Neighborhood effects on child injuries

1. Neighborhood effects on child injuries Jim McDonell Tracy Waters Institute on Family and Neighborhood Life Clemson University Clemson, SC USA 3rd Conference of the International Society for Child Indicators July 29, 2011 University of York This research was sponsored in part by a grant from The Duke Endowment

2. Introduction Child 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

3. Introduction 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

4. Introduction Falls 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)

5. Introduction Transportation 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)

6. Introduction Childhood 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

7. Introduction As 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)

8. Introduction During 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?

9. Introduction Neighborhood 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)

10. Introduction Traffic 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

11. Introduction This 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.

12. Methods The 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

13. Methods Illustration of sampled neighborhood

14. Methods Three 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

15. Methods Neighborhood Observation Scale Initial results indicate acceptable reliability and validity (McDonell & Waters, 2010)

16. Methods Items measured on 10 point Likert-type scale Example: 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.

17. Methods Child 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.

18. Methods 21 categories of injuries were collapsed into 9 categories: • Road vehicle injuries • Other vehicle injuries • Poisonings • Falls • Other accidents • Medical intervention • Suicide • Homicide • Other injuries

19. Methods Child injury codes were calculated at rates per 1,000 children Rates were also calculated for children by gender and by age group

20. Analytic Approach Path 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.

21. Analytic Approach Goodness 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.

22. Neighborhood characteristics Neighborhood type69.3% residential only 16.8% predominately residential 6.1% commercial only 5.7% predominately commercial 2.0% mixed Housing type 53.3% single family detached 16.4% duplex or row house 3.6% apartment/multiple occupancy 14.3% mobile homes 12.3% other

23. Neighborhood characteristics People in 11.9% none neighborhood 56.6% fewer than 5 25.0% 5 to 12 6.6% more than 12 Age distribution 11.3% under 12 8.2% 13 to 17 12.0% 18 to 24 37.5% 25 to 44 20.7% 45 to 64 8.7% 65 and older Gender 37.7% female 61.8% male

24. Model variables

25. Path model for road vehicle injuries χ2(13) = 20.48, p = .08 CFI = .99 RMSEA = .049 .56 The model explains 26% of the variance in child injuries from road vehicle accidents Neighborhood social appearance .00 e2 .75 Neighborhood watchfulness .15 .39 Observed resident engagement -.24 e3 e1 .02 .00 .16 Condition of sidewalks .26 -.17 e4 .48 .32 Road vehicle injuries e8 .19 -.22 Indicated resident engagement e5 -.12 .48 -.29 .00 .43 .18 -.10 Neighborhood safety .25 e6 .00 Park/public space social engagement e7

26. Path model for road vehicle injuries χ2(13) = 20.48, p = .08 CFI = .99 RMSEA = .049 .56 Neighborhood social characteristics accounted for most of the explained variance Neighborhood social appearance .00 e2 .75 Neighborhood watchfulness .15 .39 Observed resident engagement -.24 e3 e1 .02 .00 .16 Condition of sidewalks .26 -.17 e4 .48 .32 Road vehicle injuries e8 .19 -.22 Indicated resident engagement e5 Road vehicle injuries are lower in neighborhoods having a better social appearance and more resident social engagement. -.12 .48 -.29 .00 .43 .18 -.10 Neighborhood safety .25 e6 .00 Park/public space social engagement e7

27. Path model for road vehicle injuries χ2(13) = 20.48, p = .08 CFI = .99 RMSEA = .049 .56 However, observed resident engagement had a marginal direct effect in the opposite direction Neighborhood social appearance .00 e2 .75 Neighborhood watchfulness .15 .39 Observed resident engagement -.24 e3 e1 .02 .00 .16 Condition of sidewalks .26 -.17 e4 .48 .32 Road vehicle injuries e8 .19 -.22 Indicated resident engagement e5 -.12 .48 -.29 .00 .43 .18 -.10 Neighborhood safety .25 e6 .00 Park/public space social engagement e7

28. Path model for road vehicle injuries χ2(13) = 20.48, p = .08 CFI = .99 RMSEA = .049 .56 Neighborhood social appearance The condition of sidewalks, a single item measure, was the only physical appearance factor having a significant effect .00 e2 .75 Neighborhood watchfulness .15 .39 Observed resident engagement -.24 e3 e1 .02 .00 .16 Condition of sidewalks .26 -.17 e4 .48 .32 Road vehicle injuries e8 .19 -.22 Indicated resident engagement e5 -.12 .48 -.29 Road vehicle injuries were lower when sidewalks were in better condition .00 .43 .18 -.10 Neighborhood safety .25 e6 .00 Park/public space social engagement e7

29. Path model for road vehicle injuries χ2(13) = 20.48, p = .08 CFI = .99 RMSEA = .049 .56 Of the two safety measures, neighborhood watchfulness had an indirect effect while neighborhood safety risk had both a direct and an indirect effect Neighborhood social appearance .00 e2 .75 Neighborhood watchfulness .15 .39 Observed resident engagement -.24 e3 e1 .02 .00 .16 Condition of sidewalks .26 -.17 e4 .48 .32 Road vehicle injuries e8 .19 -.22 Indicated resident engagement e5 -.12 .48 -.29 .00 .43 .18 -.10 Neighborhood safety .25 e6 .00 Park/public space social engagement e7

30. Path model for road vehicle injuries χ2(13) = 20.48, p = .08 CFI = .99 RMSEA = .049 .56 The total effect of watchfulness was-.17 while the total effect of safety was -.21 Neighborhood social appearance .00 e2 .75 Neighborhood watchfulness .15 .39 -.17 Observed resident engagement -.24 e3 e1 .02 .00 .16 Condition of sidewalks .26 -.17 e4 .48 .32 Road vehicle injuries e8 .19 -.22 Indicated resident engagement -.21 e5 Road vehicle injuries are lower in neighborhoods with greater watchfulness and safety -.12 .48 -.29 .00 .43 .18 -.10 Neighborhood safety .25 e6 .00 Park/public space social engagement e7

31. .34 .73 .00 .14 .00 .00 .53 Neighborhood watchfulness Park/public space physical appearance Park/public space social engagement Neighborhood social appearance Observed resident engagement .37 Path model for falls Unintentional falls -.20 e5 e4 e2 e3 e6 χ2(5) = 4.66, p = .46 CFI = 1.00 RMSEA = .000 .01 e1 -.36 .43 .33 .30 The model explains 34% of the variance in child injuries from unintentional falls .13 -.28 -.38

32. .34 .73 .00 .14 .00 .00 .53 -.20 Neighborhood watchfulness Park/public space physical appearance Park/public space social engagement Neighborhood social appearance Observed resident engagement .37 Path model for falls Unintentional falls e5 e4 e2 e3 e6 χ2(5) = 4.66, p = .46 CFI = 1.00 RMSEA = .000 .01 e1 -.36 .43 .33 .30 Interestingly, injuries due to unintentional falls increased when parks and public spaces had a more pleasing physical appearance .13 -.28 -.38 This likely indicates higher use of parks and public spaces creating more opportunities for injuries from falls

33. .34 .73 .00 .14 .00 .00 .53 Neighborhood watchfulness Park/public space physical appearance Park/public space social engagement Neighborhood social appearance Observed resident engagement .37 Path model for falls Unintentional falls e4 e5 e2 e3 e6 χ2(5) = 4.66, p = .46 CFI = 1.00 RMSEA = .000 e1 -.36 .43 .33 Again, factors related to neighborhoodsocial appearance account for most of the variance .13 -.38 -.20 .01 .30 -.28 Observed resident engagement has a small direct effect on injuries due to falls.

34. .34 .00 .00 Park/public space physical appearance Park/public space social engagement Path model for falls Unintentional falls e5 e4 e6 χ2(5) = 4.66, p = .46 CFI = 1.00 RMSEA = .000 -.36 .43 .33 Again, neighborhood watchfulness had an indirect effect on unintentional falls. The total effect of watchfulness was -.14 .13 .53 Neighborhood social appearance -.38 e2 .00 Neighborhood watchfulness .73 -.20 .37 .14 -.14 Observed resident engagement .01 e3 e1 .30 -.28 Injuries due to unintentional falls are lower in neighborhoods with higher levels of resident watchfulness

35. Conclusions 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

36. 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.

37. 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.