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Observed Neighborhood Characteristics as an Indicator of Child Safety and Well-Being Jim McDonell, D.S.W. Institute on Family and Neighborhood Life, Clemson University International Society for Child Indicators Inaugural Conference June 26, 2007 Chicago, Illinois

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Observed Neighborhood Characteristics as an Indicator of Child Safety and Well-Being

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Observed Neighborhood Characteristics as an Indicator of Child Safety and Well-Being

Jim McDonell, D.S.W.

Institute on Family and Neighborhood Life, Clemson University

International Society for Child Indicators

Inaugural Conference

June 26, 2007

Chicago, Illinois

This research was supported by a grant from the Duke Endowment


Introduction

Neighborhood context important for child and family well-being. Studies have linked physical and social setting to:

  • Health status and mortality risk (Cohen, et. al., 2003);

  • Crime (Sampson, 2003);

  • Child maltreatment (Coulton, et. al., 1995);

  • Adolescent risk taking (Kling & Liebman, 2004);

  • Educational attainment (South, et. al., 2003);

  • Resident safety (Community & Env. Defense Services, 1999); and

  • Adolescent physical activity (Overton & Asherwood, 2003).


Introduction

Gaps in knowledge:

  • The research on neighborhood effects has focused primarily on the impact of poverty in people’s lives and the macro-level factors that lead to concentrated poverty.

  • While there is growing attention to specific neighborhood (e.g., dilapidation; litter; social cohesion) and family (e.g., parenting style; parent mental health) factors that influence child safety, these are not well understood.

  • Most research is on adolescents and adults and the evidence for neighborhood effects for children generally, especially very young children, is sparse.


Neighborhood effects on children

The available evidence is promising. Studies have found that:

  • Neighborhood cohesion moderates the risk of children’s injuries, even when a higher injury risk seems likely (Soubhi, Raina, & Kohen, 2004).

  • Rates of owner occupied housing and the age of housing stock were significant predictors of pediatric injuries, independent of other community and family characteristics (Shenassa, Stubbendick, & Brown, 2004; Reading, Haynes, & Shenassa, 2005).

  • Children have a strong place-based sensitivity to a range of neighborhood safety issues, including the role of police, gang activity, drug use, and vehicle traffic (Nayak, 2003).


Neighborhood effects on children

  • Homogeneity in residential patterns influences the normative structure of neighborhoods, making it easier for children to adhere to prevailing norms, including those for safety, and for adults to enforce the norms uniformly (Pebly & Sastry, 2003).

  • Children who live within a block of a speed bump have a significantly lower risk of being injured by an automobile (Tester, Rutherford, Wald, & Rutherford, 2004).

  • Community infrastructure design innovations may contribute to child pedestrian injuries. For example, wider roadways for large trucks make street crossing too wide for children to cross during a light change. Such roads also eliminate sidewalks, wide shoulders, and refuge islands removing “safe havens” for children (Schieber & Vegaga, 2002).


Challenges of neighborhood research

Conceptual and methodological challenges to research on neighborhood effects:

  • Lack of consensus definition for neighborhood;

  • Establishing adequate comparisons;

  • Accounting for contextual complexity; and

  • Selecting robust indicators.

    Measurement is one of the more vexing challenges. Typically handled in one or both of two ways.

  • Aggregating individual level data, typically survey findings, or

  • Macro-level or community-structural measures (e.g., census data)


Challenges to neighborhood research

Both have limitations

Macro-level indicators are at too general a level of abstraction to really say much about neighborhood residents, and there is often a lag between when the data were collected and used.

Individual level measures may capture community context but have to cover a lot of ground to do so. As a result, data collection is often overly intrusive and taxing to community residents.

Direct observation of neighborhood features is a more straight forward approach.


Purpose of this study

Study builds on earlier work by applying an observational measure of neighborhood characteristics to studies of:

  • Caregiver perceptions of neighborhood children’s safety at home, and

  • Discharge diagnosis (ICD-9 CM) suggestive of maltreatment for children seen in hospital emergency rooms or for an inpatient stay.


Methods

The research draws on three studies as part of the evaluation of Strong Communities for Children in the Golden Strip.

Begun in 2002 and supported by the Duke Endowment, Strong Communities is a ten-year effort to demonstrate and evaluate a neighborhood-based strategy to reduce child maltreatment proposed by the U.S. Advisory Board on Child Abuse and Neglect

Designed to engage the entire community in preventing child maltreatment by making child protection part of everyday life

For more information, visit the initiative’s website at: http://www.clemson.edu/strongcommunities/


Study 1: Development and validation of the Neighborhood Rating Scale

Item pool generated from literature and previous work.

Photographs of endpoints of neighborhood features were taken or located to:

  • Confirm that the feature was readily identifiable;

  • Serve as a visual reference;

  • Train raters.

    Item pool was reviewed based on these observations with 36 items retained.

    Rating scale was pilot tested by students in a graduate Sociology course.

    Debriefing relative to content, ease of administration, and administration protocol led to further modifications.

    Final version created and raters trained.


Example of endpoints

Physical appearance: Streets

Poor repair

Good repair


Sampling

Three independent ratings on each of 104 neighborhoods in 60 census block groups in southern Greenville County, SC.

Neighborhoods were selected by convenience.

A census block level road network map was created.

Neighborhoods were determined by aggregations of roads having an apparent geographic relationship. This could include road aggregations:

  • with limited through road or arterial intersection;

  • that were bounded by natural or constructed features; or

  • that were separated from other road aggregations by distance.

    Independent selections were made by the researchers and were compared to make final selections.


Illustration of specific neighborhoods


Scale analysis

Intra-class correlation was used to gauge inter-rater reliability. Results showed that 69% of observations were reliable for three raters and 81% were reliable for two raters.

Analysis of the underlying structure produced factors for:

Physical appearance (37.1% of variance) – alpha for items = .91

Social organization (21.9% of variance) – alpha for items = .73

Social engagement (15.0% of variance) – alpha for items = .69

Preliminary evidence for construct validity, with scales and items correlating in the expected direction with measures of neighborhood distress, and self-report and demographic data from a survey of residents in the same neighborhoods.


Neighborhood Rating Scale

The current version of the Neighborhood Rating Scale, then, consists of:

  • A nine item measure of neighborhood physical appearance;

  • A three item measure of social organization;

  • A five item measure for social engagement;

  • 24 individual items measuring safety, public amenities; and various dimensions of neighborhood quality.


Study 2: Parent/caregiver survey

Survey of random sample of 229 parents/caregivers of young children age 10 and under in the same neighborhoods in which observational data were collected. 138-item parent survey measured:

Know neighborhood childrenNeighboring activities

Collective efficacyNeighborhood satisfaction

Social support/mutual assistanceParenting stress/parenting efficacy

Child neglect observation/actionChild household safety

Observed/self-report parentingChild medical care


Study 3: ICD-9 coded child injuries

Data on injuries were extracted from routine hospital incident reports for inpatient admissions and emergency room visits from July 2002 through June 2004 for children age 18 and younger.

Individual ICD-9 codes were aggregated at the census block group level using the same block groups as in the neighborhood observations and parent/caregiver survey.

The initial pool of ICD-9 codes were generated from a list of codes used in a Centers for Disease Control study to improve child maltreatment surveillance.


ICD-9 codes

The codes were submitted to a panel of Pediatricians who used a five-point scale to rate each code on the extent to which it was suggestive of child maltreatment.

An a priori criterion level of an average rating of 3.6 was set for inclusion of a code in the final pool.

Age and gender criteria were also considered.

Injuries that had causes clearly identifiable as unintentional (e.g., legal intervention) or that occurred in certain locations (e.g., sports injuries) were excluded.


ICD-9 codes

The final pool of codes were classified as

  • a) those suggestive of child physical abuse;

  • b) those suggestive of child sexual abuse; and

  • c) those suggestive of child maltreatment not otherwise classified.

    Cases from both years were averaged to form a baseline and prevalence rates were calculated for each census block group.


Current study

Data from all three studies were combined and analyzed through hierarchical regression to test the extent to which neighborhood characteristics predicted resident perceptions of children’s safety at home and ICD-9 coded child injuries.

Education, income, neighborhood stability and level of neighborhood distress were held constant.


Results: Characteristics of neighborhoods (n = 104)

  • 84.5% residential only; 11.7% predominately residential; 1.3% predominately commercial; .7% commercial only; 2.3% mixed residential/commercial.

  • 82.6% detached, single family dwellings; .6% row houses; .3% duplexes; 7.8% mobile homes; 9.1% too mixed to tell

  • No people observed in 28.3% of neighborhoods; fewer than 5 people in 40.8%; 5 to 12 people in 22.4%; 13 to 20 people in 5.8%; more than 20 people in 2.7%.

  • Of residents seen, it was estimated that 5.1% were under age 6; 9.2% between 6 and 12 years old; 9.9% between 13 and 17 years old; 10.9% between 18 and 24 years old; 33.2% between 25 and 44 years old; 23.1% between 45 and 64 years old; 8.6% age 65 or older.

  • 63.5% of observed residents were male; 36.5% female.


Results: Characteristics of survey respondents (n = 229)

  • 72.5% female.

  • 35.9 years old on average (SD = 8.7).

  • 73.8% married; 11.4% sep./div./, wid; 14.8% never married.

  • 71.5% White; 23.2% Black or African-American; 3.5% Hispanic or Latino; 1.8% other race or ethnicity.

  • 10% less than HS; 24.6% HS diploma; 29.3% some college/2 year degree; 25% bachelor’s degree; 11.4% graduate/professional degree.

  • 52.4% employed full-time; 14.4% part-time; 31.9% unemployed and looking or in training; 1.3% full-time homemakers.

  • 13.8% had family income under $20,000 per year; 24% from $20,001 to $40,000; 28.6% from $40,001 to $70,000; 33.6% more than $70,000.


Results: Characteristics of child injuries (n = 557)

35% of injuries were classified as suggestive of physical abuse; 56.5% as suggestive of sexual abuse; and 8.4% were suggestive of child maltreatment not otherwise classified;

70.5% of cases were females, 29.5% males;

By age,

  • 19.4% were 0-2

  • 3.6% were 3-4

  • 5.7% were 5-9

  • 9.2% were 10-14; and

  • 62.1% were 15-19.


Results: Means, and standard deviations for outcome variables.


Results: Means, and standard deviations for predictor variables.


Results: Means and standard deviations for control variables


Results: Child Household Safety

Significant predictors:

  • Education (β = .4, SE = .2, p < .05)

  • Income (β = .4, SE = .2, p < .05)

  • Neighborhood appearance (β = .8, SE = .3, p < .01)

  • Condition of park/public space (β = -1.1, SE = .5, p < .05)

  • Symbolic barrier density (β = -.3, SE = .2, p < .05)

  • Adequacy of trash receptacles (β = -.3, SE = .1, p < .05)

Model accounts for 27% of the variance in child household safety (unadjusted R2), or 23% (adjusted R2)


Results: ICD-9 codes suggestive of child physical abuse

Significant predictors:

  • Impoverishment distress (β = .2, SE = .02, p < .001)

  • Social organizations (β = .1, SE = .04, p < .05)

  • School condition (β = -.2, SE = .09, p < .001)

  • Park condition (β = -.2, SE = .07, p < .01)

  • Communication networks (β = -.2, SE = .03, p < .05)

  • Vigilance (β = .2, SE = .02, p < .05)

  • Safety norms (β = -.2, SE = .02, p < .05)

  • Building security (β = .3, SE = .03, p < .001)

  • Vehicles speeding (β = -.2, SE = .02, p < .01)

  • Adequacy of bus stops (β = .4, SE = .05, p < .001)

  • Adequacy of public phones (β = .2, SE = .07, p < .01)

  • Adequacy of trash receptacles (β = .2, SE = .02, p < .01)


Results: ICD-9 codes suggestive of child physical abuse

Model accounts for 33% of the variance in ICD-9 codes suggestive of child physical abuse (unadjusted R2), or 29% (adjusted R2)


Conclusions

Physical and social characteristics of neighborhoods are potent predictors of children’s household safety, accounting for 27% of the variance, and injuries suggestive of child physical abuse.

Several conclusions may be drawn from these findings:


Conclusions

The factors comprising neighborhood appearance are generally amenable to change.

  • Condition of dwellings, streets, sidewalks;

  • Trash in neighborhood;

  • Abandoned dwellings;

  • Residential decorations;

  • Indications of neighborhood name;

  • For sale/for rent signs.

    Concerted action by residents through neighborhood associations and linking such organizations across neighborhoods for policy advocacy and direct action.


Conclusions

High symbolic barrier density may indicate social fragmentation in the neighborhood.

Increasing opportunities for social interaction, through neighborhood events may help reduce such fragmentation.

Research findings show that neighborhood cohesion is a protective factor for child safety and well-being

Enlist civic groups/faith community in this effort.


Conclusions

Children are sensitive to the normative environment of the neighborhood, and neighborhood norms directly impact children’s safety and well-being.

Neighborhood norms reflect the collective beliefs and actions of residents.

Efforts to foster a normative environment that sees to children’s safety will help protect children in the neighborhood and in the home.

This is supported by the finding that resident and public safety efforts to enforce safety norms is predictive of children’s safety.


Conclusion

Finally, the Neighborhood Rating Scale is a useful tool for:

  • Research on neighborhood effects on a range of social issues;

  • As a means of assessing the general health of a neighborhood; and

  • A way to understand the neighborhood context for working with families.


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