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Neighborhood effects on child injuries. Jim McDonell Tracy Waters Institute on Family and Neighborhood Life Clemson University Clemson, SC USA. 3 rd Conference of the International Society for Child Indicators July 29, 2011 University of York . This research was sponsored in part - PowerPoint PPT Presentation
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Neighborhood effects on child injuries
3rd Conference of theInternational Society for Child Indicators
July 29, 2011University of York
Jim McDonellTracy Waters
Institute on Family and Neighborhood LifeClemson UniversityClemson, SC USA
This research was sponsored in part by a grant from The Duke Endowment
IntroductionChild injuries emerged as a relevant issue in the
field of prevention and public policy in 1980s
Advances in medicine led to fewer child deaths from disease (polio, measles, etc)
Shift in thinking and terminology◦ Accidents = random, caused by chance or fate,
unpreventable ◦ Unintentional injuries = explicable and
preventable
In the United States, unintentional injuries are the leading cause of child mortality and morbidity [Centers for Disease Control and Prevention (CDC), 2008]◦ 12,000 child fatalities annually◦ 9 million initial visits to the emergency
department◦ Fatal child injury rate: 15 per 100,000◦ Nonfatal child injury rate: 11,272 per 100,000
Introduction
IntroductionFalls are the leading cause of nonfatal childhood
injury in the United States (CDC, 2008) 2.8 million children injured Injury rate: 3,420 per 100,000 children
Falls account for a large proportion of child injuries throughout the world: United Kingdom, 40% (Haynes et al, 2003) New Zealand, 40% (Kypri et al, 2001) USA, 38% (CDC, 2007)
IntroductionTransportation related injuries are the leading
cause of unintentional child fatalities in the United States (CDC, 2008)◦ Transportation-related death rate = 9.8 per
100,000 Motor vehicle crash (occupant) = 4.6 per 100,000 Pedestrian death rate = 1.2 per 100,000
Recent decline in child pedestrian injuries (Doukas et al., 2010)
IntroductionChildhood injuries are related to a number of
population and environmental factors (Freisthler et al., 2008)◦ Number of female headed households◦ Adult to child ratio◦ Neighborhood disadvantage◦ Residential instability◦ Child care burden◦ Social capital
IntroductionAs many child injuries occur in or near the
home, the context of neighborhood has received increased attention◦ 24% of child injuries occurred on the street◦ 15% of child injuries occurred at a park,
playground, or sports facility (Haynes et al., 2003)◦ Schools and parks are the most common sites of
child injuries leading to litigation (Frost, 1995)
IntroductionDuring middle childhood (5 – 9 years of age),
children are at increased risk of falls, especially falls at the playground (Kypri et al., 2001)
Children have greater independent mobility starting between 7 – 9 years of age (Soori & Bhopal, 2001)
But how do neighborhood physical and social characteristics contribute to these child injuries?
IntroductionNeighborhood characteristics are also important
for understanding motor vehicle and child pedestrian injuries ◦ Number of parked cars on the street◦ Multi-family dwellings◦ Number of pedestrians observed (Agran et al., 1996)
On school days, 71% of child pedestrian injuries occur between 3 – 7 pm (Newbury et al., 2008)
IntroductionTraffic calming techniques, such as speed humps,
are effective in reducing child pedestrian injury (Tester et al., 2004)◦ Children living on a street with a speed hump
were significantly less likely to have a pedestrian injury
◦ Speed humps and other physical structures do not require policing and appear to be more effective than conventional deterrents
Again, more research is needed on the influence of neighborhood characteristics on child injuries
IntroductionThis study attempts to fill a gap in the
literature by exploring the relationship between both physical and social characteristics of neighborhoods and unintentional child injuries.
After an overview of the methodology, this presentation will highlight the resulting path models and conclude with implications for research, policy, and practice.
MethodsThe sample consisted of 244 neighborhoods in 132
census block groups. The neighborhoods were located in the Upstate and Midlands regions of South Carolina.
Convenience sample of neighborhoods
Neighborhoods were defined using GIS software. ◦ Aggregations of roads having an apparent geographic
relationship◦ Limited through road or arterial intersection◦ Bounded by natural or constructed features◦ Isolated from other road aggregations by distance
MethodsIllustration of sampled neighborhood
MethodsThree independent observations per
neighborhood◦ One weekday afternoon/evening observation ◦ One weekend day morning/early afternoon
observation◦ One “anytime” observation
Observations completed during warm weather months by driving and/or walking through neighborhood
MethodsNeighborhood Observation ScaleConstruct Factor # items Alpha
Physical appearance
Neighborhood physical appearance 7 .94School/park/public space physical appearance 5 .89
Social appearance
Neighborhood social appearance
5 .55
Indicated social engagement 4 .63Observed social engagement 3 .56Park/public space social engagement 3 .63
Safety Resident watchfulness 3 .66Neighborhood safety risk 4 .68
Initial results indicate acceptable reliability and validity (McDonell & Waters, 2010)
Items measured on 10 point Likert-type scaleExample:
Methods
Yards are poorly kept
Yards are well kept
1 2 3 4 5 6 7 8 9 10
Poorly kept = Lawn overgrown; property is dirty and unkempt; does not appear that attention is given to upkeep
Well kept = Clean; property apparently maintained; grass is cut; stairs/porch swept and clean.
MethodsChild injury rates were calculated using ICD-9 CM
coded hospital inpatient and emergency room discharge diagnoses.
Injury codes were provided by the South Carolina Office of Research and Statistics (ORS) at the census block group level.
Injury codes corresponded to the same time period in which neighborhood observations occurred.
Methods21 categories of injuries were collapsed into 9
categories:◦ Road vehicle injuries◦ Other vehicle injuries◦ Poisonings◦ Falls◦ Other accidents◦ Medical intervention◦ Suicide◦ Homicide◦ Other injuries
MethodsChild injury codes were calculated at rates
per 1,000 children
Rates were also calculated for children by gender and by age group
Analytic ApproachPath analysis models were created using AMOS
19.0
Measures of neighborhood physical and social characteristics were previously validated using confirmatory factor analysis. These 8 factors were treated as observed endogenous variables.
Child injury rates were also treated as observed endogenous variables.
Analytic ApproachGoodness of fit indices utilized:
◦ Non-significant chi square◦ Comparative Fit Index (CFI) > 0.9◦ Root Mean Square Error of Approximation
(RMSEA) < 0.05
Initial models included all 8 neighborhood constructs. Theory and modification indices guided adjustments to models.
Neighborhood type 69.3% residential only16.8% predominately residential 6.1% commercial only 5.7% predominately commercial 2.0% mixed
Housing type 53.3% single family detached16.4% duplex or row house 3.6% apartment/multiple occupancy 14.3%
mobile homes12.3% other
Neighborhood characteristics
People in 11.9% noneneighborhood 56.6% fewer than 5
25.0% 5 to 12 6.6% more than 12
Age distribution11.3% under 12 8.2% 13 to 1712.0% 18 to 2437.5% 25 to 4420.7% 45 to 64 8.7% 65 and older
Gender 37.7% female61.8% male
Neighborhood characteristics
Variable Mean SDRate of road vehicle injuries 7.49 3.50Rate of injuries due to falls 11.01 5.04Resident watchfulness .46 .20Neighborhood social appearance 1.04 .12Observed resident engagement 1.35 .15Condition of sidewalks 6.90 1.04Indicated resident engagement 4.22 1.18Neighborhood safety risk 1.00 .09Park/Public space social appearance 1.76 .22
Model variables
Path model for road vehicle injuries
χ2(13) = 20.48, p = .08CFI = .99RMSEA = .049
The model explains26% of the variancein child injuries fromroad vehicle accidents
.48
.16
-.29
.48
.18
.32
.25
.00Neighborhoodwatchfulness
e1
.39.75
e4Condition of sidewalks
.00
.56Neighborhood
social appearance e2
.26Road vehicle
injuriese8
.15Observed resident
engagement e3
.19Indicated resident
engagement e5
Park/public space social engagement e7
.00
.43
e6
.00
-.24
-.17
.02
-.22
-.12
-.10 Neighborhoodsafety
Path model for road vehicle injuries
χ2(13) = 20.48, p = .08CFI = .99RMSEA = .049
.48
.16
-.29
.48
.18
.32
.25
.00Neighborhoodwatchfulness
e1
.39.75
e4Condition of sidewalks
.00
.56Neighborhood
social appearance e2
.26Road vehicle
injuriese8
.15Observed resident
engagement e3
.19Indicated resident
engagement e5
Park/public space social engagement e7
.00
.43Neighborhood
safety e6
.00
-.24
-.17
.02
-.22
-.12
-.10
Neighborhood social characteristics accounted for most of the explained variance
Road vehicle injuries arelower in neighborhoodshaving a better socialappearance and moreresident social engagement.
Path model for road vehicle injuries
χ2(13) = 20.48, p = .08CFI = .99RMSEA = .049
.48
.16
-.29
.48
.18
.32
.25
.00Neighborhoodwatchfulness
e1
.39.75
e4Condition of sidewalks
.00
.56Neighborhood
social appearance e2
.26Road vehicle
injuriese8
.15Observed resident
engagement e3
.19Indicated resident
engagement e5
Park/public space social engagement e7
.00
.43Neighborhood
safety e6
.00
-.24
-.17
.02
-.22
-.12
-.10
However, observed resident engagement had a marginal direct effect in the opposite direction
Path model for road vehicle injuries
χ2(13) = 20.48, p = .08CFI = .99RMSEA = .049
.48
.16
-.29
.48
.18
.32
.25
.00Neighborhoodwatchfulness
e1
.39.75
e4Condition of sidewalks
.00
.56Neighborhood
social appearance e2
.26Road vehicle
injuriese8
.15Observed resident
engagement e3
.19Indicated resident
engagement e5
Park/public space social engagement e7
.00
.43
e6
.00
-.24
-.17
.02
-.22
-.12
-.10 Neighborhoodsafety
The condition of sidewalks, a single item measure, was the only physical appearance factor having a significant effect
Road vehicle injuries were lower when sidewalks were in better condition
Path model for road vehicle injuries
χ2(13) = 20.48, p = .08CFI = .99RMSEA = .049
.48
.16
-.29
.48
.18
.32
.25
.00Neighborhoodwatchfulness
e1
.39.75
e4Condition of sidewalks
.00
.56Neighborhood
social appearance e2
.26Road vehicle
injuriese8
.15Observed resident
engagement e3
.19Indicated resident
engagement e5
Park/public space social engagement e7
.00
.43Neighborhood
safety e6
.00
-.24
-.17
.02
-.22
-.12
-.10
Of the two safety measures, neighborhood watchfulness had an indirect effect while neighborhood safety risk had both a direct and an indirect effect
Neighborhoodsafety
Path model for road vehicle injuries
χ2(13) = 20.48, p = .08CFI = .99RMSEA = .049
.48
.16
-.29
.48
.18
.32
.25
.00Neighborhoodwatchfulness
e1
.39.75
e4Condition of sidewalks
.00
.56Neighborhood
social appearance e2
.26Road vehicle
injuriese8
.15Observed resident
engagement e3
.19Indicated resident
engagement e5
Park/public space social engagement e7
.00
.43
e6
.00
-.24
-.17
.02
-.22
-.12
-.10
Road vehicle injuries are lower in neighborhoods with greater watchfulness and safety
The total effect ofwatchfulness was -.17 while the total effect of safety was -.21
-.17
-.21
Path model for falls χ2(5) = 4.66, p = .46CFI = 1.00RMSEA = .000
.37.73
Neighborhood social appearance e2
.53
Observed residentengagement e3
.14
Unintentionalfallse6
.34
Park/public space social engagement e5
.00
Park/public space physical appearance e4
.00
.00Neighborhoodwatchfulness
e1
-.28
.30
.01
-.20
.13
-.36 .33.43
-.38
The model explains34% of the variancein child injuries fromunintentional falls
Path model for falls χ2(5) = 4.66, p = .46CFI = 1.00RMSEA = .000
.37.73
Neighborhood social appearance e2
.53
Observed residentengagement e3
.14
Unintentionalfallse6
.34
Park/public space social engagement e5
.00
Park/public space physical appearance e4
.00
.00Neighborhoodwatchfulness
e1
-.28
.30
.01
-.20
.13
-.36 .33.43
-.38
Interestingly, injuries due to unintentional falls increased when parks and public spaces had a more pleasing physical appearance
This likely indicates higheruse of parks and public spaces creating moreopportunities for injuries from falls
Path model for falls χ2(5) = 4.66, p = .46CFI = 1.00RMSEA = .000
.37.73
Neighborhood social appearance e2
.53
Observed residentengagement e3
.14
Unintentionalfallse6
.34
Park/public space social engagement e5
.00
Park/public space physical appearance e4
.00
.00Neighborhoodwatchfulness
e1
-.28
.30
.01
-.20
.13
-.36 .33.43
-.38
Again, factors related to neighborhood social appearance account for most of the variance
Observed resident engagement has a small direct effect on injuries due to falls.
Path model for falls χ2(5) = 4.66, p = .46CFI = 1.00RMSEA = .000
.37.73
Neighborhood social appearance e2
.53
Observed residentengagement e3
.14
Unintentionalfallse6
.34
Park/public space social engagement e5
.00
Park/public space physical appearance e4
.00
.00Neighborhoodwatchfulness
e1
-.28
.30
.01
-.20
.13
-.36 .33.43
-.38
Again, neighborhood watchfulness had an indirect effect on unintentional falls. The total effect of watchfulness was -.14
Injuries due to unintentionalfalls are lower in neighborhoods with higher levels of resident watchfulness
-.14
This research further demonstrates the importance of neighborhood context to children’s safety
This suggests that environmental modification is key to improving child safety
However, the typical approach to improving children’s safety is by modifying the physical neighborhood
This study shows that attending to neighborhood physical features alone is not sufficient to improve children’s safety
Conclusions
Neighborhood characteristics, social characteristics in particular, are significant indicators of the risk of injuries to children
In socially cohesive settings, caregivers are more likely to watch over neighbor children, perhaps taking action to protect children from harm
In addition, social activity increases surveillance opportunities; residents are more likely to notice dangers
Too, when residents know and spend time with each other, they are more likely to talk about potential threats to children’s safety.
Conclusions
Strategies to increase social exchange among neighbors are likely to go a long way to improving children’s safety.
Such strategies as family activity groups, resident buying clubs, communal meals, and the like are low cost and easy to implement
A neighborhood watch group is a good way to foster resident engagement while simultaneously increasing watchfulness.
Finally, more research is needed to better understand the effect of neighborhood social and physical characteristics across a broader range of child injuries.
Conclusions