Adolescent outcomes and opportunities in a Canadian province: looking at siblings and neighbors

BMC Public Health

Julia Witt¹  Randy Walld²  Leslie L Roos² 

[1] Department of Economics, Faculty of Arts, University of Manitoba, 554 Fletcher Argue Building, Winnipeg, Manitoba R3T 2 N2, Canada;Manitoba Centre for Health Policy, Department of Community Health Sciences, Faculty of Medicine, University of Manitoba, 408-727 McDermot Avenue, Winnipeg, Manitoba R3E 3P5, Canada

关键词: Health costs;    Teenage pregnancy;    Educational achievement;    Inequality persistence;    Life outcomes;    Sibling correlation;    Child health;   

Others  :  1130291
DOI  :  10.1186/1471-2458-14-506

 received in 2013-10-02, accepted in 2014-05-12,  发布年份 2014

【 摘 要 】

Background

Well-organized administrative data with large numbers of cases (building on linked files from several government departments) and a population registry facilitate new studies of population health and child development. Analyses of family relationships and a number of outcomes--educational achievement, health, teen pregnancy, and receipt of income assistance--are relatively easy to conduct using several birth cohorts. Looking both at means/proportions and at sibling correlations enriches our study of opportunity and well-being in late adolescence. With observational research possibly exaggerating the causal effects of risk factors, sibling comparisons involving individuals sharing both many family characteristics and many genes help deal with such criticisms.

Methods

This paper uses a rich dataset from one Canadian province (Manitoba) covering a wide range of geographical areas (cities to rural regions). Influences on opportunity and well-being are analyzed looking at both means/proportions and sibling correlations. We measure a variety of outcomes that may reflect different causal influences. A creative application of linear programming advances the use of data on residential location.

Results

Predicting educational achievement using available variables was much easier than predicting adolescent health status (R-square of .200 versus R-square of .043). Low levels of educational achievement, high levels of teenage pregnancy, and high sibling correlations outside Winnipeg and within Winnipeg’s lower income areas highlight inequalities across socioeconomic and geographic backgrounds. Stratifying our analyses by different variables, such as income quintiles, reveals differences in means and correlations within outcomes and across groups. Particular events--changes in mother’s marital status and in place of residence--were associated with less favorable outcomes in late adolescence.

Conclusion

Our findings suggest a paradox: Canadian developmental outcomes through late adolescence appear quite similar to those in the United States, even though intergenerational mobility in Canada is closer to mobility in the Nordic countries than to that in the United States.

【 授权许可】

   
2014 Roos et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

【 参考文献 】

• [1]Mazumder B: Family and community influences on health and socioeconomic status: sibling correlations over the life course. B E J Econ Anal Policy 2011, 11(3):2876.
• [2]Mazumder B: Sibling similarities and economic inequality in the US. J Popul Econ 2008, 21(3):685-701.
• [3]Björklund A, Lindahl L, Lindquist MJ: What more than parental income, education and occupation? An exploration of what Swedish siblings get from their parents. B E J Econ Anal Policy 2010., 10(1) Article 102
• [4]Solon G, Corcoran M, Gordon R, Laren D: A longitudinal analysis of sibling correlations in economic status. J Hum Resources 1991, 26(3):509-534.
• [5]Currie J: Socioeconomic status, poor health in childhood and human capital development. J Econ Lit 2009, 47(1):87-122.
• [6]Jusot F, Tubeuf S, Trannoy A: Circumstances and efforts: How important is their correlation for the measurement of inequality of opportunity in health. Health Econ 2013, 22(12):1470-1495.
• [7]Rosa Dias P, Jones A, Editorial: Giving equality of opportunity a fair innings. Health Econ 2007, 16(2):109-112.
• [8]Sacerdote B: Nature and nurture effect on children’s outcomes: what have we learned from studies of twins and adoptees? In Handbook of Social Economics. Volume 1A, Ch. 5. Edited by Benhabib EJ, Bisin A, Jackson M. Amsterdam, NE: Elsevier Science & Technology; 2010.
• [9]Solon G, Page ME, Duncan GJ: Correlations between neighboring children in their subsequent educational attainment. Rev Econ Stat 2000, 82(3):383-392.
• [10]Page ME, Solon G: Correlations between brothers and neighboring boys in their adult earnings: the importance of being urban. J Labour Econ 2003, 21(4):831-855.
• [11]Boyle MH, Willms JD: Place effects for areas defined by administrative boundaries. Am J Public Health 1999, 149(6):577-585.
• [12]Brooks-Gunn J, Duncan GJ, Klebanov PK, Sealand N: Do neighborhoods influence child and adolescent development? Am J Sociol 1993, 99(2):353-395.
• [13]Ginther D, Haveman R, Wolfe B: Neighborhood attributes as determinants of children’s outcomes: how robust are the relationships? J Hum Resources 2000, 35(4):603-642.
• [14]Haveman R, Sandefur G, Wolfe B, Voyer A: Trends in children’s attainments and their determinants as family income inequality has increased. In Social Inequality. Edited by Neckerman KM. New York, NY: Russell Sage Foundation; 2004:149-188.
• [15]Kunz J, Page M, Solon G: Are point-in-time measures of neighborhood characteristics useful proxies for children’s long-run neighborhood environment? Econ Lett 2003, 79(2):231-237.
• [16]Sampson RJ, Morenoff JD, Gannon-Rowley T: Assessing ‘neighborhood effects’: social processes and new directions in research. Ann Rev Sociol 2002, 28:443-478.
• [17]Wodtke GT, Harding DJ, Elwert F: Neighborhood effects in temporal perspective: the impact of long-term exposure to concentrated disadvantage on high school graduation. Am Sociol Rev 2011, 76(5):713-736.
• [18]Duncan GJ: The PSID and me. In Looking at lives: American longitudinal studies of the 20th century. Edited by Phelps E, Furstenberg FF, Colby A. New York, NY: Russell Sage Foundation; 2002:133-166.
• [19]Duncan GJ, Raudenbush S: Neighborhoods and adolescent development: how can we determine the links? In Does It Take a Village? Community Effect on Children, Adolescents, and Families. Edited by Booth A, Crouter AC. State College, PA: Pennsylvania State University Press; 2001:105-136.
• [20]Wheaton B, Clarke P: Space meets time: integrating temporal and contextual influences on mental health in early adulthood. Am Sociol Rev 2003, 68(5):680-706.
• [21]Haveman R, Wolfe B: Succeeding generations: on the effects of investments in children. Russell Sage Foundation: New York, NY; 1994.
• [22]Sanbonmatsu L, Kling JR, Duncan GJ, Brooks-Gunn J: Neighborhoods and academic achievement: results from the moving to opportunity experiment. J Hum Resources 2006, 41(4):649-691.
• [23]Behrman J, Taubman P: Intergenerational earnings mobility in the United States: some estimates and a test of Becker’s intergenerational endowments model. Rev Econ Stat 1985, 67(1):144-151.
• [24]Corcoran M, Gordon R, Laren D, Solon G: Effects of family and community background on economic status. Am Econ Rev 1990, 80(2):362-366.
• [25]Oreopoulos P, Stabile M, Walld R, Roos LL: Short, medium, and long term consequences of poor infant health: an analysis using siblings and twins. J Hum Resources 2008, 43(1):88-138.
• [26]Jutte DP, Brownell M, Roos NP, Schippers C, Boyce WT, Syme SL: Rethinking what’s important: biologic versus social predictors of childhood health and educational outcomes. Epidemiol 2010, 21(3):314-323.
• [27]Adler NE, Boyce WT, Chesney MA, Cohen S, Folkman S, Kahn RL, Syme SL: Socioeconomic status and health. The challenge of the gradient. Am Psychol 1994, 49(1):15-24.
• [28]Chen E, Matthews KA, Boyce WT: Socioeconomic differences in children’s health: how and why do these relationships change with age? Psychol Bull 2002, 128(2):295-329.
• [29]Shanahan M, Gousseau C: Using the POPULIS framework for interprovincial comparisons of expenditures on health care. Med Care 1999, 37(6):JS83-JS100.
• [30]Statistics Canada: Winnipeg, Manitoba (Code 4611040) and Manitoba (Code 46) (table). Census Profile. 2011 Census. Ottawa: Statistics Canada Catalogue no. 98-316-XWE; Released October 24, 2012. [http://www12.statcan.gc.ca/census-recensement/2011/dp-pd/prof/index.cfm?Lang=E webcite] (accessed July 30, 2013)
• [31]Brownell MD, Kozyrskyj A, Roos NP, Friesen D, Mayer T, Sullivan K: Health service utilization by Manitoba children. Can J Public Health 2002, 93(S2):S57-S64.
• [32]Manitoba Education and Youth: Funding of schools 2003/2004 school year: Winnipeg, 2003. Available from: [http://www.edu.gov.mb.ca/k12/finance/schfund/funding14-15.pdf webcite]
• [33]Willms JD: Variation in literacy skills among Canadian provinces: findings from the OECD PISA. Ottawa, ON: Statistics Canada; 2004:4-51.
• [34]Wolfson M, Murphy B: Income inequality in North America: does the 49th parallel still matter? In Canadian Economic Observer. Ottawa, ON: Statistics Canada; 2000:3.1-3.24.
• [35]UNICEF: Child poverty in perspective: an overview of child well-being in rich countries. In Innocenti Report Card 7. Florence, Italy: UNICEF Innocenti Research Centre; 2007.
• [36]Conference Board of Canada: Canadian income inequality: is Canada becoming more unequal? 2011. [http://www.conferenceboard.ca/hcp/hot-topics/caninequality.aspx webcite]
• [37]Ross NA, Wolfson MC, Dunn JR, Berthelot J-M, Kaplan GA, Lynch JW: Relation between income inequality and mortality in Canada and in the United States: cross sectional assessment using census data and vital statistics. BMJ 2000, 320(7239):898-902.
• [38]Roos LL, Brownell M, Lix L, Roos NP, Walld R, MacWilliam L: From health research to social research: privacy, methods, approaches. Soc Sci Med 2008, 66(1):117-129.
• [39]Roos LL, Soodeen R, Bond R, Burchill C: Working more productively: tools for administrative data. Health Serv Res 2003, 38(5):1339-1357.
• [40]Roos LL, Menec V, Currie RJ: Policy analysis in an information-rich environment. Soc Sci Med 2004, 58(11):2231-2241.
• [41]Currie J, Stabile M, Manivong P, Roos LL: Child health and young adult outcomes. J Hum Resources 2010, 45(3):517-548.
• [42]Brownell M, Roos NP, Fransoo R, Roos LL, Guevremont A, MacWilliam L, Yallop L, Levin B: Is the class half-empty? Socioeconomic status and education achievement from a population-based perspective. IRPP Choices 2006, 12(5):1-30.
• [43]Roos LL, Nicol JP: A research registry: uses, development and accuracy. J Clin Epidemiol 1999, 52(1):39-47.
• [44]Björklund A, Jäntti M, Solon G: Influences of nature and nurture on earnings variation: a report on a study of various sibling types in Sweden. In Unequal Changes: Family Background and Economic Success. Edited by Bowles S, Gintis H, Osborne Groves M. Princeton, NJ: Princeton University Press; 2005:145-164.
• [45]Wall-Wieler E, Roos L, Chateau D: Adolescent Health and Educational Achievement: Siblings and Populations. Unpublished 2014.
• [46]Steiner PM, Cook TD, Shadish WR, Clark MH: The importance of covariate selection in controlling for selection bias in observational studies. Psychol Methods 2010, 15(3):250-267.
• [47]Mosteller F, Tukey JW: Data analysis and regression. A second course in statistics. Reading MA: Addison-Wesley; 1977.
• [48]Willms JD: Social class segregation and its relationship to pupils’ examination results in Scotland. Am Sociol Rev 1986, 51(2):224-241.
• [49]Brownell M, Chartier M, Santos R, Ekuma O, Au W, Sarkar J, Burland E, Koseva I, Guenette W: How are Manitoba’s children doing?. Winnipeg, MB: Manitoba Centre for Health Policy; 2012:1-342.
• [50]Kozyrskyj AL, Dahl ME, Soodeen RA: High cost users of pharmaceuticals: who are they? Can J Clin Pharmacol 2005, 12:e77.
• [51]Reid RJ, MacWilliam L, Verhulst L, Roos NP, Atkinson M: Performance of the ACG case-mix system in two Canadian provinces. Med Care 2001, 39(1):86-99.
• [52]Reid RJ, Roos NP, MacWilliam L, Frohlich N, Black C: Assessing population health care need using a claims-based ACG morbidity measure: a validation analysis in the province of Manitoba. Health Serv Res 2002, 37(5):1345-1364.
• [53]Sibley LM, Moineddin R, Agha MM, Glazier RH: Risk adjustment using administrative data-based and survey-derived methods for explaining physician utilization. Med Care 2010, 48:175-182.
• [54]Baldwin LM, Klabunde CN, Green P, Barlow W, Wright G: In search of the perfect comorbidity measure for use with administrative claims data: does it exist? Med Care 2006, 44(8):745-753.
• [55]Roos LL, Walld R: Neighborhood, family and health care. Can J Public Health 2007, 98(Suppl 1):554-561.
• [56]Forget EL: The town with no poverty: health effects of a Canadian guaranteed annual income field experiment. Can Public Pol 2011, 37(3):283-305.
• [57]Forget E, Deber RB, Roos LL: Medical Savings Accounts: will they reduce costs? CMJ 2002, 167(2):143-147.
• [58]Finlayson G, Jacobs P, Watson D, Bogdanovic B: A comparison of preliminary and adjusted cost per weighted case determinations for Manitoba Hospitals: impact for evaluation and report cards. Winnipeg, MB: Manitoba Centre for Health Policy; 2001.
• [59]Jutte DP, Roos NP, Brownell M, Briggs G, MacWilliam L, Roos LL: The ripples of adolescent motherhood: social, educational, and medical outcomes for children of teen and prior teen moms. Acad Pediatr 2010, 10(5):293-301.
• [60]Luong M: Life after teenage motherhood. In Perspectives. Statistics Canada, Catalogue No. 75-001-X; 2008.
• [61]SAS Institute Inc: SAS/STAT® 9.2 User’s Guide. 2nd edition. Cary, NC: SAS Institute Inc; 2009.
• [62]Duncan GJ, Boisjoly J, Harris KM: Sibling, peer, neighbor, and schoolmate correlations as indicators of the importance of context for adolescent development. Demography 2001, 38(3):437-447.
• [63]Ginther D, Pollak RA: Family structure and children’s educational outcomes: blended families, stylized facts, and descriptive regressions. Demography 2004, 41(4):671-696.
• [64]Hanley JA, McNeil BJ: The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982, 143(1):29-36.
• [65]Hedeker D, Gibbons RD: Longitudinal data analysis. John Wiley & Sons Inc: Hoboken, NJ; 2006.
• [66]Corak M: Do poor children become poor adults? Lessons from a cross country comparison of generational earnings mobility. In Discussion Paper No. 1993. Bonn, Germany: Bonn Institute for the Study of Labor; 2006.
• [67]Loehlin JC, Paige Harden K, Turkheimer E: The effect of assumptions about parental assortative mating and genotype-income correlation on estimates of genotype-environment interaction in the national merit twin study. Behav Genet 2009, 39(2):165-169.
• [68]Turkheimer E, Haley A, Waldron M, D’Onofrio B, Gottesman II: Socioeconomic status modifies heritability of IQ in young children. Psychol Sci 2003, 14(6):623-628.
• [69]Roos LL, Magoon J, Gupta S, Chateau D, Veugelers PJ: Socioeconomic determinants of mortality in two Canadian provinces: Multilevel modelling and neighborhood context. Soc Sci Med 2004, 59(7):1435-1447.
• [70]Ashenfelter O, Zimmerman D: Estimates of the returns to schooling from sibling data: fathers, sons and brothers. Rev Econ Stat 1997, 79(1):1-9.
• [71]Björklund A, Eriksson T, Jäntti M, Oddbjörn R, Österbacka E: Brother correlations in earnings in Denmark, Finland, Norway and Sweden compared to the United States. J Popul Econ 2002, 15:757-772.
• [72]Blanden J, Gregg P, Machin S: Educational inequality and intergenerational mobility. In What’s the good of education? The economics of education in the UK. Edited by Stephen M, Anna V. Princeton, NJ: Princeton University Press; 2005.
• [73]Oreopoulos P: The long-run consequences of living in a poor neighborhood. Q J Econ 2003, 118(4):1533-1575.
• [74]Hertzman C: Human development, life course, intervention, and health. In Epidemiological Methods in Life Course Research. Edited by Pickles A, Maughan B, Wadsworth M. New York, NY: Oxford University Press; 2007.
• [75]Frost JJ, Forrest JD: Understanding the impact of effective teenage pregnancy prevention programs. Fam Plann Perspect 1995, 27:188-195.
• [76]Roos NP, Roos LL, Brownell M, Fuller EL: Enhancing policy makers’ understanding of disparities: Relevant data from an information-rich environment. Milbank Q 2010, 88(3):382-403.
• [77]Rodríguez G, Elo I: Intra-class correlation in random-effects models for binary data. Stata J 2003, 3(1):32-46.