| Literature DB >> 23734241 |
Jianghong Liu1, Linda Li, Yingjie Wang, Chonghuai Yan, Xianchen Liu.
Abstract
OBJECTIVES: Examine the relationships between blood lead concentrations and children's intelligence quotient (IQ) and school performance. PARTICIPANTS AND METHODS: Participants were 1341 children (738 boys and 603 girls) from Jintan, China. Blood lead concentrations were measured when children were 3-5 years old. IQ was assessed using the Chinese version and norms of the Wechsler Preschool and Primary Scale of Intelligence - Revised when children were 6 years old. School performance was assessed by standardized city tests on 3 major subjects (Chinese, Math, and English [as a foreign language]) when children were age 8-10 years.Entities:
Mesh:
Substances:
Year: 2013 PMID: 23734241 PMCID: PMC3667072 DOI: 10.1371/journal.pone.0065230
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Sample characteristics.
| N | % | ||
|
| 1341 | ||
| Male | 738 | 55.0 | |
| Female | 603 | 45.0 | |
|
| 1341 | 4.84(0.86) | |
| 3 years | 316 | 23.6 | |
| 4 years | 415 | 30.9 | |
| 5 years | 610 | 45.5 | |
|
| 1341 | ||
| City (Jianshe) | 538 | 40.1 | |
| Suburban (Huacheng) | 521 | 38.9 | |
| Rural (Xuebu) | 282 | 21.0 | |
|
| 1304 | ||
| ≤Middle school | 503 | 38.6 | |
| High school | 420 | 32.2 | |
| College or higher | 381 | 29.2 | |
|
| 1262 | ||
| Unemployed | 52 | 4.1 | |
| Physical worker | 718 | 56.9 | |
| Professional worker | 492 | 39.0 | |
|
| 1305 | ||
| ≤Middle school | 657 | 50.3 | |
| High school | 384 | 29.4 | |
| College or higher | 264 | 20.2 | |
|
| 1273 | ||
| No | 563 | 44.2 | |
| Occasionally | 454 | 35.7 | |
| Several times/wk | 41 | 3.2 | |
| <10 cigarettes/wk | 127 | 10.0 | |
| 10–20 cigarettes/wk | 71 | 5.6 | |
| >20 cigarettes/wk | 17 | 1.3 | |
|
| Mean (SD) | 1341 | 8.13 (0.83) |
|
| Mean (SD) | 1341 | 6.43(2.64) |
| <6.0 | 611 | 45.6 | |
| 6.0 to <8.0 | 440 | 32.8 | |
| 8.0 to <10.0 | 185 | 13.8 | |
| ≥10.0 | 105 | 7.8 |
Number of children differs across sample characteristics due to missing values.
Pearson correlations between blood lead concentrations and IQ and school performance.
| Mean (SD) | N | Blood lead concentration | VIQ | PIQ | FIQ | Chinese | Math | ||
|
| 6.43(2.64) | 1341 | 1.00 | ||||||
|
| VIQ | 103.95(14.84) | 1331 | .011 | 1.00 | ||||
| PIQ | 104.06(15.07) | 1331 | −.056 | .498 | 1.00 | ||||
| FIQ | 104.19(14.38) | 1331 | −.026 | .869 | .857 | 1.00 | |||
|
| Chinese | 87.87(11.11) | 561 | −.234 | .241 | .344 | .305 | 1.00 | |
| Math | 88.80(11.67) | 561 | −.200 | .242 | .391 | .375 | .511 | 1.00 | |
| English | 89.58(13.22) | 562 | −.207 | .153 | .334 | .294 | .666 | .696 |
p<.05;
p<.01,
p<.001.
Number of children differs across sample characteristics due to missing values.
Figure 1FIQ, VIQ, and PIQ test scores by blood lead concentration (µg/dl) with estimated 95% confidence bands.
Note: The dotted line's y-intercept is at the mean IQ test score.
Mean IQ and 2009 school performance by blood concentrations of lead in preschool children.
| Blood concentrations of lead (µg/dL) | ANOVA | Post-hoc analysis, LSD (p) | ||||||
| <8 (A) | 8- <10(B) | ≥10 (C) | F | p | A vs. B | A vs. C | B vs. C | |
|
| N = 1016 | N = 182 | N = 103 | |||||
| PIQ | 104.46(14.93) | 103.32(15.58) | 100.75(16.03) | 3.04 | .048 | .349 | .018 | .168 |
| VIQ | 104.23(14.80) | 103.65(15.03) | 103.08(14.65) | 0.36 | .696 | .627 | .453 | .755 |
| FIQ | 104.55(14.36) | 103.66(14.22) | 101.86(15.25) | 1.78 | .169 | .442 | .072 | .313 |
|
| N = 421 | N = 79 | N = 49 | |||||
| Chinese | 89.33(9.20) | 83.44(13.97) | 82.12(16.67) | 17.30 | .000 | .000 | <.001 | .503 |
| Math | 90.32(9.20) | 84.29(14.66) | 83.04(19.42) | 16.32 | .000 | .000 | <.001 | .545 |
| English | 91.29(10.41) | 84.16(18.10) | 83.37(19.71) | 16.59 | .000 | .000 | <.001 | .732 |
Impact of blood concentrations of lead on IQ and school performance in Chinese preschool children (n = 1341).
| Blood concentrations of lead (µg/dL) | |||
| <8.0 | 8.0 – <10.0 | ≥10.0 | |
|
| |||
|
|
| −0.96 (−3.28, 1.36) | −1.90 (−4.89, 1.09) |
|
|
| −0.48 (−3.36, 2.40) | −1.77 (−4.01, 0.46) |
|
|
| −1.28 (−4.01, 1.46) | −1.45 (−3.50, 0.67) |
|
| |||
|
|
| −3.20 (−5.78, −0.63) | −4.02 (−7.11, −0.93) |
|
|
| −2.67 (−5.16, 0.18) | −3.60 (−6.58, −0.62) |
|
|
| −5.25 (−8.14, −2.36) | −5.27(−8.73, −1,81) |
|
|
| −4.46(−7.20, −1.72) | −4.64(−7.91, −1.36) |
|
|
| −4.33 (−7.32, −1.34) | −5.18 (−8.76, −1.59) |
|
|
| −3.62 (−6., −0.75) | −4.62 (−8.05, −1.18) |
p<.05,
p<.01.
Model 1: Adjusting for age at blood lead test, sex, blood iron, school, father's education, mother's education, father's occupation and smoking.
Model 2: Adjusting covariates in model 1 plus PIQ.