , Finch, Caroline , Bilston, Lynne
- Date: 2010
- Type: Text , Journal article
- Relation: Accident Analysis and Prevention Vol. 42, no. 6 (2010), p. 2144-2148
- Relation: http://purl.org/au-research/grants/nhmrc/565900
- Full Text:
- Reviewed:
- Description: This cross-sectional study provides population-referenced data on the restraints used and the extent of incorrect restraint use, among child vehicle passengers aged 0-12 years in NSW, Australia. A multistage stratified cluster sampling plan was used to randomly select vehicles from baby/child health clinics, pre-schools/day care centres, and primary schools across NSW to undergo detailed inspection of restraints used by child occupants within those vehicles. Overall, there were very high restraint usage rates (>99% of sampled children) but fewer than one quarter of children were using the correct size-appropriate restraints. Incorrect use (51.4%) was as common as inappropriate use (51.2%). Incorrect use was highest among users of dedicated child restraint systems (OR 16.0, 95% CI 6.9-36.0), and was more likely among those using size-appropriate restraints than those using inappropriate restraints (OR 1.8 95% CI 1.1-3.2); and among convertible restraints than those designed for a single mode of use (OR 1.5 95% CI 1.2-1.7). As incorrect use substantially reduces the protection from injury that is offered by child restraints, it is important that future strategies to reduce casualties among child occupants target both inappropriate and incorrect use. © 2010 Elsevier Ltd. All rights reserved.
Child restraint fitting stations reduce incorrect restraint use among child occupants
- Brown, Julie, Finch, Caroline, Hatfield, Julie, Bilston, Lynne
- Authors: Brown, Julie , Finch, Caroline , Hatfield, Julie , Bilston, Lynne
- Date: 2011
- Type: Text , Journal article
- Relation: Accident Analysis and Prevention Vol. 43, no. 3 (May, 2011), p. 1128-1133
- Relation: http://purl.org/au-research/grants/nhmrc/565900
- Full Text: false
- Reviewed:
- Description: This study evaluated the effectiveness of the NSW Restraint Fitting Station Network in preventing incorrect use of rearward facing and forward facing child restraints. The way children used restraints was observed randomly as they arrived at observation sites during a cross-sectional ecological study across New South Wales, Australia. Trained researchers examined restraint system installation once the child left the vehicle. A structured interview was also conducted with the driver. Logistic regression was used to examine the association between parental report of ever having the restraint checked at a Restraint Fitting Station and whether or not the restraint was used correctly, while controlling for potential confounders and accounting for the complex sample design. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. The results demonstrated that children of respondents who did not use Restraint Fitting Stations were 1.8 times more likely to be incorrectly using their restraints (95% CI 1.1–2.8) than children of Restraint Fitting Station users. Regardless of whether or not a Restraint Fitting Station had been used, there was a trend towards a greater likelihood of incorrect restraint use as the length of restraint ownership increased (OR 1.3 95% CI 1.0–1.7). These results are important for developing strategies aimed at reducing child occupant casualties by reducing the rate of incorrect restraint use, and support programs encouraging the use of Restraint Fitting Stations and similar services as a countermeasure to incorrect use.
Statistical modelling for falls count data
- Ullah, Shahid, Finch, Caroline, Day, Lesley
- Authors: Ullah, Shahid , Finch, Caroline , Day, Lesley
- Date: 2010
- Type: Text , Journal article
- Relation: Accident Analysis and Prevention Vol. 42, no. 2 (2010), p. 384-392
- Relation: http://purl.org/au-research/grants/nhmrc/565900
- Full Text:
- Reviewed:
- Description: Falls and their injury outcomes have count distributions that are highly skewed toward the right with clumping at zero, posing analytical challenges. Different modelling approaches have been used in the published literature to describe falls count distributions, often without consideration of the underlying statistical and modelling assumptions. This paper compares the use of modified Poisson and negative binomial (NB) models as alternatives to Poisson (P) regression, for the analysis of fall outcome counts. Four different count-based regression models (P, NB, zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB)) were each individually fitted to four separate fall count datasets from Australia, New Zealand and United States. The finite mixtures of P and NB regression models were also compared to the standard NB model. Both analytical (F, Vuong and bootstrap tests) and graphical approaches were used to select and compare models. Simulation studies assessed the size and power of each model fit. This study confirms that falls count distributions are over-dispersed, but not dispersed due to excess zero counts or heterogeneous population. Accordingly, the P model generally provided the poorest fit to all datasets. The fit improved significantly with NB and both zero-inflated models. The fit was also improved with the NB model, compared to finite mixtures of both P and NB regression models. Although there was little difference in fit between NB and ZINB models, in the interests of parsimony it is recommended that future studies involving modelling of falls count data routinely use the NB models in preference to the P or ZINB or finite mixture distribution. The fact that these conclusions apply across four separate datasets from four different samples of older people participating in studies of different methodology, adds strength to this general guiding principle. © 2009 Elsevier Ltd. All rights reserved.
- Authors: Ullah, Shahid , Finch, Caroline , Day, Lesley
- Date: 2010
- Type: Text , Journal article
- Relation: Accident Analysis and Prevention Vol. 42, no. 2 (2010), p. 384-392
- Relation: http://purl.org/au-research/grants/nhmrc/565900
- Full Text:
- Reviewed:
- Description: Falls and their injury outcomes have count distributions that are highly skewed toward the right with clumping at zero, posing analytical challenges. Different modelling approaches have been used in the published literature to describe falls count distributions, often without consideration of the underlying statistical and modelling assumptions. This paper compares the use of modified Poisson and negative binomial (NB) models as alternatives to Poisson (P) regression, for the analysis of fall outcome counts. Four different count-based regression models (P, NB, zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB)) were each individually fitted to four separate fall count datasets from Australia, New Zealand and United States. The finite mixtures of P and NB regression models were also compared to the standard NB model. Both analytical (F, Vuong and bootstrap tests) and graphical approaches were used to select and compare models. Simulation studies assessed the size and power of each model fit. This study confirms that falls count distributions are over-dispersed, but not dispersed due to excess zero counts or heterogeneous population. Accordingly, the P model generally provided the poorest fit to all datasets. The fit improved significantly with NB and both zero-inflated models. The fit was also improved with the NB model, compared to finite mixtures of both P and NB regression models. Although there was little difference in fit between NB and ZINB models, in the interests of parsimony it is recommended that future studies involving modelling of falls count data routinely use the NB models in preference to the P or ZINB or finite mixture distribution. The fact that these conclusions apply across four separate datasets from four different samples of older people participating in studies of different methodology, adds strength to this general guiding principle. © 2009 Elsevier Ltd. All rights reserved.
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