Health disparities and gaps in school readiness

Future of Children

Volumn 15, Issue 1, 2005, Pages 117-138

  Currie, Janet ^a,b,c  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b NATIONAL BUREAU OF ECONOMIC RESEARCH   (United States)

^c IZA   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ACADEMIC ACHIEVEMENT; ASTHMA; ATTENTION DEFICIT DISORDER; BREAST FEEDING; CHILD BEHAVIOR; CHILD HEALTH; COGNITION; DEPRESSION; EDUCATION; HEALTH CARE POLICY; HEALTH INSURANCE; HEALTH STATUS; HUMAN; LEAD POISONING; NUTRITION; RACE DIFFERENCE; REVIEW; SCHOOL; SOCIOECONOMICS;

AFRICAN AMERICANS; CHILD, PRESCHOOL; EARLY INTERVENTION (EDUCATION); EUROPEAN CONTINENTAL ANCESTRY GROUP; FEMALE; HEALTH STATUS; HUMANS; MALE; MATERNAL WELFARE; NUTRITIONAL STATUS; SCHOOL ADMISSION CRITERIA; SCHOOLS; SOCIOECONOMIC FACTORS; STUDENTS; UNITED STATES;

EID: 28044445100     PISSN: 10548289     EISSN: 15501558     Source Type: Journal    
DOI: 10.1353/foc.2005.0002     Document Type: Review

References (87)

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14. For whites, the mean score would be [(.96*50) + (.04*45)] = 49.8, and for blacks the mean score would be [(.94*50) + (.06*45)] = 49.7.
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31. The asthma studies suggest that 15.7 percent of black children have asthma and that 32.7 percent of black asthmatics are limited by their condition. Among whites, the comparable figures are 12.2 percent and 22.4 percent. Together, these figures imply that approximately 5 percent of black children and 3 percent of white children are limited by asthma. Hence, the average behavior problems score among whites would be [(.97*50) + (.03*58)] = 50.2 compared with an average score among 100 black children of [(.95*50) + (.05*58)] = 50.4 (where for behavior problems a higher score is worse).
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40. The prevalence of high lead exposure is 8.7 percent among blacks and 2 percent among whites. If high lead exposure were responsible for a five point decline in IQ scores, and this decline translated into roughly a third of a standard deviation fall in our generic test score, then we could make the following calculation: the mean score for blacks would be [(.91*50) + (.9*48)] = 49.8, while the mean score for whites would be [(.98*50) + (.2*48)] ∼ 50.0.
41. Janet Currie, "U.S. Food and Nutrition Programs," Means-Tested Transfer Programs in the United States, edited by Robert Moffitt (University of Chicago Press for NBER, 2003);
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51. Anjali Jain, John Concato, and John M. Leventhal, "How Good Is the Evidence Linking Breastfeeding and Intelligence?" Pediatrics 109, no. 6 (June 2002): 1044-53.
52. The average score for white infants would be (.29*50) + (.71*45) = 46.45 and the average score for black infants would be (.09*50) + (.91*45) = 45.45.
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67. Deborah Sharp and others, "The Impact of Postnatal Depression on Boys' Intellectual Development, "Journal of Child Psychology and Psychiatry 36 (1995): 1315-37;
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69. Sophie Kurstjens and Dieter Wolke, "Effects of Maternal Depression on Cognitive Development of Children over the First 7 Years of Life," Journal of Child Psychology and Psychiatry 42, no. 5 (2001): 623-36;
70. Petterson and Albers, "Effects of Poverty and Maternal Depression on Early Child Development" (see note 33).
71. The average score for white children would be (.03*45) + (.97*50) = 49.9 and the average score for black children would be (.11*45) + (.89*50) = 49.45.
72. Eugene Lewit, Courtney Bennett, and Richard Behrman, "Health Insurance for Children: Analysis and Recommendations," The Future of Children 13, no 1 (Spring 2003): 1-4.
73. Karen Kuhlthau and others, "Correlates of Use of Specialty Care," Pediatrics 113, no. 3, part 1 (March 2004): e249-55.
74. Janet Currie and Jeffrey Grogger, "Medicaid Expansions and Welfare Contractions: Offsetting Effects on Prenatal Care and Infant Health," Journal of Health Economics 21 (March 2002): 313-35;
75. Anna Aizer, "Low Take-up in Medicaid: Does Outreach Matter and for Whom?" American Economic Review, Papers and Proceedings (May 2003): pp. 238-41;
76. Janet Currie, "The Take-up of Social Benefits," Working Paper 10488 (Cambridge, Mass.: National Bureau of Economic Research, May 2004).
77. Anna Dixon and others, "Is the NHS Equitable? A Review of the Evidence," Health and Social Care Discussion Paper 11 (London School of Economics, 2003);
78. Lori J. Curtis and others, "The Role of Permanent Income and Family Structure in the Determination of Child Health in Canada," Health Economics 10 (4) (June 2001): 287-302.
79. Amy M. Heneghan and others, "Do Pediatricians Recognize Mothers with Depressive Symptoms," Pediatrics 106, no. 6 (December 2000): 1367-73.
80. Janet Currie, "Early Childhood Intervention Programs: What Do We Know?" Journal of Economic Perspectives 15, no. 2 (Spring 2001): 213-38.
81. Linda Fosburg and others, "The Effects of Head Start Health Services: Report of the Head Start Health Evaluation," AAI 84-13 (Cambridge, Mass.: Abt Associates Inc., March 15, 1984).
82. Janet Currie and Matthew Neidell, "Getting Inside the 'Black Box' of Head Start Quality: What Matters and What Doesn't," Working Paper 10091 (Cambridge, Mass.: National Bureau of Economic Research, November 2003).
83. David L. Olds and others, "Prenatal and Infancy Home Visitation by Nurses: Recent Findings," The Future of Children 9, no. 1 (Spring/Summer 1999): 44-65.
84. Ray Yip and others, "Declining Prevalence of Anemia among Low-Income Children in the United States," Pediatrics 258, no. 12 (1987): 1619-23;
85. Lori Kowaleski-Jones and Greg Duncan, "Effects of Participation in the WIC Food Assistance Program on Children's Health and Development: Evidence from NLSY Children," Discussion Paper 1207-00 (Madison, Wis.: Institute for Research on Poverty, 2000).
86. For an extensive review of the WIC literature, see Janet Currie, "U.S. Food and Nutrition Programs," in Means Tested Transfer Programs in the United States, edited by Robert Moffitt (University of Chicago Press for NBER, 2003).
87. Marianne Bitler, Janet Currie, and John Karl Scholz, "WIC Eligibility and Participation," Journal of Human Resources 38 (2003): 1139-79.