DetroitKidsData.org

1. DetroitKidsData.org An Informational Resource of Children, Family and Community Status for Metropolitan Detroit

2. A Children’s Bridge Program Funded by Wayne State University’s 2004 Research Enhancement Program awarded to: • Paul T. Giblin, Department of Pediatrics • Lee Kallenbach, Department of Community Medicine • Kurt Metzger, Center for Urban Studies

3. DetroitKidsData.org • What is DKD? • Why DKD • A “cooks tour” of DKD • DKD measures applied

4. What Is DKD ? • DKD is a web based highly interactive data repository of child and family information for Wayne, Macomb and Oakland Counties and the City of Detroit • DKD’s information is presented in geographic units as small as zip codes and as large as cities and counties and is compared to state and national norms

5. What is DKD? DKD’s data is presented in 4 domains • Predisposing/mediating measures of child health and development • Child developmental status and behavioral measures • Child health status and access to service • Neighborhood demographic characteristics

6. What is DKD? • DKD presents data as tables, as graphs and as maps • DKD presents data organized by specific child or family measures expressed across communities or focuses on a specific community and reports its full spectrum of child and family measures • DKD turns data into information by highlighting disparities between communities and illustrating correspondence between measures

7. Why DKD? • Data is cool • Web sites are cool • Those who do data and web sites are really cool

8. Why DKD?A child development/familysystems perspective • An ecological model of child health and development suggests the relevance of a wide range of familial and community measures • An aggregation of measures by community suggest a unit of interpretation and influence • Presenting data as information supports action

9. Why DKD?:A policy and program perspective • “New Federalism”---the dissemination of responsibility to the lowest unit of action urges the “democratization” of information • Web based technology and merged extant data systems provide data repositories allowing timely programmatic response • Epidemiologic surveillance allows the measurement of community benefit resulting from program action or institutional mission

10. Why DKD?A public health perspective • The IOM’s Community Health Improvement Process (CHIP) begins with problem identification based on ongoing monitoring of community measures • Problem identification also requires an ongoing forum for community participation in which data is presented in a timely manner and transformed into information • Health promotion begins with provision of health information to improve life skills and make healthy choices

11. Why DKD?A university perspective • A shared baseline for problem identification, program justification and evaluation of progress • A single source of measures employed by varied social science, human service and health science disciplines • A common ground to foster university and community collaboration

12. A “Cook’s Tour” of DKD • Home Page • Accessing Data • Measures by DKD district • Measure across regions • Groupings of Measures • Demographic information • Predisposing/mediating measures • Child developmental/behavioral measures • Health status and access to services • Web Page Walk Through

13. DKD Measures Applied • “Neighborhoods (are) a potent source of unequal opportunity” (Brooks-Gunn, et al, 1993 p.385) • “Poverty is social quicksand; it swallows up community” (Garbarino, 1998 p.114) • “I’ve been rich and I’ve been poor and rich is better.” (Sophie Tucker)

14. Neighborhood Neighborhood implies the existence of both a structural boundary and a social context

15. Neighborhood Neighborhood factors which may influence child outcomes include: • Demographic composition (income, ethnicity, positive role models, racial segregation) • Social organization or disorganization and the presence or absence of social controls (economic decline, population turnover, decreased institutional resources)

16. Neighborhood • Stressors in the neighborhood (violence, incarceration, housing density, environmental pollutants) • Parenting practices and social networks (parenting styles, two versus single parent households, divorce, multiple siblings closely spaced) (Ingoldsby& Shaw, 2002)

17. Poverty • Poverty is a measure of subsistence---the “poverty line” for the U.S. is set by the Department of Agriculture’s estimate of food costs for a basic nutritionally adequate diet multiplied by three (assuming that a subsistence level family spends 1/3 of its income on food)

18. Poverty • Poverty is more concentrated in children because of the declining incomes of young families and the increase in female headed single parent families • Poverty expresses itself through maternal stress, and inadequate emotional, informational and social supports

19. Poverty • Outcomes of poverty include disparities in survival (neonatal and infant mortality, mortality from trauma) and morbidity (intellectual performance, social/emotional functioning, chronic medical conditions, nutrition and growth, lead poisoning, asthma) and homelessness

20. DKD Measures Applied How may neighborhood conditions affect child health and development?

21. DKD Measures Applied • Contagion model: The impact of neighborhood peer influences on the prevalence of child behavior problems in socioeconomic and racially homogenous communities • Collective socialization model: Child outcomes as influenced by the prevalence of neighborhood adults who can serve as role models and monitors of the behavior of neighborhood children

22. DKD Measures Applied • Resource model: Child outcomes as influenced by the level of resources (community centers, parks, medical care, daycare) available in a neighborhood • Competition model: Neighborhood effects on child outcomes as a function of community residents competing for scarce resources (Jenks & Meyer, 1990)

23. DetroitKidsData.org Predisposing/Mediating Neighborhood Factors for Child Health and Development Measures:Four Models of Influence(Social Demographic)

24. DetroitKidsData.orgPredisposing/Mediating Neighborhood Factors for Child Health and Development Measures:Four Models of Influence(Child Welfare)

25. DetroitKidsData.orgPredisposing/Mediating Neighborhood Factors for Child Health and Development Measures:Four Models of Influence(Community Health)

26. DetroitKidsData.orgPredisposing/Mediating Neighborhood Factors for Child Health and Development Measures:Four Models of Influence(Educational Resources)

27. Neighborhood and Child Outcomes Four Weddings and a Funeral

28. The Neighborhood Context of Adolescent Mental Health* CAROL S. ANESHENSEL CLEA A. SUCOFF(Journal of Health and Social Behavior. 1996, 37 (December):293-310 ) • Neighborhood Context • Structural • median household incomes • % population below poverty line, • % labor force in professional, executive managerial occupations • Racial Ethnic • % Black % Hispanic • Segregated vs integrated neighborhoods • Experiential • Ambient hazards (11 Y/N potential dangers) • Social cohesion (Likert scale) • Adolescent Mental Health • Depression/Anxiety • Oppositional defiant disorders • Conduct disorders • Family Background • SES & racial ethnicity • Family structure • Parental mental health

29. Do Neighborhoods Influence Child and Adolescent Development?'Jeanne Brooks-Gunn,Greg J. Duncan,Pamela Kato Klebanov, Naomi Sealand(Amer J. Sociology; 1993; 99 (2): 353-95) • Neighborhood Effects • % of families with incomes<$10,000 • % families affluent (>$30,000) • Social Isolation: >40% of neighborhood who were not • elderly were poor & no more than 10% families earned >$30,000 • % males working in professional, managerial occupations • % Black • % families with children headed by women • % families on assistance • % adult males unemployed • Family Effects • Maternal education • Family income • Female headship status • Developmental Outcomes • Cognitive/ School functioning • Stanford-Binet at 36 months • HS dropout rate

30. Some Ways in Which Neighborhoods, Nuclear Families, Friendship Groups, and Schools Jointly Affect Changes in Early Adolescent DevelopmentThomas D. Cook, Melissa R.Hennan, Meredith Phillips, and Richard A. Settersten, Jr.(Child Development. 2002; 73 (4): 1283-1309) • COMMUNITY CONTEXT • Family • ·  Structural features (size, income, parents) • ·  Process (parenting) • Schools • ·   Structure (size, location, class size) • ·   Process (valuing of academics) • Neighborhood • ·   Structure (employment) • ·   Process (social cohesion, social context) • Friendship Groups • Child Characteristics • ·  Gender • ·  Achievement test scores • ·   SES • ·   2-parent family • ·   Race/ ethnicity • BBehavioral Outcomes • ·   GPA • ·   Attendance • ·    Self Esteem • ·    Risk Behaviors

31. Contemporary Developmental Theory and Adolescence: Developmental Systems and Applied Developmental Science Richard M. Lerner, Ph.D. and Domini R. Castellino, Ph.D.(J Adoles Health. 2002; 31: 122-135)

32. Figure 1. A developmental contextual model of adolescent-context relations (Lerner & Castellino, 2002).

34. DKD Measures Applied Caveats • Neighborhood boundaries as experienced by a child may change developmentally • The “social address” of a child may extend beyond the neighborhood of a child • Neighborhoods and children have a transactional effect on each other • Neighborhoods are not static and have temporal rhythms

35. DKD Measures Applied Program Recommendations for Neighborhood Interventions: • Addressing only those families/children with the highest scores on an index of risk is unlikely to affect a community’s base rate of risk factors • Adopt community wide primary prevention programs which assure basic preventive services---health care, education and parent support (Chamberlin, 1996)

36. Future Directions: Data • More Measures (80 and counting) • More Time Points • Baseline (Year 2000) • Current (2002-2003) • More Detail for Existing Measures • Race / ethnicity • Age / gender • Other

37. Future Directions: Geography • More Geographic Specificity • In Detroit • Subcommunities • Expand Coverage to Additional Counties • Statewide • Requires additional resources

38. Future Directions: Functionality • Geographic Areas • Ability to Aggregate DKD Districts • Data Reporting • Change Over Time • Custom / Interactive Maps • User-specified • By Measure • By Geography

39. Considerations • Small Numbers • More Detail in Geography • More Detail in Population Subgroups • Change Over Time • What is the denominator?

40. What Would You Like To See? • Data • Geography • Functionality • Other