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Lead exposure and academic achievement: evidence from childhood lead poisoning prevention efforts

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Abstract

Though the adverse consequences of lead exposure in children have been well known for over a century, the recent Flint water crisis has drawn renewed attention to the impacts of lead exposure on human health and development. This study considers connections to educational outcomes, asking whether population-level lead exposure in early childhood influences later academic achievement and racial achievement gaps. It assesses the effectiveness of recent local- and state-level lead hazard control programs in mitigating exposure and uses this source of exogenous variation in early childhood exposure across birth cohorts to draw inferences about the long-term effects of lead on mean student test scores. Our findings indicate that lead hazard control grants reduced lead poisoning incidents by over 70% of the baseline prevalence. And each one percentage point reduction in lead poisoning in early childhood translated to a growth of 0.04 standard deviations in student math test scores and 0.08 standard deviations in student reading scores. This same reduction in lead poisoning narrowed both the white-Hispanic math achievement gap and white-Hispanic reading achievement gap by 0.06 standard deviations, implying important downstream consequences for economic inequality.

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Notes

  1. For more information, see Fig. 6, which plots the total amount of HUD spending on lead hazard control and lead hazard reduction demonstration grants by fiscal year, and Table 7 in the Appendix, which lists aggregate HUD lead hazard control funding received by each state (and counties within the state) over the analytical time period.

  2. For more information on lead screening and reporting requirements across states, see Dickman (2017).

  3. A one standard deviation improvement in our analysis represents one standard deviation in the distribution of student scores rather than one standard deviation in the distribution of county scores, which would be an average effect of smaller magnitude.

  4. For the education data, we assign every grade-by-year cohort of students to a birth year based on the median age of that grade level.

  5. We also estimate effects of treatment by “age-at-grant-receipt” of the cohort to see if our findings are sensitive to the cutoff point between pre- and postprogram. See Section 4.

  6. Because this equation also serves as a first-stage equation for lead exposure effects on academic achievement, we additionally include year and grade fixed effects in the model with pooled grade levels.

  7. Some of these variables reflect relevant population or demographic shifts; the educational control variables are included because we need consistent covariates between the first-stage equation and second-stage equation, which predicts test score outcomes.

  8. This precision-weighting process is motivated by the fact that county achievement mean statistics have large variation in their margins of error, and is a standard procedure in other research using this data (Shores and Steinberg 2017; Reardon et al. 2017).

  9. To examine this question, we used county-level data on geographic mobility from the 2006 to 2010 5-year American Community Survey. Using the 5-year data allows us to examine mobility by subgroup for even less populous counties, but limits our ability to examine residential sorting through panel data methods as used in the rest of the study. Instead, we compared inflow and outflow migration cross-sectionally for counties that had received lead hazard control grants between the years 2004 to 2006 to those that had not. We find no significant differential net changes in population composition (inflow-outflow) by percent black, percent Hispanic, and percent with children from 1 to 4 years of age in treatment counties as compared to control counties in the years following lead poisoning prevention activities.

  10. We chose 2003 for our main event study analysis because it is the year with the largest number of grant recipients and because it is right in the center of our birth year cohort coverage span. Approximately a third of all lead hazard control grants were received in 2003. Similar pretreatment trends graphs for recipients in a later year are provided in Fig. 8.

  11. In fact, positive tests for 2 to 10 lead in children’s blood are over 100 times more common than positive tests for greater than 10 (Gould 2009).

  12. According to Bloom et al. (2008), the average gain in nationally referenced test scores between sixth and seventh grades is 0.30 standard deviations in math and 0.28 standard deviations in reading.

  13. Figure 8 presents the same information for counties receiving grants in 2008 and counties never receiving grants to allow for more years of pretreatment binned averages.

References

  • Aizer A, Currie J, Simon P, Vivier P (2016) Do low levels of blood lead reduce children’s future test scores? NBER Working Paper No. 22558

  • American Academy of Pediatrics (AAP) (1998) Screening for elevated blood lead levels. Pediatrics 101(6):1072–1078

    Article  Google Scholar 

  • Anderson TW (1951) Estimating linear restrictions on regression coefficients for multivariate normal distributions. Ann Math Stat 20(3):46–63

    Google Scholar 

  • Apollonio DE, Wolfe N, Bero LA (2016) Realist review of policy intervention studies aimed at reducing exposures to environmental hazards in the United States. BMC Public Health 16(1):822. https://doi.org/10.1186/s12889-016-3461-7

    Article  Google Scholar 

  • Bellinger DC (2012) A strategy for comparing the contributions of environmental chemicals and other risk factors to neurodevelopment of children. Environ Health Perspect 120(4):501–507

    Article  Google Scholar 

  • Bloom HS, Hill CJ, Black AR, Lipsey MW (2008) Performance trajectories and performance gaps as achievement effect-size benchmarks for educational interventions. J Res Educ Eff 1(4):289–328

    Article  Google Scholar 

  • Brown MJ, Gardner J, Sargent JD, Swartz K, Hu H, Timperi R (2001) The effectiveness of housing policies in reducing children’s lead exposure. Am J Public Health 91(4):621–624

    Article  Google Scholar 

  • Burdick-Will J, Ludwig J, Raudenbush SW, Sampson R, Sanbonmatsu L, Sharkey P (2011) Converging evidence for neighborhood effects on children't test scores: An experimental, quasi-experimental, and observational comparison. In Duncan GJ, Murnane RJ (eds) Whither opportunity? Rising inequality, schools, and children's life chances, Russell Sage Foundation, pp 255–276.

  • Canfield RL, Henderson CR Jr, Cory-Slechta DA, Cox C, Jusko TA, Lanphear BP (2003) Intellectual impairment in children with blood lead concentrations below 10 μg per deciliter. N Engl J Med 348(16):1517–1526

    Article  Google Scholar 

  • Centers for Disease Control and Prevention (CDC). (2016) Blood lead levels in children. Accessed 8 March 2017. https://www.cdc.gov/nceh/lead/acclpp/lead_levels_in_children_fact_sheet.pdf

  • Centers for Disease Control and Prevention (CDC). (2017) National Environmental Public Health Tracking Network. Accessed February 9, 2017. Available at: https://ephtracking.cdc.gov/showHome.action

  • Clark S, Galke W, Succop P, Grote JA, McLaine P, Wilson J, Dixon S, Menrath W, Roda S, Chen M (2011) Effects of HUD-supported lead hazard control interventions in housing on children’s blood lead. Environ Res 111:301–311

    Article  Google Scholar 

  • Cragg JG, Donald SG (1993) Testing Identifiability and specification in instrumental variable models. Economic Theory 9(2):222–240

    Article  Google Scholar 

  • Dickman J (2017) Children at risk: gaps in state lead screening policies. Safer Chemicals, Healthy Families, Washington

    Google Scholar 

  • Dixon SL, Jacobs DE, Wilson JW, Akoto JY, Nevin R, Scott Clark C (2012) Window replacement and residential lead paint hazard control 12 years later. Environ Res 113:14–20

    Article  Google Scholar 

  • Environmental Protection Agency (EPA) (1995) Report on The National Survey of Lead-Based Paint in Housing. Accessed 8 March 2017. https://www.epa.gov/sites/production/files/documents/r95-003.pdf

  • Environmental Protection Agency (EPA) (2017) Protect your family from exposures to lead. Accessed 8 March 2017. https://www.epa.gov/lead/protect-your-family-exposures-lead

  • Frieden TS (2010) A framework for public health action: the health impact pyramid. Am J Public Health 100(4):590–595

    Article  Google Scholar 

  • Fryer RG, Levitt SD (2004) Falling behind: new evidence on the Black-White achievement gap. J Educ Next 4(4):64–71

  • Galke W, Clark S, Wilson J, Jacobs D, Succop P, Dixon S, Bornschein B, McLaine P, Chen M (2001) Evaluation of the HUD lead hazard control grant program: early overall findings. Environ Res 86:149–156

    Article  Google Scholar 

  • Gennart J-P, Bernard A, Lauwerys R (1992) Assessment of thyroid, testes, kidney and autonomic nervous system function in lead-exposed workers. Int Arch Occup Environ Health 64(1):49–57

    Article  Google Scholar 

  • Gould E (2009) Childhood lead poisoning: conservative estimates of the social and economic benefits of lead hazard control. Environ Health Perspect 117(7):1162–1167

    Article  Google Scholar 

  • Grandjean P, Landrigan PJ (2014) Neurobehavioural effects of developmental toxicity. Lancet Neurol 13(3):330–338

    Article  Google Scholar 

  • Ho AD, Reardon SF (2012) Estimating achievement gaps from test scores reported in ordinal "proficiency" categories. J Educ Behav Stat 37(4):489–517.

  • Jacobs DE, Clickner RP, Zhou JY, Viet SM, Marker DA, Rogers JW, Zeldin DC, Broene P, Friedman W (2002) The prevalence of lead-based paint hazards in U.S. housing. Environ Health Perspect 110(10):599–606

    Article  Google Scholar 

  • Jones RL, Homa DM, Meyer PA, Brody DJ, Caldwell KL, Pirkle JL, Brown MJ (2009) Trends in blood lead levels and blood lead testing among US children aged 1 to 5 years, 1988–2004. Pediatrics 123(3):e376–e385

    Article  Google Scholar 

  • Kalia K, Flora S (2005) Strategies for safe and effective therapeutic measures for chronic arsenic and lead poisoning. J Occup Health 47(1):1–21

    Article  Google Scholar 

  • Kennedy C, Lordo R, Sucosky MS, Boehm R, Brown MJ (2016) Evaluating the effectiveness of state specific lead-based paint hazard risk reduction laws in preventing recurring incidences of lead poisoning in children. Int J Hyg Environ Health 219(1):110–117. https://doi.org/10.1016/j.ijheh.2015.09.009

    Article  Google Scholar 

  • Koller K, Brown T, Spurgeon A, Levy L (2004) Recent developments in low-level lead exposure and intellectual impairment in children. Environ Health Perspect 112(9):987–994

    Article  Google Scholar 

  • Kruse J (2015) Healthy housing and lead hazard control. National Low Income Housing Coalition. Accessed 8 March 2017. http://nlihc.org/sites/default/files/Sec5.03_Healthy-Homes_2015.pdf

  • Lanphear BP, Hornung R, Khoury J, Yolton K, Baghurst P, Bellinger DC, Canfield RL, Dietrich KN, Bornschein R, Greene T, Rothenberg SJ, Needleman HL, Schnaas L, Wasserman G, Graziano J, Roberts R (2005) Low-level environmental lead exposure and children’s intellectual function: an international pooled analysis. Environ Health Perspect 113(7):894–899

    Article  Google Scholar 

  • Leighton J, Klitzman S, Sedlar S, Matte T, Cohen NL (2003) The effect of lead-based paint hazard remediation on blood lead levels of lead poisoned children in New York City. Environ Res 92:182–190

    Article  Google Scholar 

  • McMichael AJ, Vimpani GV, Robertson EF, Baghurst PA, Clark PD (1986) The Port Pirie cohort study: maternal blood lead and pregnancy outcome. J Epidemiol Community Health 40(1):18–25

    Article  Google Scholar 

  • Michigan Civil Rights Commission (2017) The Flint water crisis: systematic racism through the lens of Flint. Report of the Michigan Civil Rights Commission. Accessed 8 March 2017. http://www.michigan.gov/documents/mdcr/MDCR_Flint_Water_Crisis_Report_552190_7.pdf

  • Moody H, Darden JT, Pigozzi BW (2016) The racial gap in childhood blood lead levels related to socioeconomic position of residence in metropolitan Detroit. Sociol Race Ethn 2(2):200–218

    Article  Google Scholar 

  • Navas-Acien A, Guallar E, Silbergeld EK, Rothenberg SJ (2007) Lead exposure and cardiovascular disease: a systematic review. Environ Health Perspect 115(3):472–482

    Article  Google Scholar 

  • Needleman HL, Schell A, Bellinger D, Leviton A, Allred EN (1990) The long-term effects of exposure to low doses of lead in childhood. N Engl J Med 322:83–88

    Article  Google Scholar 

  • Nevin R (2000) How lead exposure relates to temporal changes in IQ, violent crime, and unwed pregnancy. Environ Res 83(1):1–22

    Article  Google Scholar 

  • Rau T, Reyes L, Urzua S (2013) The long-term effects of early lead exposure: evidence from a case of environmental negligence. NBER Working Paper No. 18915

  • Reardon SF, Robinson JP, Weathers ES (2014) Patterns and trends in racial/ethnic and socioeconomic academic achievement gaps. In Ladd HF, Goertz ME (eds) Handbook of research in education finance and policy, (2nd edn), Routledge, pp 491–509

  • Reardon SF, Kalogrides D, Ho A, Shear B, Shores K, Fahle E (2016) Stanford education data archive. http://purl.stanford.edu/db586ns4974. For more information, please visit http://seda.stanford.edu

  • Reardon SF, Kalogrides D, Ho A (2017) Linking U.S. school district test score distributions to a common scale. https://cepa.stanford.edu/sites/default/files/wp16-09-v201706.pdf

  • Reyes JW (2015) Lead policy and academic performance: insights from Massachusetts. Harv Educ Rev 85(1):75–107

    Article  Google Scholar 

  • Sampson RJ, Winter AS (2016) The racial ecology of lead poisoning: toxic inequality in Chicago neighborhoods 1995–2013. Du Bois Review: Social Science Research on Race, pp 1–23

    Article  Google Scholar 

  • Schwartz J, Otto D (1991) Lead and minor hearing impairment. Arch Environ Health 46:300–305

    Article  Google Scholar 

  • Selevan SG, Rice DC, Hogan KA, Euling SY, Pfahles-Hutchens A, Bethel J (2003) Blood lead concentration and delayed puberty in girls. N Engl J Med 348:1527–1536

    Article  Google Scholar 

  • Sharkey P, Faber JW (2014) Where, when, why, and for whom do residential contexts matter? Moving away from the dichotomous understanding of neighborhood effects. Annual Review of Sociology 40:559-579.

    Article  Google Scholar 

  • Shores K, Steinberg MP (2017) The impact of the great recession on student achievement: evidence from population data. CEPA Working Paper No. 17-09

  • Stock JH, Yogo M (2002) Testing for weak instruments in linear IV regression. NBER Working Paper No. 284

  • U.S. Census Bureau (2012) The 2006–2010 ACS 5-year selected population tables. Table B25036: tenure by year structure built. Accessed 27 Oct 2016

  • U.S. Department of Housing and Urban Development (HUD) (2011) American healthy homes survey: lead and arsenic findings. Accessed 8 March 2017. https://portal.hud.gov/hudportal/documents/huddoc?id=AHHS_Report.pdf

  • U.S. Department of Housing and Urban Development (HUD) (2015) Lead-based paint hazard control (LBPHC) grant program. FR-5900-N-12. Available at: https://portal.hud.gov/hudportal/documents/huddoc?id=2015lbphcnofa.pdf

  • U.S. Department of Housing and Urban Development (HUD) (2016) Archived funding announcements. Accessed 1 Jan 2017. Available at: https://archives.hud.gov/funding/index.cfm

  • Zhang N, Baker HW, Tufts M, Raymond RE, Salihu H, Elliott MR (2013) Early childhood lead exposure and academic achievement: evidence from Detroit public schools, 2008–2010. Am J Public Health 103(3):e72–e77

    Article  Google Scholar 

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Acknowledgements

The authors are grateful for the support from the Russell Sage Foundation, William T. Grant Foundation, and the Nelson A. Rockefeller Institute of Government. They would like to thank the anonymous reviewers for valuable comments and recommendations, as well as Sean Reardon, Steven Alvarado, participants at the RSF Workshop on Monitoring Educational Opportunity, and participants at the 2017 AEFP session on Special Education, Special Needs, and Health.

Funding

This study was funded by the Russell Sage Foundation and William T. Grant Foundation (Award #83-17-05). It was also supported by the Nelson A. Rockefeller Institute of Government.

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Authors and Affiliations

  1. Rockefeller College of Public Affairs and Policy, University at Albany, State University of New York, 135 Western Avenue, Albany, NY, 12222, USA

    Lucy C. Sorensen, Ashley M. Fox & Erika G. Martin

  2. School of Public Affairs, Arizona State University, Tempe, AZ, USA

    Heyjie Jung

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  1. Lucy C. Sorensen
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  2. Ashley M. Fox
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Correspondence to Lucy C. Sorensen.

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Responsible editor: Erdal Tekin

Appendix

Appendix

Table 7 Aggregate HUD lead hazard control grants by state
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Table 8 Sensitivity of results to alternative coding of suppressed elevated blood lead level counts
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Table 9 Full regression results: effect of county-level lead hazard control grants on childhood elevated blood lead level prevalence (first stage)
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Table 10 Full regression results: effect of state-level lead hazard control grants on childhood elevated blood lead level prevalence (first stage)
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Table 11 Placebo test for lead hazard control grant effects on childhood lead poisoning incidence
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Table 12 Full regression results: IV estimates of effect of lead poisoning incidence on mean student test scores (pooled across grade levels)
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Table 13 Full regression results: IV estimates of effect of lead poisoning incidence on racial achievement gaps (pooled across grade levels)
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Fig. 6
figure 6

Total HUD lead hazard control spending by year (2000–2016)

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Fig. 7
figure 7

Demographic trends for counties receiving LHC grants in 2003 compared to counties never receiving grants

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Fig. 8
figure 8

a Elevated blood lead level trends for counties receiving LHC grants in 2008 compared to counties never receiving grants. b Math score trends for counties receiving LHC grants in 2008 compared to counties never receiving grants

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Fig. 9
figure 9

Number of children tested trends for counties receiving LHC grants in 2008 compared to counties never receiving grants

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Fig. 10
figure 10

Per-pupil education expenditure trends for counties receiving LHC grants in 2008 compared to counties never receiving grants

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Sorensen, L.C., Fox, A.M., Jung, H. et al. Lead exposure and academic achievement: evidence from childhood lead poisoning prevention efforts. J Popul Econ 32, 179–218 (2019). https://doi.org/10.1007/s00148-018-0707-y

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  • DOI: https://doi.org/10.1007/s00148-018-0707-y

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