Abstract
To measure child well-being, we constructed composite indices with equal weights to component indicators for four domains such as health, safety, education, and economic well-being. The overall index was also constructed in the same way with equal weights to component domains. Based on the index scores (overall and four domains), North Carolina counties were ranked. In addition, urban and rural counties as well as four physiographic regions were also compared in terms of child well-being. According to the findings in the present study, urban counties generally provide better environments for child well-being although they are not statistically different in most domains of child well-being. Among four physiographic regions, the Inner Coastal region provides a significantly lower level of child well-being than the other regions in most domains, whereas the Blue Ridge and the Outer Coastal regions provide a generally higher level of child well-being than the Piedmont and the Outer Coastal Regions in most domains. These findings would not only help citizens make a more informed decision about where to live and where to raise their children, but also provide policy makers and implementers an idea about the strengths and weaknesses in their communities and what they should do to make their communities more attractive.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
The quality of life and well-being will be regarded synonymous in the present study as in other studies (e.g., Rossouw and Naude 2008).
This change rate is between April 1, 2000 and July 1, 2009. The population change rate for the U.S. during the same period is 9.1 percent (US Census Bureau 2010).
The Kolmogorov-Smirnov test is commonly used to check if the distribution is normal (Lilliefors 1967).
Cronbach’s alpha values for health, safety, education, and economic well-being domains were 0.54, 0.70, 0.77, and 0.91, respectively.
As seen in comp1 column of table (c) in Appendix 1, the value was 0.50, 0.47, 0.53, and 0.51 for each domain.
Micropolitan areas were included in rural areas. According to the U.S. Office of Management and Budget’s (2009) notice, a metro area contains a core urban area of 50,000 or more population, and a micro area contains an urban core of at least 10,000 (but less than 50,000) population.
According to the NC geological survey map (2004), seven counties (Polk, Rutherfield, MCdowell, Caldwell, Wilkes, Surry, Burke) were spanned over Blue Ridge and Piedmont, 13 counties (Richmond, Montgomery, Moore, Lee, Harnett, Wake, Johnston, Wilson, Nash, Edgecombe, Halifax, Northampton, Wayne) were spanned over Piedmont and Inner Coastal, and 12 counties (Gates, Perquimans, Chowan, Washington, Beaufort, Pamlico, Craven, Carteret, Onslow, Pender, New Hanover, Brunswick) were spanned over Inner Coastal and Outer Coastal regions.
In the safety domain, the Inner Coastal region had a higher index score than others, but the p-value was a little bit higher (0.6) than the traditional threshold of significance (0.5).
The number of urban and rural counties in each physiographic region is as follows: Blue Ridge (urban: 4, rural: 13), Piedmont (urban 24, rural: 17), Inter Coastal (urban: 11, rural: 19), and Outer Coastal (urban: 1, rural: 11).
References
Ammons, D. (1996). Municipal benchmarks: Assessing local performance and establishing community standards. Thousand Oaks: Sage.
Ammons, D. N., Coe, C., & Lombardo, M. (2001). Performance-comparison projects in local government: participants’ perspectives. Public Administration Review, 61(1), 100–110.
Belanger, K., & Stone, W. (2008). The social service divide: service availability and accessibility in rural versus urban counties and impact on child welfare outcomes. Child Welfare, 87(4), 101–124.
Ben-Arieh, A. (2008). The child indicators movement: past, present, and future. Child Indicators Research, 1(1), 3–16. doi:10.1007/s12187-007-9003-1.
Booysen, F. (2002). An overview and evaluation of composite indices of development. Social Indicators Research, 59(2), 115–151.
Bradshaw, J., & Richardson, D. (2009). An index of child well-being in Europe. [Article]. Child Indicators Research, 2(3), 319–351. doi:10.1007/s12187-009-9037-7.
Bradshaw, J., Noble, M., Bloor, K., Huby, M., McLennan, D., Rhodes, D., et al. (2009). A child well-being index at small area level in England. Child Indicators Research, 2(2), 201–219. doi:10.1007/s12187-008-9022-6.
Bureau of Labor Statistics (2009). Regional and state employment and unemployment—december 2009. http://www.bls.gov/news.release/archives/laus_01222010.pdf. Accessed February 10 2010.
Casas, F., Figuer, C., Gonzalez, M., Malo, S., Alsinet, C., & Subarroca, S. (2007). The well-being of 12- to 16-year-old adolescents and their parents: results from 1999 to 2003 Spanish samples. Social Indicators Research, 83(1), 87–115. doi:10.1007/s11205-006-9059-1.
Cattell, R. B. (1965). Factor analysis: an introduction to essentials. Biometrics, 21, 190–215.
Ceballo, R., McLoyd, V. C., & Toyokawa, T. (2004). The influence of neighborhood quality on adolescents’ educational values and school effort. Journal of Adolescent Research, 19(6), 716–739. doi:10.1177/0743558403260021.
Coulton, C. J., Crampton, D. S., Irwin, M., Spilsbury, J. C., & Korbin, J. E. (2007). How neighborhoods influence child maltreatment: a review of the literature and alternative pathways. Child Abuse & Neglect, 31(11–12), 1117–1142. doi:10.1016/j.chiabu.2007.03.023.
Cummins, R. A. (1996). The domains of life satisfaction: an attempt to order chaos. Social Indicators Research, 38(3), 303–328.
Cummins, R. A. (2000). Objective and subjective quality of life: an interactive model. Social Indicators Research, 52(1), 55–72.
Gade, O., Rex, A. B., Young, J. E., & Perry, L. B. (2002). North carolina: People and environments (2nd ed.). Boone: Parkway.
Gallardo, L., Burillo, P., Garcia-Tascon, M., & Salinero, J. J. (2009). The ranking of the regions with regard to their sports facilities to improve their planning in sport: the case of Spain. Social Indicators Research, 94(2), 297–317. doi:10.1007/s11205-008-9424-3.
Gerson, E. M. (1976). Quality of life. American Sociological Review, 41(5), 793–806.
Ginsberg, L. (1998). Social work in rural communities (3rd ed.). Alexandria: Council on Social Work Education.
Hagerty, M. R., & Land, K. C. (2007). Constructing summary indices of quality of life—a model for the effect of heterogeneous importance weights. [Proceedings Paper]. Sociological Methods & Research, 35(4), 455–496. doi:10.1177/0049124106292354.
Hagerty, M. R., Cummins, R. A., Ferriss, A. L., Land, K., Michalos, A. C., Peterson, M., et al. (2001). Quality of life indexes for national policy: review and agenda for research. Social Indicators Research, 55(1), 1–96.
Hair, J. E., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis (5th ed.). New Jersey: Prentice-Hall.
Hanafin, S., & Brooks, A. M. (2009). From rhetoric to reality: challenges in using data to report on a national set of child well-being indicators. Child Indicators Research, 2(1), 33–55. doi:10.1007/s12187-008-9024-4.
Jordan, T. E. (1983). Developing an international index of quality of life for children—the NICQL index. Journal of the Royal Society of Health, 103(4), 127–130.
Jordan, T. E. (1993). Estimating the quality of life for children around the world: NICQL ‘92. Social Indicators Research, 30(1), 17–38.
Kim, J.-O., & Mueller, C. W. (1978). Factor analysis: Statistical methods and practical issues. Beverly Hills: Sage.
Land, K. C., Lamb, V. L., & Mustillo, S. K. (2001). Child and youth well-being in the united states, 1975–1998: Some findings from a new index. Social Indicators Research, 56(3), 241–320.
Land, K. C., Lamb, V. L., Meadows, S. O., & Taylor, A. (2007). Measuring trends in child well-being: an evidence-based approach. Social Indicators Research, 80(1), 105–132. doi:10.1007/s11205-006-9023-0.
Landsman, M. J. (2002). Rural child welfare practice from an organization-in-environment perspective. Child Welfare, 81(5), 791–819.
Lau, M., & Bradshaw, J. (2010). Child well-being in the pacific rim. [Article]. Child Indicators Research, 3(3), 367–383. doi:10.1007/s12187-010-9064-4.
Lee, J., Lamb, V. L., & Land, K. C. (2009). Composite indices of changes in child and youth well-being in the san Francisco bay area and the state of California, 1995–2005. Child Indicators Research, 2(4), 353–373. doi:10.1007/s12187-009-9039-5.
Liao, P. S. (2009). Parallels between objective indicators and subjective perceptions of quality of life: a study of metropolitan and county areas in Taiwan. Social Indicators Research, 91(1), 99–114. doi:10.1007/s11205-008-9327-3.
Lilliefors, H. W. (1967). On the Kolmogorov-Smirnov test for normality with mean and variance unknown. Journal of the American Statistical Association, 62(318), 399–402.
Lumeng, J. C., Appugliese, D., Cabral, H. J., Bradley, R. H., & Zuckerman, B. (2006). Neighborhood safety and overweight status in children. Archives of Pediatrics & Adolescent Medicine, 160(1), 25–31.
McDonell, J., & Skosireva, A. (2009). Neighborhood characteristics, child maltreatment, and child injuries. Child Indicators Research, 2(2), 133–153. doi:10.1007/s12187-009-9038-6.
McWayne, C. M., McDermott, P. A., Fantuzzo, J. W., & Culhane, D. P. (2007). Employing community data to investigate social and structural dimensions of urban neighborhoods: an early childhood education example. American Journal of Community Psychology, 39(1–2), 47–60. doi:10.1007/s10464-007-9098-z.
Menanteau-Horta, D., & Yigzaw, M. (2002). Indicators of social well-being and elements of child welfare in Minnesota rural counties. Child Welfare, 81(5), 709–735.
Moore, K. A., Vandivere, S., Lippman, L., McPhee, C., & Bloch, M. (2007). An index of the condition of children: the ideal and a less-than-ideal us example. Social Indicators Research, 84(3), 291–331. doi:10.1007/s11205-007-9120-8.
Moore, K. A., Theokas, C., Lippman, L., Bloch, M., Vandivere, S., & O’Hare, W. (2008). A microdata child well-being index: conceptualization, creation, and findings. Child Indicators Research, 1(1), 17–50. doi:10.1007/s12187-007-9000-4.
Musgrave, R. A. (1939). The voluntary exchange theory of public economy. Quarterly Journal of Economics, 53(2), 213–237.
Niclasen, B., & Kohler, L. (2009). Core indicators of children’s health and well-being at the municipal level in Greenland. Child Indicators Research, 2(2), 221–244. doi:10.1007/s12187-009-9035-9.
North Carolina Geological Survey. (2004). Physiography of north carolina. Raleigh: Department of Environment and Natural Resources.
Norton, R. K. (2007). Planning for school facilities—school board decision making and local coordination in Michigan. Journal of Planning Education and Research, 26(4), 478–496. doi:10.1177/0739456x07299844.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York: McGraw-Hill.
O’Campo, P., Rao, R. P., Gielen, A. C., Royalty, W., & Wilson, M. (2000). Injury-producing events among children in low-income communities: the role of community characteristics. Journal of Urban Health-Bulletin of the New York Academy of Medicine, 77(1), 34–49.
Richardson, D., Hoelscher, P., & Bradshaw, J. (2008). Child well-being in central and eastern European countries (CEE) and the commonwealth of independent states (CIS). [Article]. Child Indicators Research, 1(3), 211–250. doi:10.1007/s12187-008-9020-8.
Rossouw, S., & Naude, W. (2008). The non-economic quality of life on a sub-national level in South Africa. Social Indicators Research, 86(3), 433–452. doi:10.1007/s11205-007-9178-3.
Samuelson, P. A. (1954). The pure theory of public expenditure. The Review of Economics and Statistics, 36(4), 387–389.
Sirgy, M. J., Michalos, A. C., Ferriss, A. L., Easterlin, R. A., Patrick, D., & Pavot, W. (2006). The quality-of-life (QOL) research movement: past, present, and future. Social Indicators Research, 76(3), 343–466. doi:10.1007/s11205-005-2877-8.
State Bureau of Investigation (2009). Crime in north carolina 2008: Annual summary report of 2008 uniform crime reporting data. North Carolina Department of Justice.
The Annie E. Casey Foundation. (2010). 2009 kids count data book: State profiles of child well-being. Baltimore: The Annie E. Casey Foundation.
Tiebout, C. M. (1956). A pure theory of local expenditures. The Journal of Political Economy, 64(5), 416–424.
U.S. Census Bureau (2010). State & county quick facts.
Vandivere, S., & McPhee, C. (2008). Methods for tabulating indices of child well-being and context: an illustration and comparison of performance in 13 American states. Child Indicators Research, 1(3), 251–290. doi:10.1007/s12187-008-9009-3.
Whitaker, W. H. (1984). A survey of perceptions of social work practice in rural and urban areas. Human Services in the Rural Environment, 9(3), 12–19.
Xue, Y., Zimmerman, M. A., & Caldwell, C. H. (2007). Neighborhood residence and cigarette smoking among urban youths: the protective role of prosocial activities. American Journal of Public Health, 97(10), 1865–1872. doi:10.2105/ajph.2005.081307.
Author information
Authors and Affiliations
Corresponding author
Appendices
Appendix 1. Principal Component Analysis Results for Component Domains
a. Principal components/correlation
Component | Eigenvalue | Difference | Proportion | Cumulative |
|---|---|---|---|---|
Comp1 | 2.6612 | 2.09537 | 0.6653 | 0.6653 |
Comp2 | .5658 | .09731 | 0.1415 | 0.8068 |
Comp3 | .4685 | .16408 | 0.1171 | 0.9239 |
Comp4 | .3044 | 0.0761 | 1 |
Number of observation—100
b. Scree plot
c. Principal components (eigenvector)
Variable | Comp1 | Comp2 | Comp3 | Comp4 | Unexplained |
|---|---|---|---|---|---|
Health | 0.4965 | −0.535 | 0.4924 | 0.4742 | 0 |
Safety | 0.4709 | 0.7202 | 0.4779 | −0.1767 | 0 |
Education | 0.5256 | −0.3707 | −0.2292 | −0.7306 | 0 |
Economic Wa | 0.5055 | 0.24 | −0.6904 | 0.4584 | 0 |
aEconomic Well-being
Appendix 2. Comparison Between Urban and Rural Counties (t-test)
(a) t-test results
Index | Levene’s Test for Equality of Variances | T-Test for Equality of Means | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
F | Sig. | t | df | Sig. (2-tailed) | Mean Difference | Std. Error Difference | 95% Confidence interval | |||
Lower | Upper | |||||||||
Overall | Equala | .773 | .381 | −2.43 | 98.00 | 0.02 | −0.29 | 0.12 | −0.53 | −0.05 |
Unequalb | −2.48 | 88.97 | 0.02 | −0.29 | 0.12 | −0.53 | −0.06 | |||
Health | Equal | .766 | .384 | −1.18 | 98.00 | 0.24 | −0.16 | 0.13 | −0.42 | 0.11 |
Unequal | −1.22 | 92.47 | 0.23 | −0.16 | 0.13 | −0.41 | 0.10 | |||
Safety | Equal | .118 | .732 | −0.63 | 98.00 | 0.53 | −0.08 | 0.13 | −0.34 | 0.18 |
Unequal |
|
| −0.64 | 90.57 | 0.52 | −0.08 | 0.13 | −0.33 | 0.17 | |
Education | Equal | 2.283 | .134 | −0.72 | 98.00 | 0.47 | −0.11 | 0.16 | −0.43 | 0.20 |
Unequal |
|
| −0.76 | 96.08 | 0.45 | −0.11 | 0.15 | −0.41 | 0.18 | |
Economic Well-being | Equal | .592 | .444 | −4.98 | 98.00 | 0.00 | −0.82 | 0.16 | −1.14 | −0.49 |
Unequal |
|
| −5.05 | 87.47 | 0.00 | −0.82 | 0.16 | −1.14 | −0.50 | |
aEqual variances assumed
bEqual variances not assumed
(b) Descriptive statistics of urban and rural county indices
Index | Urban/rural | N | Mean | Std. deviation | Min | Max |
|---|---|---|---|---|---|---|
Overall | Urban | 40 | −0.18 | 0.56 | −1.14 | 1.36 |
Rural | 60 | 0.11 | 0.61 | −1.15 | 1.63 | |
Health | Urban | 40 | −0.09 | 0.58 | −1.13 | 1.52 |
Rural | 60 | 0.06 | 0.69 | −1.46 | 1.64 | |
Safety | Urban | 40 | −0.05 | 0.59 | −1.07 | 1.24 |
Rural | 60 | 0.03 | 0.67 | −1.50 | 2.46 | |
Education | Urban | 40 | −0.07 | 0.65 | −1.07 | 1.25 |
Rural | 60 | 0.05 | 0.85 | −1.83 | 2.12 | |
Economic Well-being | Urban | 40 | −0.49 | 0.77 | −2.04 | 1.74 |
Rural | 60 | 0.33 | 0.82 | −1.82 | 1.84 |
Appendix 3. Comparison Among Physiographic Regions (ANOVA)
(a) Test for homogeneity of variances
Index | Levene statistic | df1 | df2 | Sig. |
|---|---|---|---|---|
Overall | 1.978 | 3 | 96 | .122 |
Health | 3.481 | 3 | 96 | .019 |
Safety | 1.506 | 3 | 96 | .218 |
Education | 2.015 | 3 | 96 | .117 |
Economic Well-being | 1.710 | 3 | 96 | .170 |
The health index (p < 0.05) does not have equal variances
(b) Descriptive statistics
N | Mean | Standard deviation | Std. error | 95% Confidence interval for mean | Minimum | Maximum | |||
|---|---|---|---|---|---|---|---|---|---|
Lower bound | Upper bound | ||||||||
Overall | Blue Ridge | 17 | −0.32 | 0.37 | 0.09 | −0.51 | −0.12 | −1.15 | 0.34 |
Piedmont | 41 | −0.11 | 0.52 | 0.08 | −0.27 | 0.06 | −1.14 | 1.38 | |
Inner Coastal | 30 | 0.41 | 0.62 | 0.11 | 0.18 | 0.64 | −0.66 | 1.63 | |
Outer Coastal | 12 | −0.21 | 0.63 | 0.18 | −0.61 | 0.19 | −1.02 | 0.88 | |
Total | 100 | 0.00 | 0.60 | 0.06 | −0.12 | 0.12 | −1.15 | 1.63 | |
Health | Blue Ridge | 17 | −0.53 | 0.39 | 0.09 | −0.73 | −0.33 | −1.18 | 0.11 |
Piedmont | 41 | 0.01 | 0.49 | 0.08 | −0.15 | 0.16 | −1.13 | 1.64 | |
Inner Coastal | 30 | 0.40 | 0.72 | 0.13 | 0.13 | 0.67 | −1.01 | 1.59 | |
Outer Coastal | 12 | −0.27 | 0.62 | 0.18 | −0.67 | 0.12 | −1.46 | 0.43 | |
Total | 100 | 0.00 | 0.65 | 0.06 | −0.13 | 0.13 | −1.46 | 1.64 | |
Safety | Blue Ridge | 17 | −0.19 | 0.51 | 0.12 | −0.45 | 0.07 | −0.86 | 1.17 |
Piedmont | 41 | −0.08 | 0.56 | 0.09 | −0.26 | 0.09 | −1.10 | 1.05 | |
Inner Coastal | 30 | 0.32 | 0.73 | 0.13 | 0.05 | 0.59 | −0.63 | 2.46 | |
Outer Coastal | 12 | −0.25 | 0.56 | 0.16 | −0.61 | 0.11 | −1.50 | 0.41 | |
Total | 100 | 0.00 | 0.64 | 0.06 | −0.13 | 0.13 | −1.50 | 2.46 | |
Education | Blue Ridge | 17 | −0.59 | 0.50 | 0.12 | −0.85 | −0.33 | −1.83 | 0.26 |
Piedmont | 41 | −0.05 | 0.65 | 0.10 | −0.25 | 0.16 | −1.16 | 1.58 | |
Inner Coastal | 30 | 0.50 | 0.72 | 0.13 | 0.23 | 0.76 | −0.82 | 2.12 | |
Outer Coastal | 12 | −0.24 | 0.91 | 0.26 | −0.82 | 0.34 | −1.29 | 1.81 | |
Total | 100 | 0.00 | 0.77 | 0.08 | −0.15 | 0.15 | -1.83 | 2.12 | |
Economic Well-being | Blue Ridge | 17 | 0.04 | 0.65 | 0.16 | −0.30 | 0.37 | −0.97 | 1.24 |
Piedmont | 41 | −0.30 | 0.83 | 0.13 | −0.57 | −0.04 | −2.04 | 1.71 | |
Inner Coastal | 30 | 0.43 | 0.87 | 0.16 | 0.10 | 0.75 | −1.07 | 1.84 | |
Outer Coastal | 12 | −0.08 | 1.11 | 0.32 | −0.79 | 0.62 | −1.82 | 1.32 | |
Total | 100 | 0.00 | 0.90 | 0.09 | −0.18 | 0.18 | −2.04 | 1.84 | |
(c) ANOVA results
Index | Sum of squares | df | Mean square | F | Sig. | |
|---|---|---|---|---|---|---|
Overall | Between groups | 7.725 | 3 | 2.575 | 8.683 | .000 |
Within groups | 28.470 | 96 | .297 | |||
Total | 36.196 | 99 | ||||
Healtha | Between groups | 10.293 | 3 | 3.431 | 10.466 | .000 |
Within groups | 31.470 | 96 | .328 | |||
Total | 41.763 | 99 | ||||
Safety | Between groups | 4.651 | 3 | 1.550 | 4.204 | .008 |
Within groups | 35.406 | 96 | .369 | |||
Total | 40.057 | 99 | ||||
Education | Between groups | 14.085 | 3 | 4.695 | 10.010 | .000 |
Within groups | 45.027 | 96 | .469 | |||
Total | 59.112 | 99 | ||||
Economic well-being | Between groups | 9.352 | 3 | 3.117 | 4.270 | .007 |
Within groups | 70.084 | 96 | .730 | |||
Total | 79.436 | 99 | ||||
aDue to unequal variances in health as seen in part (a), Kruskal-Wallis (K-W) test was conducted. K-W results confirmed that there were significant differences in health among physiographic regions
(d) Post-hoc test results (the Sheffee method used)
Index | (I) Physiographic region | (J) Physiographic region | Mean difference (I-J) | Std. error | Sig. | 95% Confidence interval | |
|---|---|---|---|---|---|---|---|
Lower bound | Upper bound | ||||||
Overall | Blue Ridge | 2 | −0.21 | 0.16 | 0.61 | −0.66 | 0.24 |
3 | −0.73 | 0.17 | 0.00 | −1.20 | −0.26 | ||
4 | −0.11 | 0.21 | 0.97 | −0.69 | 0.48 | ||
Piedmont | 1 | 0.21 | 0.16 | 0.61 | −0.24 | 0.66 | |
3 | −0.52 | 0.13 | 0.00 | −0.89 | −0.14 | ||
4 | 0.10 | 0.18 | 0.95 | −0.40 | 0.61 | ||
Inner Coastal | 1 | 0.73 | 0.17 | 0.00 | 0.26 | 1.20 | |
2 | 0.52 | 0.13 | 0.00 | 0.14 | 0.89 | ||
4 | 0.62 | 0.19 | 0.01 | 0.09 | 1.15 | ||
Outer Coastal | 1 | 0.11 | 0.21 | 0.97 | −0.48 | 0.69 | |
2 | −0.10 | 0.18 | 0.95 | −0.61 | 0.40 | ||
3 | −0.62 | 0.19 | 0.01 | −1.15 | −0.09 | ||
Health | Blue Ridge | 2 | −0.53 | 0.17 | 0.02 | −1.00 | −0.06 |
3 | −0.92 | 0.17 | 0.00 | −1.42 | −0.43 | ||
4 | −0.26 | 0.22 | 0.71 | −0.87 | 0.36 | ||
Piedmont | 1 | 0.53 | 0.17 | 0.02 | 0.06 | 1.00 | |
3 | −0.39 | 0.14 | 0.05 | −0.78 | 0.00 | ||
4 | 0.28 | 0.19 | 0.53 | −0.26 | 0.81 | ||
Inner Coastal | 1 | 0.92 | 0.17 | 0.00 | 0.43 | 1.42 | |
2 | 0.39 | 0.14 | 0.05 | 0.00 | 0.78 | ||
4 | 0.67 | 0.20 | 0.01 | 0.11 | 1.22 | ||
Outer Coastal | 1 | 0.26 | 0.22 | 0.71 | −0.36 | 0.87 | |
2 | −0.28 | 0.19 | 0.53 | −0.81 | 0.26 | ||
3 | −0.67 | 0.20 | 0.01 | −1.22 | −0.11 | ||
Safety | Blue Ridge | 2 | −0.11 | 0.18 | 0.95 | −0.61 | 0.39 |
3 | −0.51 | 0.18 | 0.06 | −1.03 | 0.02 | ||
4 | 0.06 | 0.23 | 0.99 | −0.59 | 0.71 | ||
Piedmont | 1 | 0.11 | 0.18 | 0.95 | −0.39 | 0.61 | |
3 | −0.40 | 0.15 | 0.06 | −0.81 | 0.02 | ||
4 | 0.17 | 0.20 | 0.87 | −0.40 | 0.74 | ||
Inner Coastal | 1 | 0.51 | 0.18 | 0.06 | −0.02 | 1.03 | |
2 | 0.40 | 0.15 | 0.06 | −0.02 | 0.81 | ||
4 | 0.57 | 0.21 | 0.06 | −0.02 | 1.16 | ||
Outer Coastal | 1 | −0.06 | 0.23 | 0.99 | −0.71 | 0.59 | |
2 | −0.17 | 0.20 | 0.87 | −0.74 | 0.40 | ||
3 | −0.57 | 0.21 | 0.06 | −1.16 | 0.02 | ||
Education | Blue Ridge | 2 | −0.54 | 0.20 | 0.06 | −1.11 | 0.02 |
3 | −1.09 | 0.21 | 0.00 | −1.68 | −0.50 | ||
4 | −0.35 | 0.26 | 0.60 | −1.09 | 0.38 | ||
Piedmont | 1 | 0.54 | 0.20 | 0.06 | −0.02 | 1.11 | |
3 | −0.54 | 0.16 | 0.02 | −1.01 | −0.08 | ||
4 | 0.19 | 0.22 | 0.87 | −0.45 | 0.83 | ||
Inner Coastal | 1 | 1.09 | 0.21 | 0.00 | 0.50 | 1.68 | |
2 | 0.54 | 0.16 | 0.02 | 0.08 | 1.01 | ||
4 | 0.73 | 0.23 | 0.02 | 0.07 | 1.40 | ||
Outer Coastal | 1 | 0.35 | 0.26 | 0.60 | −0.38 | 1.09 | |
2 | −0.19 | 0.22 | 0.87 | −0.83 | 0.45 | ||
3 | −0.73 | 0.23 | 0.02 | −1.40 | −0.07 | ||
Economic well-being | Blue Ridge | 2 | 0.34 | 0.25 | 0.60 | −0.36 | 1.04 |
3 | −0.39 | 0.26 | 0.52 | −1.13 | 0.35 | ||
4 | 0.12 | 0.32 | 0.99 | −0.80 | 1.04 | ||
Piedmont | 1 | −0.34 | 0.25 | 0.60 | −1.04 | 0.36 | |
3 | −0.73 | 0.21 | 0.01 | −1.31 | −0.15 | ||
4 | −0.22 | 0.28 | 0.89 | −1.02 | 0.58 | ||
Inner Coastal | 1 | 0.39 | 0.26 | 0.52 | −0.35 | 1.13 | |
2 | 0.73 | 0.21 | 0.01 | 0.15 | 1.31 | ||
4 | 0.51 | 0.29 | 0.39 | −0.32 | 1.34 | ||
Outer Coastal | 1 | −0.12 | 0.32 | 0.99 | −1.04 | 0.80 | |
2 | 0.22 | 0.28 | 0.89 | −0.58 | 1.02 | ||
3 | −0.51 | 0.29 | 0.39 | −1.34 | 0.32 | ||
- 1. Blue Ridge, 2. Piedmont, 3. Inner Coastal, 4. Outer Coastal
- Significant cases are marked in boldface. If cases are not significant but p-vale is less than .10, they are italicized (see the safety domain)
Appendix 4. Overall Index of Child Well-being for North Carolina Counties
County | Z-score | County | Z-score | County | Z-score | County | Z-score | County | Z-score |
|---|---|---|---|---|---|---|---|---|---|
Watauga | −1.152 | New Hanover | −0.468 | Brunswick | −0.212 | Rockingham | 0.095 | Wilson | 0.479 |
Wake | −1.143 | Pender | −0.466 | Craven | −0.201 | Mitchell | 0.117 | Chowan | 0.488 |
Camden | −1.025 | Yancey | −0.456 | Surry | −0.179 | Pasquotank | 0.149 | Sampson | 0.545 |
Davie | −1.016 | Davidson | −0.400 | Granville | −0.173 | Wilkes | 0.174 | Nash | 0.575 |
Union | −1.015 | Ashe | −0.399 | Franklin | −0.170 | Perquimans | 0.180 | Hertford | 0.582 |
Orange | −0.987 | Haywood | −0.338 | Caldwell | −0.163 | Person | 0.196 | Bladen | 0.728 |
Currituck | −0.974 | Hyde | −0.329 | Avery | −0.155 | Cleveland | 0.209 | Richmond | 0.755 |
Carteret | −0.881 | Stokes | −0.288 | Stanly | −0.128 | Gaston | 0.213 | Northampton | 0.765 |
Dare | −0.822 | Yadkin | −0.285 | Mecklenburg | −0.122 | McDowell | 0.256 | Greene | 0.830 |
Henderson | −0.765 | Catawba | −0.278 | Harnett | −0.111 | Graham | 0.277 | Bertie | 0.882 |
Chatham | −0.673 | Alleghany | −0.276 | Guilford | −0.071 | Duplin | 0.290 | Washington | 0.884 |
Cabarrus | −0.668 | Onslow | −0.273 | Caswell | −0.069 | Beaufort | 0.301 | Anson | 0.887 |
Johnston | −0.661 | Macon | −0.263 | Rowan | −0.061 | Hoke | 0.303 | Columbus | 0.929 |
Moore | −0.660 | Jackson | −0.252 | Cherokee | −0.035 | Swain | 0.337 | Warren | 0.947 |
Clay | −0.608 | Pamlico | −0.251 | Lee | −0.001 | Wayne | 0.337 | Lenoir | 0.964 |
Transylvania | −0.597 | Madison | −0.250 | Alamance | 0.018 | Montgomery | 0.361 | Scotland | 1.081 |
Buncombe | −0.579 | Tyrrell | −0.248 | Jones | 0.025 | Rutherford | 0.380 | Edgecombe | 1.365 |
Iredell | −0.566 | Burke | −0.239 | Gates | 0.025 | Cumberland | 0.399 | Vance | 1.376 |
Polk | −0.505 | Randolph | −0.238 | Forsyth | 0.054 | Martin | 0.408 | Halifax | 1.539 |
Alexander | −0.493 | Lincoln | −0.236 | Durham | 0.078 | Pitt | 0.464 | Robeson | 1.630 |
- Overall index consists of four domains such as health, safety, education, and economic well-being
- Counties were ordered from low to high scores, based on their z-scores
- A lower z-score indicates a higher status of overall child well-being because indices of all component domains measured negative constructs
Appendix 5. Health Index of Child Well-being for North Carolina Counties
County | Z-score | County | Z-score | County | Z-score | County | Z-score | County | Z-score |
|---|---|---|---|---|---|---|---|---|---|
Tyrrell | −1.458 | Brunswick | −0.601 | Cherokee | −0.154 | Guilford | 0.135 | Perquimans | 0.425 |
Clay | −1.178 | Ashe | −0.560 | Haywood | −0.152 | Surry | 0.146 | Gates | 0.510 |
Davie | −1.129 | Chatham | −0.546 | Davidson | −0.115 | Durham | 0.187 | Sampson | 0.554 |
Moore | −1.014 | Buncombe | −0.538 | Iredell | −0.098 | Rutherford | 0.188 | Person | 0.567 |
Carteret | −1.007 | Jones | −0.518 | Rockingham | −0.088 | Camden | 0.214 | Nash | 0.642 |
Alleghany | −0.962 | Union | −0.486 | Wilkes | −0.076 | Anson | 0.220 | Forsyth | 0.647 |
Watauga | −0.950 | Macon | −0.468 | McDowell | −0.076 | Wilson | 0.220 | Warren | 0.658 |
Yancey | −0.909 | Swain | −0.400 | Catawba | −0.072 | Chowan | 0.227 | Richmond | 0.753 |
Alexander | −0.904 | Onslow | −0.390 | Harnett | −0.057 | Craven | 0.228 | Hertford | 0.791 |
Hyde | −0.828 | Caswell | −0.358 | Northampton | −0.048 | Gaston | 0.233 | Polk | 0.792 |
Henderson | −0.793 | Johnston | −0.348 | Avery | 0.009 | Alamance | 0.248 | Martin | 0.816 |
Transylvania | −0.756 | Lee | −0.297 | Washington | 0.016 | Duplin | 0.312 | Scotland | 0.844 |
Currituck | −0.717 | Rowan | −0.254 | Mecklenburg | 0.033 | Pasquotank | 0.335 | Halifax | 1.033 |
Jackson | −0.671 | Burke | −0.246 | Graham | 0.036 | Stanly | 0.372 | Robeson | 1.254 |
Orange | −0.648 | Cabarrus | −0.244 | Beaufort | 0.055 | Lincoln | 0.375 | Lenoir | 1.273 |
New Hanover | −0.644 | Randolph | −0.229 | Cleveland | 0.064 | Cumberland | 0.375 | Bertie | 1.331 |
Pender | −0.643 | Franklin | −0.219 | Hoke | 0.067 | Wayne | 0.377 | Greene | 1.493 |
Wake | −0.638 | Caldwell | −0.194 | Pamlico | 0.096 | Yadkin | 0.378 | Edgecombe | 1.524 |
Madison | −0.615 | Stokes | −0.194 | Mitchell | 0.112 | Bladen | 0.387 | Columbus | 1.589 |
Dare | −0.611 | Granville | −0.192 | Montgomery | 0.114 | Pitt | 0.402 | Vance | 1.638 |
- Health index consists of four indicators such as infant and children death by illness rate, infant mortality rate, teen pregnancy rate, and low birthweight rate
- Counties were ordered from low to high scores, based on their z-scores
- A lower z-score indicates a higher status of child well-being in that domain because negative constructs of child well-being were measured by most indicators and when positive constructs were measured, we put opposite signs to their z-scores
Appendix 6. Safety Index of Child Well-being for North Carolina Counties
County | Z-score | County | Z-score | County | Z-score | County | Z-score | County | Z-score |
|---|---|---|---|---|---|---|---|---|---|
Camden | −1.496 | Surry | −0.556 | Buncombe | −0.214 | Tyrrell | 0.118 | Guilford | 0.497 |
Polk | −1.098 | Perquimans | −0.552 | Cherokee | −0.210 | Pasquotank | 0.121 | Richmond | 0.506 |
Davie | −1.074 | Randolph | −0.523 | Iredell | −0.201 | Martin | 0.135 | Rutherford | 0.509 |
Wake | −0.879 | Cabarrus | −0.471 | Clay | −0.165 | Forsyth | 0.146 | Pitt | 0.562 |
Watauga | −0.862 | Davidson | −0.444 | Harnett | −0.151 | Beaufort | 0.205 | Columbus | 0.604 |
Caswell | −0.859 | Pender | −0.406 | Burke | −0.148 | Person | 0.208 | Mecklenburg | 0.619 |
Orange | −0.836 | Pamlico | −0.398 | Craven | −0.124 | Rowan | 0.231 | Vance | 0.653 |
Ashe | −0.776 | Henderson | −0.376 | Alleghany | −0.099 | Lee | 0.245 | McDowell | 0.655 |
Currituck | −0.735 | Alexander | −0.364 | Rockingham | −0.078 | Warren | 0.266 | Wilson | 0.682 |
Yancey | −0.717 | Madison | −0.360 | Greene | −0.065 | Sampson | 0.278 | Wayne | 0.694 |
Union | −0.709 | Stanly | −0.353 | Moore | −0.059 | New Hanover | 0.301 | Graham | 0.739 |
Hyde | −0.674 | Avery | −0.341 | Stokes | −0.052 | Montgomery | 0.302 | Anson | 0.985 |
Chatham | −0.651 | Carteret | −0.330 | Dare | −0.052 | Northampton | 0.303 | Nash | 1.053 |
Jones | −0.634 | Granville | −0.324 | Alamance | −0.044 | Onslow | 0.318 | Swain | 1.171 |
Johnston | −0.622 | Haywood | −0.272 | Duplin | −0.041 | Wilkes | 0.343 | Edgecombe | 1.197 |
Yadkin | −0.621 | Caldwell | −0.243 | Brunswick | −0.036 | Washington | 0.388 | Cumberland | 1.238 |
Franklin | −0.619 | Lincoln | −0.236 | Bladen | −0.001 | Durham | 0.396 | Lenoir | 1.301 |
Hertford | −0.594 | Hoke | −0.235 | Mitchell | 0.027 | Gaston | 0.400 | Scotland | 1.342 |
Bertie | −0.576 | Gates | −0.228 | Jackson | 0.034 | Chowan | 0.406 | Halifax | 1.380 |
Macon | −0.561 | Transylvania | −0.220 | Catawba | 0.053 | Cleveland | 0.492 | Robeson | 2.460 |
- Safety index consists of four indicators such as violent crime rate, child abuse & neglect rate, delinquency rate, and homicide rate
- Counties were ordered from low to high scores, based on their z-scores
- A lower z-score indicates a higher status of child well-being in safety because only negative constructs of child well-being were measured
Appendix 7. Education Index of Child Well-being for North Carolina Counties
County | Z-score | County | Z-score | County | Z-score | County | Z-score | County | Z-score |
|---|---|---|---|---|---|---|---|---|---|
Watauga | −1.826 | Buncombe | −0.693 | Alexander | −0.208 | Alamance | 0.147 | Lenoir | 0.572 |
Dare | −1.286 | Catawba | −0.686 | Macon | −0.193 | Randolph | 0.190 | Nash | 0.632 |
Carteret | −1.254 | Currituck | −0.671 | Mitchell | −0.161 | Cumberland | 0.214 | Franklin | 0.649 |
Polk | −1.161 | Yancey | −0.642 | Cleveland | −0.149 | Swain | 0.261 | Durham | 0.666 |
Henderson | −1.069 | Surry | −0.636 | Caldwell | −0.142 | Wayne | 0.267 | Jones | 0.746 |
Union | −1.042 | Johnston | −0.606 | Hyde | −0.135 | Scotland | 0.301 | Pitt | 0.803 |
Wake | −1.020 | Pender | −0.558 | Chatham | −0.110 | Person | 0.312 | Edgecombe | 0.998 |
Camden | −1.002 | Haywood | −0.556 | Brunswick | −0.065 | Beaufort | 0.326 | Sampson | 1.009 |
Iredell | −0.948 | New Hanover | −0.548 | Rowan | 0.002 | Gaston | 0.342 | Bladen | 1.040 |
Burke | −0.932 | Craven | −0.526 | Forsyth | 0.016 | Rutherford | 0.353 | Northampton | 1.175 |
Clay | −0.921 | Cabarrus | −0.525 | Mecklenburg | 0.025 | Perquimans | 0.372 | Anson | 1.180 |
Graham | −0.907 | Davidson | −0.502 | Madison | 0.036 | Rockingham | 0.396 | Robeson | 1.216 |
Transylvania | −0.894 | Avery | −0.493 | Stanly | 0.046 | Gates | 0.398 | Hoke | 1.243 |
Tyrrell | −0.873 | Lincoln | −0.479 | McDowell | 0.052 | Richmond | 0.421 | Greene | 1.254 |
Moore | −0.821 | Ashe | −0.462 | Jackson | 0.056 | Granville | 0.446 | Hertford | 1.377 |
Alleghany | −0.807 | Stokes | −0.333 | Lee | 0.066 | Duplin | 0.509 | Bertie | 1.432 |
Cherokee | −0.779 | Guilford | −0.310 | Martin | 0.074 | Chowan | 0.516 | Vance | 1.498 |
Pamlico | −0.770 | Yadkin | −0.303 | Harnett | 0.079 | Wilson | 0.521 | Warren | 1.578 |
Davie | −0.726 | Onslow | −0.297 | Pasquotank | 0.106 | Columbus | 0.526 | Washington | 1.813 |
Orange | −0.718 | Wilkes | −0.284 | Montgomery | 0.125 | Caswell | 0.531 | Halifax | 2.117 |
- Education index consists of four indicators such as high school dropout rate, combined (reading and math) proficient rates for third grade students, combined (reading and math) proficient rates for eight grade students, and SAT score
- Counties were ordered from low to high scores, based on their z-scores
- A lower z-score indicates a higher status of child well-being in education because when positive constructs were measured (i.e., proficient rates and SAT score), we put opposite signs to their z-scores to be consistent with the other negative indicator (i.e., dropout rate)
Appendix 8. Economic Well-being Index of Child Well-being for North Carolina Counties
County | Z-score | County | Z-score | County | Z-score | County | Z-score | County | Z-score |
|---|---|---|---|---|---|---|---|---|---|
Wake | −2.036 | Granville | −0.624 | Alamance | −0.279 | Swain | 0.315 | Hertford | 0.753 |
Union | −1.824 | Guilford | −0.606 | Pender | −0.257 | Hyde | 0.320 | Alleghany | 0.765 |
Camden | −1.816 | Lincoln | −0.606 | Cumberland | −0.231 | Surry | 0.329 | Chowan | 0.801 |
Currituck | −1.772 | Yadkin | −0.594 | Rowan | −0.222 | Sampson | 0.338 | Montgomery | 0.902 |
Orange | −1.746 | Forsyth | −0.594 | Clay | −0.167 | Burke | 0.368 | Columbus | 0.996 |
Cabarrus | −1.432 | Gates | −0.579 | Brunswick | −0.147 | Duplin | 0.382 | Cherokee | 1.001 |
Chatham | −1.386 | Stanly | −0.576 | Gaston | −0.122 | McDowell | 0.393 | Anson | 1.162 |
Dare | −1.337 | Stokes | −0.573 | Caldwell | −0.071 | Caswell | 0.413 | Tyrrell | 1.222 |
Mecklenburg | −1.164 | Polk | −0.551 | Madison | −0.060 | Cleveland | 0.427 | Graham | 1.238 |
Davie | −1.136 | Davidson | −0.538 | Nash | −0.025 | Yancey | 0.445 | Warren | 1.283 |
Johnston | −1.070 | Transylvania | −0.519 | Lee | −0.017 | Rutherford | 0.472 | Washington | 1.318 |
Iredell | −1.017 | Alexander | −0.495 | Wayne | 0.009 | Perquimans | 0.474 | Richmond | 1.338 |
New Hanover | −0.980 | Franklin | −0.490 | Pasquotank | 0.032 | Mitchell | 0.490 | Bertie | 1.340 |
Watauga | −0.971 | Jackson | −0.426 | Pamlico | 0.067 | Wilson | 0.494 | Bladen | 1.485 |
Durham | −0.938 | Catawba | −0.408 | Pitt | 0.087 | Jones | 0.507 | Robeson | 1.590 |
Carteret | −0.931 | Randolph | −0.390 | Hoke | 0.135 | Martin | 0.609 | Halifax | 1.627 |
Buncombe | −0.870 | Craven | −0.380 | Rockingham | 0.151 | Beaufort | 0.618 | Northampton | 1.629 |
Henderson | −0.825 | Haywood | −0.374 | Macon | 0.172 | Greene | 0.635 | Vance | 1.714 |
Moore | −0.746 | Harnett | −0.315 | Avery | 0.203 | Lenoir | 0.711 | Edgecombe | 1.741 |
Onslow | −0.723 | Person | −0.304 | Ashe | 0.204 | Wilkes | 0.715 | Scotland | 1.836 |
- Economic well-being index consists of four indicators such as unemployment rate, free/reduced lunch rate, poverty rate, and median household income
- Counties were ordered from low to high scores, based on their z-scores
- A lower z-score indicates a higher status of child well-being in the economic well-being domain because negative constructs of child well-being were measured by most indicators, and when positive constructs were measured (i.e., median household income), we put opposite signs to their z-scores to be consistent with other negative indicators
Rights and permissions
About this article
Cite this article
Hur, Y., Testerman, R. An Index of Child Well-Being at a Local Level in the U.S.: The Case of North Carolina Counties. Child Ind Res 5, 29–53 (2012). https://doi.org/10.1007/s12187-010-9087-x
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12187-010-9087-x