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August 2016Volume 175, Pages 173–181
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Blood Lead Levels in Young Children: US, 2009-2015

Leland F. McClure
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Leland F. McClure
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Correspondence

  • Reprint requests: Leland F. McClure, PhD, Director, Medical Science Liaison, Medical Affairs - Quest Diagnostics, 11636 Administration Drive, St Louis, MO 63146.
, PhD'Correspondence information about the author PhD Leland F. McClure
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Leland F. McClure
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Correspondence

  • Reprint requests: Leland F. McClure, PhD, Director, Medical Science Liaison, Medical Affairs - Quest Diagnostics, 11636 Administration Drive, St Louis, MO 63146.
,
Justin K. Niles
x
Justin K. Niles
, MA
,
Harvey W. Kaufman
x
Harvey W. Kaufman
, MD
Quest Diagnostics, Madison, NJ
Blood Lead Levels in Young Children: US, 2009-2015
DOI: https://doi.org/10.1016/j.jpeds.2016.05.005
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Objectives

To evaluate trends in blood lead levels in children <6 years of age, this Quest Diagnostics Health Trends report builds on previously reported National Health and Nutrition Examination Survey data with a much larger national group and adds more detail and novel assessments.

Study design

This report describes the results from a 6-year retrospective study (May 2009-April 2015) based on >5 million blood lead level results (including >3.8 million venous results) from children <6 years old living in all 50 states and the District of Columbia. We evaluated yearly changes and examined demographic categories including sex, pre-1950s housing construction, poverty income ratios (PIRs), Medicaid enrollment status, and geographic regions.

Results

Among children <6 years old, 3.0% exhibited blood lead levels ≥5.0 μg/dL (high). There were significant differences in high blood lead levels based on sex, pre-1950s housing construction quintiles, and PIR <1.25 and PIR >5 (all P < .01). Health and Human Services regions, states, and 3-digit ZIP code areas exhibited drastically different frequencies of high blood lead levels and blood lead levels ≥10.0 μg/dL (very high). Generally, levels declined over time for all groups.

Conclusion

Examination of more than 5 million venous blood lead level results in children younger than 6 years old allowed for a robust, detailed analysis of blood lead level group results by geography and other criteria that are prohibited with the narrower National Health and Nutrition Examination Survey database. Progress in reducing the burden of lead toxicity is a public health success story that is incomplete with some identified factors posing larger, ongoing challenges.

Keywords:

blood lead levels, children, pre-1950s housing construction, poverty income ratios, regions

Abbreviations:

ACCLPP (Advisory Committee on Childhood Lead Poisoning Prevention), CDC (Centers for Disease Control and Prevention), HHS (US Department of Health and Human Services), NHANES (National Health and Nutrition Examination Survey), PIR (Poverty income ratio)

Childhood lead toxicity is a preventable environmental disease with long-lasting adverse health and behavioral effects.1x1Agency for Toxic Substances and Disease Registry. Toxicological profile for lead. US Department of Health and Human Services, CDC, Agency for Toxic Substances and Disease Registry, Atlanta, GA; 2007

Google ScholarSee all References Public health services and other health professionals throughout the US have dedicated more than 4 decades of efforts to screen children, especially those at high risk, for lead exposure and to identify primary sources of lead.2x2Parsons, P.J., Reilly, A.A., and Esernio-Jenssen, D. Screening children exposed to lead: an assessment of the capillary blood lead fingerstick test. Clin Chem. 1997; 43: 302–311

PubMed | Google ScholarSee all References Federal and local environmental policies have included the removal of lead from gasoline, reduction of lead in paints, and testing of homes for lead-based paint. These efforts along with laboratory testing and case management efforts have been instrumental in significantly reducing blood lead levels in the US. The 2007-2010 National Health and Nutrition Examination Survey (NHANES) estimate of the geometric mean blood lead level was 1.3 μg/dL,3x3Centers for Disease Control and Prevention. Blood lead levels in children aged 1-5 years – United States, 1999-2010. MMWR Morb Mortal Wkly Rep. 2013; 62: 245–248

PubMed | Google ScholarSee all References which is a 90% decrease compared with the 1976-1980 NHANES II 12.8 μg/dL estimate.4x4Pirkle, J.L., Brody, D.J., Gunter, E.W., Kramer, R.A., Paschal, D.C., Flegal, K.M. et al. The decline of blood lead levels in the United States: the National Health and Nutrition Examination Surveys (NHANES). JAMA. 1994; 272: 284–291

Crossref | PubMed | Scopus (70) | Google ScholarSee all References

In 1991, the Centers for Disease Control and Prevention (CDC) recommended changes for preventing childhood lead poisoning, which included a reduction for the blood lead level deemed safe (from 25 μg/dL to 10 μg/dL).5x5Centers for Disease Control and Prevention. Preventing lead poisoning in young children. CDC, Atlanta; 1991

Google ScholarSee all References In May 2012, the CDC Advisory Committee on Childhood Lead Poisoning Prevention (ACCLPP) identified that there is no safe blood lead level and the CDC accepted ACCLPP recommendations to remove all CDC blood lead level references to “blood lead level of concern.”6x6CDC Advisory Committee on Childhood Lead Poisoning Prevention. Low level lead exposure harms children: A renewed call for primary prevention. CDC, Atlanta; 2012

Google ScholarSee all References The CDC position of “no safe blood lead level” is based on an absence of blood lead levels without effects and low blood lead levels that are associated with intellectual deficits, attention deficit behaviors, and poor academic achievement.7x7Chandramouli, K., Steer, C.D., Ellis, M., and Emond, A.M. Effects of early childhood lead exposure on academic performance and behavior of school age children. Arch Dis Child. 2009; 94: 844–848

Crossref | PubMed | Scopus (78) | Google ScholarSee all References, 8x8Nigg, J.T., Nikolas, M., Mark Knottnerus, G., Cavanagh, K., and Friderici, K. Confirmation and extension of association of blood lead level with attention-deficit/hyperactivity disorder (ADHD) and ADHD symptom domains at population-typical exposure levels. J Child Psychol Psychiatry. 2010; 51: 58–65

Crossref | PubMed | Scopus (91) | Google ScholarSee all References That these effects appear to be irreversible9x9Needleman, H.L., Schell, A., Bellinger, D., Leviton, A., and Allred, E.N. The long-term effects of exposure to low doses of lead in childhood. An 11-year follow-up report. N Engl J Med. 1990; 332: 83–88

Crossref | Scopus (837) | Google ScholarSee all References, 10x10Bellinger, D.C., Stiles, K.M., and Needleman, H.L. Low-level lead exposure, intelligence and academic achievement: a long-term follow-up study. Pediatrics. 1992; 90: 855–861

PubMed | Google ScholarSee all References, 11x11Rogan, W.J., Dietrich, K.N., Ware, J.H., Dockery, D.W., Salganik, M., Radcliffe, J. et al. The effect of chelation therapy with succimer on neuropsychological development in children exposed to lead. N Engl J Med. 2001; 344: 1421–1426

Crossref | PubMed | Scopus (237) | Google ScholarSee all References emphasizes a public health care shift to primary prevention rather than secondary and tertiary prevention efforts, which are based on responses after detecting lead exposure.

In May 2012, the CDC also adopted the ACCLPP committee recommendations to use the NHANES 97.5th blood lead level percentile (5.0 μg/dL) as an upper reference interval threshold to identify children with elevated blood lead levels. The 5.0 μg/dL value is based on 2 consecutive cycles of the NHANES blood lead level data distribution among study children 1-5 years of age. Based on the 5.0 μg/dL threshold, the 2012 ACCLPP committee report estimated 450 000 children in the US as having blood lead levels greater than the new reference limit.12x12Centers for Disease Control and Prevention. Response to Advisory Committee on Childhood Lead Poisoning Prevention Recommendations in “Low Level Exposure Harms Children: A Renewal Call of Primary Prevention” CDC. ; 2012http://www.cdc.gov/nceh/lead/acclpp/cdc_response_lead_exposure_recs.pdf. (Accessed May 10, 2016)

Google ScholarSee all References The NHANES analysis includes demographic categories with long-standing disparities of risk for elevated blood lead levels, including age, sex, race/ethnicity, age of housing, poverty income ratio (PIR), and Medicaid enrollment status.

Despite the insights provided by the NHANES analysis, the study has several limitations. One such limitation is that the low numbers of NHANES-enrolled children with blood lead levels ≥10 μg/dL (only 9 children in 2007-2008; 6 children in 2009-2010) make interpretation of population estimates of very high blood lead levels unreliable. In addition, the NHANES was not designed to produce estimates at the state and local level and may not detect statistically significant disparities with important public health implications.

This Quest Diagnostics Health Trends report describes the results of a 6-year retrospective study based on a large national clinical laboratory database with more than 5 million results from children younger than 6 years of age. Our analysis builds upon previously reported NHANES data and includes insights into yearly trends and the distributions of blood lead levels by specimen type (venous and capillary), sex, payer type, US Department of Health and Human Services (HHS) region, residence state, PIR, and pre-1950s housing construction.

Methods

The specimen requirement for venous blood lead level analysis is whole blood collected into an evacuated collection tube certified for lead testing, such as tan-top and royal blue-top tubes containing the anticoagulant EDTA. For the capillary collection method, the specimen collection container is the lavender-top capillary tube.

The blood lead level analyses were performed by the use of either inductively coupled plasma/mass spectrometry or the Zeeman graphite furnace atomic absorption spectroscopy. Instrument calibrations are performed with standards traceable to the National Institutes of Standards and Technology. Performance for all methods is in compliance with the ± 4 μg/dL (or 10%, whichever is greater) CDC accuracy standards.13x13Centers for Disease Control and Prevention. Screening young children for lead poisoning: Guidance for state and local public health officials; Appendix C1: The Lead Laboratory. ; 2013www.cdc.gov/nceh/lead/publications/screening.htm. (Accessed December 12, 2015)

Google ScholarSee all References The blood lead level results were evaluated with a 3.0 μg/dL lower reporting threshold. The laboratory analysis of venous specimens is consistent with the CDC definition for “confirmed elevated blood lead level” when indicated.14x14CDC Standard Surveillance Definitions and Classifications. ; 2013http://www.cdc.gov/nceh/lead/data/definitions.htm. (Accessed December 12, 2015)

Google ScholarSee all References

The blood lead level data set includes deidentified results of testing performed for children <6 years of age, from May 2009 through April 2015 (3 years before and after the 2012 CDC change from the 10 μg/dL “level of concern” to the 5.0 μg/dL reference interval threshold). Instances of blood lead level results reported as a specimen submitted in a tube/container not certified for lead testing were excluded from the study. This study was deemed exempt by the Western Institutional Review Board.

To avoid duplication of patient data, when 2 or more tests were associated with the same individual, only the first venous result (or the first capillary result if there were no venous results) within the data set was included in this study. The 3.0 μg/dL reporting threshold precluded our ability to estimate the mean blood lead level for the study with sufficient precision. Instead, analyses focused on the proportions of the population falling into each of 4 blood lead level groups: ≤3.0 μg/dL (below the reporting limit); 3.1-4.9 μg/dL (above the reporting limit and below the CDC 2012 reference interval threshold); 5.0-9.9 μg/dL (between the 2012 reference interval threshold and the previous 1991 CDC “level of concern”); and ≥10.0 μg/dL.

Patient data were limited to patients <6 years of age, corresponding to the CDC age definition for high risk. Blood lead levels results missing patient sex were excluded from sex analysis.

Data from the US Census Bureau's 2009-2013 American Community Survey 5-Year Estimates15x15US Census Bureau, 2009-2013 5-Year American Community Survey, http://factfinder.census.gov/faces/tableservices/jsf/pages-/productview.xhtml?pid=ACS_13_5YR_B25034&prodType=table. Accessed December 12, 2015.

Google ScholarSee all References were used to determine the proportion of housing constructed before 1950 by ZIP code. According to the CDC, “houses built before 1950 pose the greatest hazard to children because they are much more likely to contain lead-based paint than newer houses.”16x16CDC. Facts on Lead. ; 2013http://www.cdc.gov/nceh/lead/publications/1997/factlead.htm. (Accessed December 12, 2015)

Google ScholarSee all References Quintiles were defined as the percentage of the housing category by ZIP code. Quintile thresholds for pre-1950s housing were defined as <3.6%, 3.6%-12.9%, 13.0%-29.9%, 30.0%-50.9%, and ≥51.0%. All quintile thresholds were chosen to provide approximately equal numbers in each quintile group. Demographics were divided into quintiles to demonstrate trends in blood lead level proportions. ZIP codes are based on patient residence, not the site of the blood collection.

Data from the United States Census Bureau's 2008-2012 American Community Survey 5-Year Estimates17x17US Census Bureau, 2008-2012 5-Year American Community Survey, http://factfinder.census.gov/faces/tableservices/jsf/pages/-productview.xhtml?pid=ACS_12_5YR_B17024&prodType=table. Accessed December 12, 2015.

Google ScholarSee all References were used to determine PIR of children's area of residence by ZIP code. Quintiles were defined as the percentage of PIR <1.25 (low income) and PIR >5 (high income) by ZIP code. Quintile ranges were defined as <16.0%, 16.0%-27.9%, 28.0%-38.9%, 39.0%-51.9%, and ≥52.0% for PIR <1.25, and <2.8%, 2.8%-6.9%, 7.0%-13.9%, 14.0%-27.9%, and ≥28.0% for PIR >5.

This study included specimens submitted for blood lead level testing from all 50 states and the District of Columbia. Data were grouped for analysis by HHS region, state, and 3-digit ZIP code region. We limited our state analyses to those with at least 2000 children and our 3-digit ZIP code analysis to areas with at least 1000 children. The proportion of housing that was constructed before 1950 in various geographical regions also was analyzed. These data were weighted by the number of patients with specimens from individual ZIP codes.

Statistical Analyses

The Cochran-Armitage test was used to analyze trends in proportions of children with blood lead levels ≥5.0 μg/dL (high blood lead level) and ≥10.0 μg/dL (very high blood lead level) for various groups. Testing for statistical significance between the 2 groups was conducted with the χ2 test. Multivariable logistic regression models to determine characteristics associated with high blood lead level and very high blood lead level also are reported. Variables in both models were chosen based on plausibility and/or statistical significance in previous studies.3x3Centers for Disease Control and Prevention. Blood lead levels in children aged 1-5 years – United States, 1999-2010. MMWR Morb Mortal Wkly Rep. 2013; 62: 245–248

PubMed | Google ScholarSee all References Living in ZIP codes associated with the greatest quintile of pre-1950s housing, low income, and high income were included as binary variables. Living in HHS regions 1, 3, or 7 also was included as a binary variable. Despite the small measures of association determined by unadjusted ORs in logistic regression models, year of service, patient age, sex, and payer status were included in the multivariable models because of their potential as confounding factors. Results of adjusted and unadjusted models were stated as ORs and 95% CIs. Data were analyzed with SAS, version 9.4 (SAS Institute, Cary, North Carolina).18x18SAS, version 9.4. Cary, NC: SAS Institute.

Google ScholarSee all References

Results

This study included 5 266 408 blood lead levels from children <6 years of age. Venous blood draws represent 72.2% of all specimen submissions (n = 3 803 070). Blood lead levels were below the reporting threshold of ≤3.0 μg/dL in 94.9% of venous specimens; 3.1-4.9 μg/dL in 2.2%; and ≥5.0 μg/dL in 3.0%. Results from the  1 178 000 capillary specimens were slightly, but statistically significantly (P < .01), more likely to fall into greater blood lead level categories: capillary blood lead levels were ≤3.0 μg/dL in 93.6%, 3.1-4.9 μg/dL in 3.3%, and ≥5.0 μg/dL in 3.1%. There also was a group of 285 338 specimens with unknown draw type with the following blood lead level distribution: 95.8% ≤3.0 μg/dL, 2.3% between 3.0 and 4.9 μg/dL, and 1.9% ≥5.0 μg/dL. The remainder of the results section will focus on the 3 803 070 children with venous blood results.

Sex

Of the venous specimens tested, 1 947 693 (51.2%) were from boys and 1 842 881 (48.5%) were from girls; the other 12 496 (0.3%) specimens had no sex information. High blood lead level was only slightly greater for boys (3.1%) than girls (2.8%), although the difference was statistically significant (P < .01; Table I).

Table IBlood lead levels in children <6 years old: 2009-2015
Total≤3.0 μg/dL>3.0 and <5.0 μg/dL≥5.0 and <10.0 μg/dL≥10.0 μg/dL (Very high BLL)≥5.0 μg/dL (High BLL)
Number (Percent)
Total3 803 0703 607 874 (94.87)82 867 (2.18)90 092 (2.37)22 237 (0.58)112 329 (2.95)
Sex1
 Male1 947 6931 843 442 (94.65)44 032 (2.26)48 312 (2.48)11 907 (0.61)60 219 (3.09)
 Female1 842 8811 752 875 (95.12)38 384 (2.08)41 384 (2.25)10 238 (0.56)51 622 (2.80)
Pre-1950s housing quintile2
 <3.6%660 387647 545 (98.06)5777 (0.87)5817 (0.88)1248 (0.19)7065 (1.07)
 3.6-12.9%662 327643 939 (97.22)8522 (1.29)7994 (1.21)1872 (0.28)9866 (1.49)
 13.0-29.9%661 936637 074 (96.24)11 099 (1.68)11 116 (1.68)2647 (0.40)13 763 (2.08)
 30.0-50.9%659 314617 464 (93.65)17 581 (2.67)19 334 (2.93)4935 (0.75)24 269 (3.68)
 ≥51.0%627 376564 372 (89.96)25 622 (4.08)29 936 (4.77)7446 (1.19)37 382 (5.96)
Payer type3
 Private2 665 3302 531 010 (94.96)57 982 (2.18)61 863 (2.32)14 475 (0.54)76 338 (2.86)
 Medicaid/Medicare769 566734 185 (95.40)15 157 (1.97)16 288 (2.12)3936 (0.51)20 224 (2.63)
Low income (PIR <1.25) quintile4
 <16.0%703 782682 503 (96.98)9066 (1.29)9779 (1.39)2434 (0.35)12 213 (1.74)
 16.0-27.9%624 981602 837 (96.46)9874 (1.58)9816 (1.57)2454 (0.39)12 270 (1.96)
 28.0-38.9%643 452614 280 (95.47)12 798 (1.99)13 141 (2.04)3233 (0.50)16 374 (2.54)
 39.0-51.9%698 627658 817 (94.30)17 067 (2.44)18 214 (2.61)4529 (0.65)22 743 (3.26)
 ≥52.0%597 828549 471 (91.91)19 730 (3.30)23 144 (3.87)5483 (0.92)28 627 (4.79)
High income (PIR >5) quintile4
 <2.8%657 317613 075 (93.27)18 333 (2.79)21 018 (3.20)4891 (0.74)25 909 (3.94)
 2.8-6.9%666 236627 939 (94.25)16 417 (2.46)17 607 (2.64)4273 (0.64)21 880 (3.28)
 7.0-13.9%692 538658 850 (95.14)14 352 (2.07)15 261 (2.20)4075 (0.59)19 336 (2.79)
 14.0-27.9%614 839590 014 (95.96)10 800 (1.76)11 198 (1.82)2827 (0.46)14 025 (2.28)
 ≥28.0%637 740618 030 (96.91)8633 (1.35)9010 (1.41)2067 (0.32)11 077 (1.74)
HHS region5
 1: CT, MA, ME, NH, RI, VT165 624151 422 (91.43)5184 (3.13)7306 (4.41)1712 (1.03)9018 (5.44)
 2: NJ, NY722 385681 603 (94.35)19 431 (2.69)16 950 (2.35)4401 (0.61)21 351 (2.96)
 3: DE, DC, MD, PA, VA, WV406 681374 655 (92.13)11 407 (2.80)16 313 (4.01)4306 (1.06)20 619 (5.07)
 4: AL, FL, GA, KY, MS, NC, SC, TN509 539494 543 (97.06)6637 (1.30)7085 (1.39)1274 (0.25)8359 (1.64)
 5: IL, IN, MI, MN, OH, WI262 144244 002 (93.08)6711 (2.56)8849 (3.38)2582 (0.98)11 431 (4.36)
 6: AR, LA, NM, OK, TX264 833255 900 (96.63)3549 (1.34)4240 (1.60)1144 (0.43)5384 (2.03)
 7: IA, KS, MO, NE96 23287 446 (90.87)3292 (3.42)4424 (4.60)1070 (1.11)5494 (5.71)
 8: CO, MT, ND, SD, UT, WY21 37220 346 (95.20)436 (2.04)503 (2.35)87 (0.41)590 (2.76)
 9: AZ, CA, HI, NV874 401848 895 (97.08)13 291 (1.52)10 268 (1.17)1947 (0.22)12 215 (1.40)
 10: AK, OR, ID, WA11 70011 255 (96.20)212 (1.81)172 (1.47)61 (0.52)233 (1.99)
Time period (Year)
 May 2009-April 2010823 198770 737 (93.63)22 217 (2.70)24 185 (2.94)6059 (0.74)30 244 (3.67)
 May 2010-April 2011737 826698 385 (94.65)16 847 (2.28)18 449 (2.50)4145 (0.56)22 594 (3.06)
 May 2011-April 2012633 374602 166 (95.07)13 522 (2.13)14 171 (2.24)3515 (0.55)17 686 (2.79)
 May 2012-April 2013560 906534 990 (95.38)10 955 (1.95)11 993 (2.14)2968 (0.53)14 961 (2.67)
 May 2013-April 2014540 016516 139 (95.58)10 184 (1.89)10 941 (2.03)2752 (0.51)13 693 (2.54)
 May 2014-April 2015507 750485 457 (95.61)9142 (1.80)10 353 (2.04)2798 (0.55)13 151 (2.59)
View Table in HTML

PIR, povery income ratio.

Notes:

1 - 12 496 results did not have gender data.

2 - 531 730 results did not have pre-1950 house construction data available.

3 - 368 174 results did not have payer data available.

4 - 534 400 results did not have poverty/wealth data.

5 - 468 159 results did not have state data available.

Pre-1950s Housing Construction

Living in an area with a high proportion of pre-1950 housing construction was strongly associated with having a high blood lead level (Table I). Living in a ZIP code where ≥51.0% of housing units were constructed before 1950 (the highest quintile) was associated with a significantly larger proportion of high blood lead levels (OR 5.86, 95% CI 5.71-6.01) or very high blood lead levels (OR 6.34, 95% CI 5.97-6.74) than living in an area with the lowest quintile. There was a statistically significant trend for both high blood lead levels and very high blood lead levels among the pre-1950s housing quintiles (both P < .01, Table I).

Payer Type and PIRs

Approximately 20% of patients (n = 768 879) with venous blood draws had Medicaid as the payer and 687 had Medicare as the payer. Patients with Medicaid or Medicare had a slightly, but statistically significantly, lower frequency of high blood lead level than did those with private payers (2.6 vs 2.9%; P < .01).

Comparisons of other lead groups between payer types were also similar (Table I). The data also showed a positive association between percentage of PIR <1.25 in patient ZIP codes and high blood lead level (Table I). Children living in ZIP codes in which ≥52.0% have PIR <1.25 (the highest quintile) had a greater proportion of high blood lead level (OR 2.85, 95% CI 2.79-2.91) and very high blood lead level (OR 2.67, 95% CI 2.54-2.80) compared with those living in the lowest quintile. There was a statistically significant trend in both high blood lead level and very high blood lead level among the poverty quintiles (Table I). There was an inverse association between the greater-income ZIP codes and high blood lead level. Those living in ZIP codes with the greatest percentage of PIR >5 (the highest quintile) were much less likely to exhibit high blood lead levels (OR 0.43, 95% CI 0.42-0.44) and very high blood lead level (OR 0.43, 95% CI 0.41-0.46) than were those in the lowest quintile. There was a statistically significant trend in both high blood lead level and very high blood lead level among the PIR >5 quintiles (Table I).

Geographic Regions

Blood lead levels group results were analyzed by HHS region (Table I). Region 7 (Iowa, Kansas, Missouri, and Nebraska) had the largest proportion of both high blood lead levels (5.7%) and very high blood lead levels (1.1%). Region 1 (Connecticut, Massachusetts, Maine, New Hampshire, Rhode Island, and Vermont) and Region 3 (Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, and West Virginia) also had notably large proportions of high blood lead levels (5.4% and 5.1%, respectively), and very high blood lead levels (1.0% and 1.1%, respectively).

The states with the largest proportions of high blood lead levels were Minnesota (10.3%), Pennsylvania (7.8%), Kentucky (7.1%), Ohio (7.0%), and Connecticut (6.7%) (Table II). All these states and 20 others (25/37, 68%) exhibited a decline in the proportion of high blood lead levels between the first year and the final year of the study. New Hampshire had the largest absolute decline (from 9.7% to 2.6% high blood lead levels), and Mississippi had the largest absolute increase (from 3.1% to 6.3% high blood lead levels) between the first year and the final year of the study. Florida and California had the lowest proportions of high blood lead levels (1.1% and 1.4%, respectively) and very high blood lead levels (0.1% and 0.2%, respectively).

Table IIBlood lead levels in children < 6 years old by state
TotalMay 2009-April 2015May 2009-April 2010May 2014-April 2015
≤3.0 μg/dL>3.0 and <5.0 μg/dL≥5.0 and <10.0 μg/dL≥10.0 μg/dL≥5.0 μg/dLTotal≥5.0 μg/dLTotal≥5.0 μg/dL
StateNumber (Percent)Absolute % change
MN23452030 (86.57)74 (3.16)184 (7.85)57 (2.43)241 (10.28)63860 (9.40)34526 (7.54)−1.86
PA190 843168 214 (88.14)7728 (4.05)11 633 (6.10)3268 (1.71)14 901 (7.81)41 5684444 (10.69)21 7821644 (7.55)−3.14
KY85307598 (89.07)324 (3.80)461 (5.40)147 (1.72)608 (7.13)1291125 (9.68)172770 (4.05)−5.63
OH35 70331 715 (88.83)1501 (4.20)1889 (5.29)598 (1.67)2487 (6.97)6420575 (8.96)3668209 (5.70)−3.26
CT76 52068 697 (89.78)2705 (3.54)4099 (5.36)1019 (1.33)5118 (6.69)16 0951324 (8.23)10 250639 (6.23)−2.00
WI52164700 (90.11)170 (3.26)255 (4.89)91 (1.74)346 (6.63)2275165 (7.25)28419 (6.69)−0.56
MO82 20074 375 (90.48)2976 (3.62)3931 (4.78)918 (1.12)4849 (5.90)20 1091450 (7.21)9918474 (4.78)−2.43
NH10 5719616 (90.97)344 (3.25)474 (4.48)137 (1.30)611 (5.78)1236120 (9.71)179247 (2.62)−7.09
MI30 13227 427 (91.02)967 (3.21)1411 (4.68)327 (1.09)1738 (5.77)7650502 (6.56)4163208 (5.00)−1.56
LA17 89116 491 (92.17)524 (2.93)647 (3.62)229 (1.28)876 (4.90)4180249 (5.96)247089 (3.60)−2.36
MS98699044 (91.64)362 (3.67)388 (3.93)75 (0.76)463 (4.69)114035 (3.07)57236 (6.29)3.22
SC71146611 (92.93)179 (2.52)261 (3.67)63 (0.89)324 (4.55)101136 (3.56)80154 (6.74)3.18
IN20 64519 295 (93.46)479 (2.32)663 (3.21)208 (1.01)871 (4.22)2277115 (5.05)3282106 (3.23)−1.82
MA78 01672 651 (93.12)2123 (2.72)2698 (3.46)544 (0.70)3242 (4.16)7564374 (4.94)20 969777 (3.71)−1.23
WV11 31510 561 (93.34)318 (2.81)338 (2.99)98 (0.87)436 (3.85)161195 (5.90)196555 (2.80)−3.10
IL168 103158 835 (94.49)3520 (2.09)4447 (2.65)1301 (0.77)5748 (3.42)37 6751815 (4.82)23 036644 (2.80)−2.02
OK23 60522 356 (94.71)467 (1.98)616 (2.61)166 (0.70)782 (3.31)346896 (2.77)3909116 (2.97)0.20
TN15 20414 372 (94.53)331 (2.18)417 (2.74)84 (0.55)501 (3.30)172749 (2.84)336895 (2.82)−0.02
NY598 685562 660 (93.98)17 291 (2.89)14 880 (2.49)3854 (0.64)18 734 (3.13)140 5585448 (3.88)72 2651799 (2.49)−1.39
NC15 73114 995 (95.32)270 (1.72)371 (2.36)95 (0.60)466 (2.96)181843 (2.37)7517264 (3.51)1.14
AL94848990 (94.79)222 (2.34)225 (2.37)47 (0.50)272 (2.87)167058 (3.47)161640 (2.48)−0.99
UT23752243 (94.44)64 (2.69)56 (2.36)12 (0.51)68 (2.86)45820 (4.37)35219 (5.40)1.03
MD157 736150 431 (95.37)2849 (1.81)3713 (2.35)743 (0.47)4456 (2.82)30 5891179 (3.85)23 340512 (2.19)−1.66
AR78657518 (95.59)129 (1.64)171 (2.17)47 (0.60)218 (2.77)159333 (2.07)80523 (2.86)0.79
KS11 85911 332 (95.56)205 (1.73)265 (2.23)57 (0.48)322 (2.72)237684 (3.54)177234 (1.92)−1.62
GA56 86454 194 (95.30)1147 (2.02)1309 (2.30)214 (0.38)1523 (2.68)10 445257 (2.46)7952226 (2.84)0.38
CO18 52817 674 (95.39)359 (1.94)423 (2.28)72 (0.39)495 (2.67)3395126 (3.71)375085 (2.27)−1.44
NM26212520 (96.15)35 (1.34)53 (2.02)13 (0.50)66 (2.52)2964 (1.35)96426 (2.70)1.35
OR65626302 (96.04)114 (1.74)105 (1.60)41 (0.62)146 (2.22)124232 (2.58)95630 (3.14)0.56
NJ123 700118 943 (96.15)2140 (1.73)2070 (1.67)547 (0.44)2617 (2.12)29 570810 (2.74)13 706251 (1.83)−0.91
VA26 91126 088 (96.94)309 (1.15)381 (1.42)133 (0.49)514 (1.91)7343125 (1.70)303170 (2.31)0.61
DE86478415 (97.32)80 (0.93)117 (1.35)35 (0.40)152 (1.76)196931 (1.57)110122 (2.00)0.43
TX212 851207 015 (97.26)2394 (1.12)2753 (1.29)689 (0.32)3442 (1.62)38 871699 (1.80)31 439519 (1.65)−0.15
WA24742391 (96.65)45 (1.82)30 (1.21)8 (0.32)38 (1.54)63615 (2.36)1935 (2.59)0.23
DC11 22910 946 (97.48)123 (1.10)131 (1.17)29 (0.26)160 (1.42)251841 (1.63)174917 (0.97)−0.66
CA873 944848 450 (97.08)13 285 (1.52)10 262 (1.17)1947 (0.22)12 209 (1.40)200 4133538 (1.77)107 4431448 (1.35)−0.42
FL386 743378 739 (97.93)3802 (0.98)3653 (0.94)549 (0.14)4202 (1.09)72 9511070 (1.47)59 019513 (0.87)−0.60
View Table in HTML

Absolute change reflects the difference in >5.0 μg/dL from the first to the second time periods.

Data from 325 3-digit ZIP code regions with more than 1000 specimens (36.0% of all 3-digit ZIP codes with specimens in the study) also were analyzed to assess their impact on state data. In 6 regions, >14.0% of specimens had high blood lead levels: Syracuse, NY (40.1%), Buffalo, NY (18.8%), Cincinnati, OH (16.0%), Poughkeepsie, NY (14.9%), York, PA (14.4%), and Oil City, PA (14.0%). The 11 regions with the largest proportions of specimens with very high blood lead levels also were all in New York, Pennsylvania, or Ohio. Syracuse, NY (16.0%), Buffalo, NY (6.0%), York, PA (5.5%), Poughkeepsie, NY (4.9%), and Oil City, PA (4.3%) had the greatest rates in the study. In 49 3-digit ZIP codes, <1.0% of specimens had high blood lead levels. Eighteen of these 3-digit ZIP codes were found in California, including San Jose (0.61%), which had the lowest proportion in the study. Eight were found in Florida, with South Florida (0.65%) having the lowest proportion in Florida.

Yearly Changes in Blood Lead Level Distribution

The distributions of patient blood lead levels showed year-over-year percentage increases in blood lead level groups ≤3.0 μg/dL (Table I). This increase outpaced the decrease in the 3.1-4.9 μg/dL blood lead group, resulting in a net decrease of those below the 2012 CDC 5 μg/dL threshold: from 3.67% for May 2009-April 2010 to 2.59% for May 2014-April 2015. For the 5.0-9.9 μg/dL blood lead level group and the very high blood lead level group, the patient distributions showed year-over-year decreases during the same period (Table I). May 2014-April 2015 showed a slight reversal of these trends. The top 2.5% blood lead level threshold (97.5th percentile) was 5.1 μg/dL every year of the study.

Yearly Changes in High Blood Lead Level for Various Risk Factors

Table III illustrates the trends in high blood lead levels for all the risk factors mentioned previously across the 6 years of the study. Male subjects maintained a greater proportion of high blood lead level than female subjects during each year of the study, and this difference remained similar over the years (0.21%-0.39%). The statistically significant trend among ZIP codes with increasing proportions of pre-1950s housing quintiles and PIR <1.25 remained when we examined data from each year of the study individually. Patients with private payer insurance had larger rates of high blood lead levels than patients with Centers for Medicare and Medicaid Services payers each year from May 2009-April 2014 but exhibited a lower rate of high blood lead levels than those with Centers for Medicare and Medicaid Services payers during the final year of the study. HHS Regions 1, 3, and 7 all exhibited a substantial decline in high blood lead level proportion during the study period but were the only regions with >4.0% high blood lead levels during the final year of the study. HHS Region 10 was the only region that had an increase in high blood lead levels during the study period and was the only factor examined that did not demonstrate a statistically significant (P < .05) downward trend in high blood lead level over the study period.

Table IIITrends in high blood lead levels of children <6 years old
May 2009-April 2015May 2009-April 2010May 2010-April 2011May 2011-April 2012May 2012-April 2013May 2013-April 2014May 2014-April 2015Significant trend
3 803 070823 198737 826633 374560 906540 016507 750
Number (Percent)
Gender1
 Male1 947 69360 219 (3.09)16 216 (3.86)12 079 (3.20)9357 (2.89)8063 (2.81)7379 (2.66)7125 (2.72)*
 Female1 842 88151 622 (2.80)13 856 (3.47)10 417 (2.91)8245 (2.68)6828 (2.51)6277 (2.40)5999 (2.44)*
Pre-1950 housing quintile2
 <3.6%660 3877065 (1.07)1555 (1.21)1295 (1.05)1097 (0.99)1015 (1.01)855 (0.89)1248 (1.23)P = .0446
 3.6-12.9%662 3279866 (1.49)2124 (1.50)1993 (1.52)1785 (1.59)1411 (1.42)1262 (1.37)1291 (1.51)P = .0290
 13.0-29.9%661 93613 763 (2.08)3587 (2.50)2725 (2.13)2288 (2.05)1923 (1.95)1642 (1.78)1598 (1.82)*
 30.0-50.9%659 31424 269 (3.68)6706 (4.74)4743 (3.77)3817 (3.51)3310 (3.34)2966 (3.09)2727 (3.10)*
 51.0% +627 37637 382 (5.96)10 766 (7.59)7573 (6.27)5615 (5.54)4669 (5.25)4550 (4.94)4209 (5.13)*
Payer type3
 Private2 665 33076 338 (2.86)22 060 (3.53)15 933 (2.94)11 504 (2.74)9531 (2.53)8899 (2.49)8411 (2.45)*
 Medicaid/Medicare769 56620 224 (2.63)4371 (3.35)3492 (2.80)3583 (2.50)3092 (2.44)2869 (2.11)2817 (2.60)*
Low income (PIR <1.25) quintile4
 <16.0%703 78212 213 (1.74)2993 (2.02)2266 (1.70)2005 (1.73)1610 (1.54)1528 (1.54)1811 (1.78)*
 16.0-28.9%624 98112 270 (1.96)3116 (2.34)2586 (2.10)1947 (1.88)1633 (1.75)1566 (1.75)1422 (1.73)*
 29.0-39.9%643 45216 374 (2.54)4327 (3.19)3334 (2.65)2531 (2.35)2100 (2.19)2034 (2.20)2048 (2.37)*
 40.0-51.9%698 62722 743 (3.26)6424 (4.19)4433 (3.35)3476 (2.99)3067 (2.97)2752 (2.74)2591 (2.78)*
 52.0% +597 82828 627 (4.79)7842 (6.25)5684 (4.98)4632 (4.58)3899 (4.38)3383 (3.91)3187 (3.92)*
High income (PIR >5) quintile4
 <2.8%657 31725 909 (3.94)7241 (5.06)5045 (4.03)4156 (3.78)3487 (3.58)3063 (3.28)2917 (3.31)*
 2.8-6.8%666 23621 880 (3.28)6152 (4.31)4346 (3.46)3359 (3.05)2886 (2.91)2631 (2.69)2506 (2.77)*
 6.9-13.9%692 53819 336 (2.79)4894 (3.37)3883 (2.87)3046 (2.62)2672 (2.56)2513 (2.53)2328 (2.52)*
 14.0-27.9%614 83914 025 (2.28)3605 (2.77)2863 (2.38)2183 (2.12)1843 (2.05)1673 (1.95)1858 (2.17)*
 28.0% +637 74011 077 (1.74)2810 (2.08)2166 (1.76)1847 (1.76)1421 (1.49)1383 (1.51)1450 (1.65)*
HHS region5
 1: CT, MA, ME, NH, RI, VT165 6249018 (5.44)1824 (7.30)1636 (7.39)1330 (5.06)1147 (4.45)1607 (4.82)1474 (4.46)*
 2: NJ, NY722 38521 351 (2.96)6258 (3.68)4997 (3.25)3342 (2.84)2393 (2.42)2311 (2.41)2050 (2.38)*
 3: DE, DC, MD, PA, VA, WV406 68120 619 (5.07)5915 (6.91)4128 (5.23)2941 (4.35)2822 (4.52)2439 (4.22)2320 (4.38)*
 4: AL, FL, GA, KY, MS, NC, SC, TN509 5398359 (1.64)1673 (1.82)1598 (1.75)1368 (1.57)1376 (1.68)1046 (1.40)1298 (1.57)*
 5: IL, IN, MI, MN, OH, WI262 14411 431 (4.36)3232 (5.68)1974 (4.41)1942 (4.15)1740 (4.20)1331 (3.55)1212 (3.48)*
 6: AR, LA, NM, OK, TX264 8335384 (2.03)1081 (2.23)1012 (1.96)1041 (2.18)816 (2.08)661 (1.73)773 (1.95)*
 7: IA, KS, MO, NE96 2325494 (5.71)1610 (7.02)1010 (5.55)866 (5.55)774 (5.56)654 (4.93)580 (4.72)*
 8: CO, MT, ND, SD, UT, WY21 372590 (2.76)156 (3.92)138 (3.69)63 (1.98)57 (1.95)69 (2.03)107 (2.58)*
 9: AZ, CA, HI, NV874 40112 215 (1.40)3540 (1.77)2328 (1.32)2004 (1.41)1574 (1.24)1320 (1.09)1449 (1.35)*
 10: AK, OR, ID, WA11 700233 (1.99)58 (2.51)51 (1.87)24 (1.07)34 (1.87)28 (2.11)38 (2.96)P = .2356
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All values Number (Percent) reflect results of ≥5.0 μg/dL; CDC changed threshold to 5.0 μg/dL in May 2012.

Notes:

1 - chi2 P < .01 for all years; 12 496 results did not have gender data.

2 - Cochran Armitage test for trend P < .01 for all years; 531 730 results did not have pre-1950 house construction data available.

3 - 368 174 results did not have payer data available.

4 - Cochran Armitage test for trend P < .01 for all years; 534 400 results did not have poverty data.

5 - 468 159 results did not have state data available.

High Blood Lead Level and Very High Blood Lead Level Models

Logistic regression models were used to analyze the impact of the factors examined in Table I on high blood lead levels and very high blood lead levels. In unadjusted models, the strongest measures of association with high blood lead levels were being in the greatest pre-1950s housing quintile (OR 2.99, 95% CI 2.95-3.03) and living in HHS Region 1, 3, or 7 (OR 2.43, 95% CI 2.40-2.46). Living in a region in the lowest income quintile also was associated with high blood lead level (OR 2.06, 95% CI 2.03-2.09), whereas living in a region in the top income quintile had a significant protective effect (OR for high blood lead level = 0.56, 95% CI 0.54-0.57). The measures of association for these factors were similar in the adjusted multivariable model (Table IV). Private payer status had a small but significant association with high blood lead levels in the unadjusted model (OR 1.09, 95% CI 1.08-1.11) but had a significant protective effect in the adjusted model (aOR 0.84, 95% CI 0.82-0.85). Measures of association in the very high blood lead level models (both adjusted and unadjusted) were similar to those in the high blood lead level models (Table IV).

Table IVLogistic models: Factors associated with high blood lead levels and very high blood lead levels
Factors associated with high BLL (≥5.0 μg/dL)Factors associated with very high BLL (≥10.0 μg/dL)
Unadjusted OR95% CIaOR95% CIUnadjusted OR95% CIaOR95% CI
Study year0.93(0.92-0.93)0.92(0.91-0.92)0.94(0.93-0.95)0.93(0.92-0.94)
Private payer1.09(1.08-1.11)0.84(0.82-0.85)1.06(1.02-1.10)0.80(0.77-0.83)
Male1.11(1.09-1.12)1.11(1.09-1.13)1.10(1.07-1.13)1.08(1.04-1.11)
Top housing quintile2.99(2.94-3.02)2.50(2.46-2.54)2.96(2.87-3.04)2.58(2.50-2.68)
Top 3 HHS regions (1,3,7)2.43(2.40-2.46)2.23(2.20-2.26)2.48(2.40-2.55)2.21(2.13-2.29)
Top poverty quintile2.06(2.03-2.09)1.64(1.61-1.67)1.95(1.88-2.01)1.55(1.50-1.61)
Top wealth quintile0.56(0.54-0.57)0.65(0.64-0.67)0.53(0.51-0.55)0.62(0.59-0.65)
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BLL, blood lead level; CI, confidence interval; OR, odds ratio.

Discussion

Reducing blood lead levels in children has been and continues to be a major public health success. The declining blood lead levels are the result of public health initiatives that include the removal of leaded gasoline, the banning of lead paint, effective treatment of potable water supplies, and remediation of homes found to be contaminated with lead. Studies conducted by the CDC3x3Centers for Disease Control and Prevention. Blood lead levels in children aged 1-5 years – United States, 1999-2010. MMWR Morb Mortal Wkly Rep. 2013; 62: 245–248

PubMed | Google ScholarSee all References, 19x19Raymond, J., Wheeler, W., and Brown, M.J. Lead screening and prevalence of blood lead levels in children aged 1–2 years—Child Blood Lead Surveillance System, United States, 2002–2010 and National Health and Nutrition Examination Survey, United States, 1999–2010. MMWR Suppl. 2014; 63: 36–42

Google ScholarSee all References have provided valuable insight into the changing lead levels in children and associated risk factors. The millions of test results reported by individual states have allowed the CDC to track the changes in lead levels over time.19x19Raymond, J., Wheeler, W., and Brown, M.J. Lead screening and prevalence of blood lead levels in children aged 1–2 years—Child Blood Lead Surveillance System, United States, 2002–2010 and National Health and Nutrition Examination Survey, United States, 1999–2010. MMWR Suppl. 2014; 63: 36–42

Google ScholarSee all References The demographic factors associated with high blood lead levels, however, come from a much smaller set: n = 793 from 2007-2010 for ages 1-2 years19x19Raymond, J., Wheeler, W., and Brown, M.J. Lead screening and prevalence of blood lead levels in children aged 1–2 years—Child Blood Lead Surveillance System, United States, 2002–2010 and National Health and Nutrition Examination Survey, United States, 1999–2010. MMWR Suppl. 2014; 63: 36–42

Google ScholarSee all References and n = 1653 from 2007-2010 for ages 1-5 years.13x13Centers for Disease Control and Prevention. Screening young children for lead poisoning: Guidance for state and local public health officials; Appendix C1: The Lead Laboratory. ; 2013www.cdc.gov/nceh/lead/publications/screening.htm. (Accessed December 12, 2015)

Google ScholarSee all References The study presented here examines similar factors in a much larger data set of 3.8 million children. The CDC studies also were unable to look at factors associated with blood lead level ≥10.0 μg/dL because of small numbers (9 children in 2007-2008; 6 children in 2009- 2010).3x3Centers for Disease Control and Prevention. Blood lead levels in children aged 1-5 years – United States, 1999-2010. MMWR Morb Mortal Wkly Rep. 2013; 62: 245–248

PubMed | Google ScholarSee all References In contrast, our study was able to examine factors associated with very high venous blood lead level results (n = 22 237).

Our study provides insights for the time period through mid-2015, 4.5 years after the end of data collection in the most recent NHANES report, which included data through the end of 2010. This timeframe extension enabled the examination of the continuing decline in high blood lead level and very high blood lead level levels. This was true for the population as whole (from 3.67% to 2.59% high blood lead levels and from 0.74% to 0.55% very high blood lead levels) and for most demographic groups and geographic regions. The results also demonstrate a slight increase in the incidence of high blood lead levels and very high blood lead levels in the final year of the study. After years of consecutive decline, the rise was unexpected, especially given that there was no major observable change in demographic proportions during the final year. Future studies are needed to evaluate the evolution of high blood lead levels and very high blood lead levels.

To a large extent, the results presented here confirm the significance of factors examined by the CDC3x3Centers for Disease Control and Prevention. Blood lead levels in children aged 1-5 years – United States, 1999-2010. MMWR Morb Mortal Wkly Rep. 2013; 62: 245–248

PubMed | Google ScholarSee all References, 19x19Raymond, J., Wheeler, W., and Brown, M.J. Lead screening and prevalence of blood lead levels in children aged 1–2 years—Child Blood Lead Surveillance System, United States, 2002–2010 and National Health and Nutrition Examination Survey, United States, 1999–2010. MMWR Suppl. 2014; 63: 36–42

Google ScholarSee all References and exhibit similar measures of association. Our study, using a different methodology, confirms the findings in NHANES associating pre-1950s housing data and low PIR with high blood lead level. Examining PIR and housing construction data by ZIP code instead of direct patient data is a limiting factor but also highlights the ability of physicians to identify geographic regions with increased risk, particularly in the event that individual patient risk factors are unavailable or difficult to obtain. Using data available on the US Census Bureau website, health care experts can determine the proportion of housing constructed before 1950 and PIR of the ZIP codes they serve to help assess the level of risk in their patients, even if individual factors are not available.

All previously reported NHANES cycles found increased levels of high blood lead level in Medicaid patients (the differences in 1999-2002 and in 2003-2006 were statistically significant). The current Quest Diagnostics Health Trends study found that children with private payers had a significantly larger rate of high blood lead level than those with Medicaid/Medicare payers. In the adjusted model, however, private payer status had a significant protective effect. Thus, with all factors explored in the study considered together, the private payer results seem to indicate the same relationship found in the NHANES studies.

There were also some differences between our findings and those of the NHANES studies. The 2003-2006 and 2007-2010 NHANES cycles both found female participants to have slightly greater proportions of high blood lead level than male participants (although these differences were not found to be statistically significant). In the present study, male participants exhibited a small but statistically significantly larger proportion of high blood lead levels than female participants.

Our study examined results from patients living in all 50 states and the District of Columbia; however, analyses by state were limited to the 36 states and the District of Columbia with more than 2000 specimens during the study period. Our results for high blood lead level at the state level are often similar (within 3%) to the results reported by the CDC in their national surveillance data (2010-2014),20x20Centers for Disease Control and Prevention. CDC's National Surveillance Data (1997-2014). ; 2016http://www.cdc.gov/nceh/lead/data/national.htm. (Accessed March 10, 2016)

Google ScholarSee all References but there are also interesting differences. The rates of high blood lead level in our study were considerably lower than those reported by the CDC for New Hampshire (6.2% vs 12.0%), Mississippi (4.5% vs 9.2%), and Illinois (4.5% vs 7.9%). Only Minnesota showed a considerably larger rate of high blood lead level in our study than in the CDC report (10.3% vs 2.9%). At the national level, we found a virtually identical rate of very high blood lead level (0.58%) as the CDC (0.57%) over a similar 5-year period, but the rate of high blood lead level was lower in our study (2.95% vs 5.48%). The reasons for these differences are unclear but could reflect the inclusion of capillary blood results in the CDC data.

According to the CDC, “houses built before 1950 pose the greatest hazard to children because they are much more likely to contain lead-based paint than newer houses.”16x16CDC. Facts on Lead. ; 2013http://www.cdc.gov/nceh/lead/publications/1997/factlead.htm. (Accessed December 12, 2015)

Google ScholarSee all References Lead-contaminated dust on floors, windowsills, and window wells is associated with elevated blood lead levels in children.21x21Lanphear, B.P., Weitzman, M., Winter, N.L., Eberly, S., Yakir, B., Tanner, M. et al. Lead-contaminated house dust and urban children’s blood lead levels. Am J Public Health. 1996; 86: 1416–1421

Crossref | PubMed | Scopus (133) | Google ScholarSee all References Our findings showed that, in general, the regions with the greatest adjusted level of pre-1950s housing construction had the greatest proportions of patients with high blood lead levels. HHS Region 2 (New York and New Jersey) was an interesting deviation from this trend. Despite having the greatest level of housing built before 1950 (based on study participant ZIP codes), the overall levels of high blood lead level were below average for the study. It is also interesting that New York State (3.1%) was near the national average (3.0%) for high blood lead level while having several 3-digit ZIP codes with the largest proportions of high blood lead levels and very high blood lead levels found in the study. The impact of abatement and active lead surveillance in these states is also unclear. In general, southern regions had lower proportions of high blood lead levels. This includes Florida, with more than 386 000 specimens and 1.1% with high blood lead levels, and California, with more than 873 000 specimens and 1.4% with high blood lead levels. We have no easy explanation why 12 of the 36 states and the District of Columbia, with sufficient number of results, had an increase in the proportion of high blood lead levels between the first year and the final year of the study.

We found that living in ZIP codes with greater percentages of residents <1.25 PIR exhibited a stronger association with high blood lead levels than individual payer type. The reasons for this perplexing difference are unclear. One possibility may be that ZIP codes with greater levels of low income also have greater proportions of housing built before 1950 or other associated factors. Although this relationship may exist, the multivariable models indicate that it is not reason for the association, because both variables maintain significant associations with high blood lead levels and very high blood lead levels in the adjusted multivariable models.

All risk factors associated with high blood lead levels also were associated with very high blood lead levels. In both unadjusted and adjusted models, the measures of association were remarkably similar. This finding is reassuring because the risk factors identified in previous studies were not only confirmed for the most part in this larger study but found to be associated with very high blood lead levels as well.

The major strengths of this study are its large size, national representation with data from 50 states and the District of Columbia, and the inclusion of data through mid-2015. Analyses were conducted on more than 5 million results for children <6 years of age. The analyses focused on more than 3.8 million results of venous blood draws from children <6 years of age, consistent with the CDC definition of confirmed elevated blood lead level. This study also examined demographics for the vast majority of participants. Having demographics available for so many participants enabled analysis of factors associated with very high blood lead levels.

This study also had limitations. The 3.0 μg/dL reporting threshold precluded our ability to estimate the mean blood lead level for the study population. Some blood lead level groups are narrower than the range of instrument variability, but we assume there is no bias in the data set. It is also possible that some patients were tested as a follow-up to prior blood lead level results at another laboratory or because healthcare providers suspected a high probability of elevated blood lead level. It also may be possible that population segments or regional populations deemed to be at risk are being tested more frequently. Sociological, familial, and environmental factors also may play a role in determining who is tested for lead; however, with our 97.5th percentile being the same as found in NHANES, we feel the selection bias is minimal. Quest Diagnostics does not perform all lead testing in the country, and these data should only be seen as a large sample of national data. These data do not necessarily reflect the population as a whole but reflect those tested in medical practices in the US.

In summary, progress in reducing the burden of lead toxicity is a public health success story that is incomplete. This analysis of more than 5 million blood lead level results over a 6-year period, extending through April 2015, includes 3.8 million venous blood lead level results for infants and children <6 years of age. This allowed for a robust, detailed analysis of results by geography and other criteria that are impossible with the narrower NHANES approach. Unique observations include the correlation of results for patients with blood lead level results of ≥10.0 μg/dL to those with results of 5.1-10.0 μg/dL. Many of the 3-digit ZIP code regions with high blood lead levels and very high blood lead levels are in New York, Pennsylvania, and Ohio. Additional study will be necessary to assure that the improvements reported will continue and that specific state and local efforts achieve the desired goals.

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Funded by Quest Diagnostics, which provided support in the form of salaries for all authors but did not have any additional role in the study design, collection, analysis and interpretation of data, writing of the manuscript, or decision to publish. The authors declare no conflicts of interest.

© 2016 Elsevier Inc. All rights reserved.
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