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A Simplified Indicator of Social Well-Being in the United States: Examining the Ecological Impact of Family Formation within a County Level Framework

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Abstract

In 1995, a study entitled “Does Marriage Matter?” was published by Linda Waite in the journal of Demography, which was concerned with the direction of such causal relationships. While Waite’s examination of the causal relationships associated with marriage, and most other analyses of this type, is primarily concerned with the individual level effects of marriage on a variety of outcomes, little is understood concerning the ecological effect of community marriage rates on levels of aggregate well-being. This study aims to contribute to this gap through the implementation of a recent conceptualization of social well-being as a multi-dimensional measure incorporating both biological, operationalized as average life expectancy, and social phenomena, operationalized as, community level crime rates (Raphael, Making the links: what do health promotion, crime prevention, and social development have in common? in 2004). It is important to understand such aggregate level effects in the face of the existing literature, which relies heavily on relational associations which could be subject to ecological fallacy. Analytic techniques incorporate Exploratory Spatial Data Analysis and spatial regression techniques, due to the high existence of spatial autocorrelation often evident in census data, as a way of understanding the effect of the aggregate level marriage rate on the constructed social well being indicator.

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Notes

  1. Both the percent of the households in the community that are headed by a single parent and the percent of the individuals in the community that are divorced were examined in relation to potential high levels of correlation with the percent of the population measured. Neither produced correlations, in absolute terms above 0.4, making them acceptable for inclusion as determinants. Furthermore, all Variance Inflation Factors and Tolerance scores associated with subsequent multivariate modeling procedures lacked evidence of colinearity.

  2. The most common case is that of positive autocorrelation in which the local unit’s (i) value on a variable of interest is significantly, and positively, correlated with the average neighborhood (j) value. Less frequently, negative autocorrelation refers to an instance when a local unit’s (i) value pertaining to a specific variable is significantly in opposition to the neighborhood’s (j) average value.

  3. Due to higher than sought after correlations between a few of the independent variables with the social disorganization framework, colinearity diagnostics were examined in conjunction with the coefficient estimates in order to ensure that the models did not violate the linear regression assumption. On that point, all models exhibited high levels of non-orthogonality, indicating no colinearity.

  4. Geoda is an open source software package, developed by Luc Anselin, specifically designed for the analysis of data through a series of techniques designed for the identification and controlling of spatially correlated data.

  5. Ultimately, the type of spatial autocorrelation identified involved correlating error terms within local neighborhoods. In regards to the analysis, this means that a traditional OLS approach violates the assumption of uncorrelated error terms.

References

  • Anselin, L. (1988). Spatial econometrics: Methods and models. Boston, MA: Kluwer Academic.

    Google Scholar 

  • Anselin, L. (1990). Spatial dependence and spatial structural instability in applied regression analysis. Journal of Regional Science, 30(2), 185.

    Article  Google Scholar 

  • Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27, 93–115.

    Article  Google Scholar 

  • Anselin, L. (1999). The future of analysis in the social sciences. Geographic Information Sciences, 5(2), 67–76.

    Google Scholar 

  • Anselin, L. (2000). GIS, spatial econometrics and social science research. Journal of Geographical Systems, 2, 11–15.

    Article  Google Scholar 

  • Anselin, L. (2001a). Spatial econometrics. In B. Baltagi (Ed.), Companion to econometrics (pp. 310–330). Oxford, England: Basil Blackwell.

    Google Scholar 

  • Anselin, L. (2001b). Spatial effects of econometric practice in environmental and resource economics. American Journal of Agricultural Economics, 83(3), 705–710.

    Article  Google Scholar 

  • Anselin, L. (2002). Under the hood: Issues in the specification and interpretation of spatial regression models. Agricultural Economics, 27, 247–267.

    Article  Google Scholar 

  • Anselin, L. (2003). Networks and spatial externalities in the specification of spatial regression models. Atlanta, GA: Keynote Speech—American Sociological Association Meetings.

    Google Scholar 

  • Arah, O., Westert, G., Delnoij, D., & Klazinga, N. (2005). Health system outcomes and determinants amenable to public health in industrialized countries: A pooled, cross-sectional time series analysis. BMC Public Health, 5(81). http://www.biomedcentral.com.

  • Bursik, R. J., Jr. (1988). Social disorganization and theories of crime and delinquency: Problems and prospects. Criminology, 26, 529–551.

  • Bursik, R. J., Jr., & Grasmick, H. G. (1993). Neighborhoods and crime: The dimensions of effective community control. New York: Lexington Books.

  • Buttner, T., & Spengler, H. (2003). Local determinants of crime: Distinguishing between resident and non-resident offenders. Paper provided by the Department of Economics at Darmstadt University of Technology in its Series Darmstadt Discussion Papers in Economics, p 120.

  • Center for Disease Control (CDC). (2004). Married adults are the healthiest. http://www.cdc.gov.

  • Crepaz, M., & Crepaz, N. (2004). Is equality good medicine? Determinants of life expectancy in industrialized democracies. Journal of Public Policy, 24(3), 275–298.

    Article  Google Scholar 

  • Cressie, N. (1993). Statistics for spatial data. New Jersey: Wiley, Interscience.

    Google Scholar 

  • deGraf, T., Florax, R., Raymond, J., Nijkamp, P., & Reggiani, A. (2001). A general misspecification test for spatial regression models: Dependence, heterogeneity, and nonlinearity. Journal of Regional Science, 41, 2.

    Google Scholar 

  • Farrington, D. P., Sampson R. J., & Wikstrom, P. H. (1993). Integrating individual and ecological aspects of crime. Stockholm, Sweden: National Council for Crime Prevention.

  • Goldman, N. (1993). Marriage selection and mortality patterns: Inferences and fallacies. Demography, 30(2), 189–208.

    Article  Google Scholar 

  • Gorman, B., & Read, J. (2006). Gender disparities in adult health: An examination of three measures of morbidity. Journal of Health and Social Behavior, 47, 95–110.

    Article  Google Scholar 

  • Hogan, D. (1978). The effects of demographic factors, family background, and early job achievement on age at first marriage. Demography, 15(2), 161–176.

    Article  Google Scholar 

  • Huebner, B. (2005). The effect of incarceration on marriage and work over the life course. Justice Quarterly, 22(3), 281–303.

    Article  Google Scholar 

  • Huston, T., & Melz, H. (2004). The case for (promoting) marriage: The devil is in the details. Journal of Marriage and Family, 66, 943–958.

    Article  Google Scholar 

  • Iceland, J. (2004). A multigroup entropy measure: Also know as Theil’s H or information theory index. US Census Bureau. Available at: http://www.census.gov/hhes/www/housing/housing_patterns/multigroup_entropy.pdf.

  • iMAPP: Institute for Marriage and Public Policy. (2005). Can married parents prevent crime? Recent research on family structure and delinquency 2000–2005. http://www.imapp.org (Washington D.C.).

  • Lewis, M., & Butterfield, R. (2007). Social control in marital relationships: Effect on one’s partner on health behaviors. Journal of Applied Social Psychology, 37(2), 298–319.

    Article  Google Scholar 

  • Lo, C., & Zhong, H. (2006). Linking crime rates to relationship factors: The use of gender-specific data. Journal of Criminal Justice, 34, 317–329.

    Article  Google Scholar 

  • Low, M., Low, B., Baumler, E., & Huynh, P. (2005). Can education policy be health policy? Implications of research on the social determinants of health. Journal of Health Politics, Policy and Law, 30(6), 1131–1162.

    Article  Google Scholar 

  • Lynch, J., Harper, S., Kaplan, G., & Smith, G. (2005). Associations between income inequality and mortality among US states: The importance of time period and source of income data. Research and Practice, 95(8), 1424–1430.

    Google Scholar 

  • Manzoli, L., Villari, P., Pirone, G., & Boccia, A. (2007). Marital status and mortality in the elderly: A systematic review and meta-analysis. Social Science and Medicine, 64, 77–94.

    Article  Google Scholar 

  • Maume, M., Ousey, G., & Beaver, K. (2005). Cutting the grass: A reexamination of the link between marital attachment, delinquent peers and desistance from marijuana use. Journal of Quantitative Criminology, 21(1), 27–53.

    Article  Google Scholar 

  • Messner, S. F., Anselin, L., Baller, R., Hawkins, D. F., Deane, G., & Tolnay, S. E. (1999). The spatial patterning of county homicide rates: An application of exploratory spatial data analysis. Journal of Quantitative Criminology, 15(4), 423–450.

    Article  Google Scholar 

  • Murray, C., Kulkarni, S., Michaud, C., Tomijima, N., Bulzacchelli, M., Iandiorio, T., & Ezzati, J. (2005). Eight Americas: Investigating mortality disparities across races, counties and race-counties in the United States. PLoS Medicine, 3(9:e261), 1513–1524.

    Google Scholar 

  • Park, R. K., Burgess, E. W., & McKenzie, R. D. (Eds). (1925). The city. Chicago: University of Chicago Press.

  • Paulsen, D. J., & Robinson, M. B. (2004). Spatial aspects of crime: Theory and practice. Boston: Pearson Education, Inc.

  • Pearlstein, M. (2005). Crime and marriage in Minnesota and the nation: If wedding rings help break vicious and violent cycles, what’s impeding them from doing so more often. American Experiment Quarterly, Fall, 1–36.

  • Porter, J. R. (2008). Mapping human development at the sub-national level: Spatial contours of development in the US. Journal of Maps, pp. 472–484.

  • Porter, J. R. (2010). Tracking the mobility of crime: New methodologies and geographies in modeling the diffusion of offending. United Kingdom: Cambridge Scholars Publishing.

    Google Scholar 

  • Porter, J. R. (2011a). Religion and politics: Understanding the effects of conservative origins on contemporary patterns of human development. Quality and Quantity. doi:10.1007/s11135-011-9450-0.

  • Porter, J. R. (2011b). Plantation economics, violence, and social well-being: The lingering effects of racialized group oppression on contemporary human development. Journal of Human Development and Capabilities (in press) (August Publication).

  • Porter, J. R. (2011c). Identifying spatio-temporal patterns of articulated criminal offending: An application using phenomenologically meaningful police jurisdictional geographies. Systems Research and Behavioral Science, 28(3), 197–211.

    Article  Google Scholar 

  • Porter, J. R., & Howell, F. M. (2009). On the ‘Urbanness’ of metro areas: Testing the homogeneity hypothesis, 1970–2000. Population Research and Policy Review, 28(5), 589–613.

    Article  Google Scholar 

  • Porter, J. R., & Purser, C. W. (2008). Measuring relative sub-national human development: An application of the United Nation’s Human Development Index in the US. Journal of Social and Economic Measurement, 33(4), 253–269.

    Google Scholar 

  • Porter, J. R., & Purser, C. W. (2010). Social disorganization, marriage, and reported crime: A spatial econometrics examination of family formation and criminal offending. Journal of Criminal Justice, 38(5), 942–950.

    Article  Google Scholar 

  • Potter, L. (1991). Socioeconomic determinants of white and black males’ life expectancy differentials, 1980. Demography, 28(2), 303–321.

    Article  Google Scholar 

  • Raphael, D. (2004). Making the links: What do health promotion, crime prevention, and social development have in common?. Presentation to The Atlantic Summer Institute on Healthy and Safe Communities. UPEI, August 2004.

  • Ross, C. E., & Mirowsky, J. (1995). Does employment affect health? Journal of Health and Social Behavior, 36, 230–243.

    Article  Google Scholar 

  • Ross, C. E., & Mirowsky, J. (2002). Family relationships, social support and subjective life expectancy. Journal of Health and Social Behavior, 43, 469–489.

    Article  Google Scholar 

  • Sampson, R. (1987). Urban black violence: The effect of male joblessness and family disruption. American Journal of Sociology, 93(2), 348–382.

    Article  Google Scholar 

  • Sampson, Robert. J. (2003). The neighborhood context of well-being. Perspectives in Biology and Medicine, 46(3), S53–S64.

    Article  Google Scholar 

  • Sampson, R. J., & Groves, W. B. (1989). Community structure and crime: Testing social-disorganization theory. American Journal of Sociology, 94(4), 774–802.

    Article  Google Scholar 

  • Sampson, R. J., & Laub, J. H. (1990). Crime and deviance over the life course: The salience of adult social bonds. American Sociological Review, 55(5), 609–627.

    Article  Google Scholar 

  • Sampson, R., Laub, J., & Wimer, C. (2006). Does marriage reduce crime? A counterfactual approach to within-individual causal effects. Criminology, 44(3), 465–508.

    Article  Google Scholar 

  • Schwartz, J. (2006). Effects of diverse forms of family structure on female and male homicide. Journal of Marriage and Family, 68, 1291–1312.

    Article  Google Scholar 

  • Semaan, S., Sternberg, M., Zaidi, A., & Aral, S. (2007). Social capital and rates of Gonorrhea in the United States: Spatial regression analyses of state level associations. Social Sciences and Medicine, 64(11), 2324–2341.

    Article  Google Scholar 

  • Shaw, C., & McKay, H. (1942). Juvenile delinquency and urban areas (5th ed.). Chicago, IL: University of Chicago Press.

  • Smith, W. R., Frazee, S. G., & Davison, E. L. (2000). Furthering the integration of routine activity and social disorganization theories: Small units of analysis and the study of street robbery and a diffusion process. Criminology, 38(2), 489–523.

    Google Scholar 

  • Veysey, B., & Messner, S. (1999). Further testing of social disorganization theory: An elaboration of Sampson and Grove’s ‘community structure and crime’. The Journal of Research in Crime and Delinquency, 36(2), 156–174.

    Google Scholar 

  • Voss, P., Long, D., Hammer, R., & Friedman, S. (2006). County child poverty rates in the US: A spatial regression approach. Population Research and Policy Review, 25(4), 369–391.

    Article  Google Scholar 

  • Waite, L. (1995). Does marriage matter? Demography, 32(4), 483–507.

    Article  Google Scholar 

  • Waite, L. J., & Lehrer, E. L. (2003). The benefits from marriage and religion in the United States: A comparative analysis. Population and Development Review, 29(2), 255–275.

    Article  Google Scholar 

  • Waller, L. A., & Gotway, C. A. (2004). Applied spatial statistics for public health data. Hoboken, NJ: Wiley.

    Book  Google Scholar 

  • Wilcox, W., Dougherty, W., Fisher, H., Galston, W., Glenn, N., Gottman, J., et al. (2005). Why marriage matters, second edition: Twenty-six conclusions from the social sciences. A report from family scholars. New York, NY: Institute for American Values.

    Google Scholar 

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Acknowledgments

The author would like to acknowledge the helpful commentary and discussion with Dr. Frank Howell, Dr. Emory Morrison, Dr. Wesley James, and the anonymous reviewers and editor for their remarks. However, all errors of fact or interpretation are to be attributed solely to the author. Furthermore, it should be acknowledged that a previous version of this paper was honored with an award by the American Sociologial Association with an "Outstanding Student Paper of the Year" Award.

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  1. Graduate Center, Brooklyn College & Institute for Demographic Research, City University of New York (CUNY), 218 Whitehead Hall, 2900 Bedford Ave., New York, NY, 11210, USA

    Jeremy R. Porter

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Correspondence to Jeremy R. Porter.

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Porter, J.R. A Simplified Indicator of Social Well-Being in the United States: Examining the Ecological Impact of Family Formation within a County Level Framework. Soc Indic Res 108, 421–440 (2012). https://doi.org/10.1007/s11205-011-9884-8

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