title: Blood lead levels and associated sociodemographic factors among preschool children in the South Eastern region of China.
abstract: Children are especially vulnerable to lead toxicity, and exposure to lead has been linked to poor school performance and delinquency in children and adolescents. Even low-level lead exposure [blood lead level (BLL) <10 µg/dL] can cause intellectual deficit. In China, BLLs in children decreased slightly after the phasing out of lead in gasoline, but few studies have examined the sociodemographic factors associated with BLL above 10 µg/dL. In this study, we sought to examine the hypothesis that sociodemographic factors predict BLLs. We measured BLLs of 1344 preschool children (3-5 years old) from the China Jintan Child Cohort Study. Children's sociodemographic and health statuses, as well as parental sociodemographic data, were collected using questionnaires. Regression models were used to explore the association between sociodemographic factors and log-transformed BLLs as well as the relationship between sociodemographic factors and the risk of BLL ≥10 µg/dL. We found the median BLL to be 6.2 µg/dL (range: 1.8-32.0 µg/dL); 8% of children had BLLs ≥10 µg/dL. Boys had a higher median BLL (6.4 µg/dL) than girls and were more likely to have BLL ≥10 µg/dL [odds ratio = 1.77, 95% confidence interval 1.14, 2.74]. BLLs increased as children aged, with a median BLL of 6.6 µg/dL among 5-year-old children. Children with siblings had a higher average BLL and greater prevalence of a BLL ≥10 µg/dL than those without siblings. Living in a crowded neighbourhood was also associated with increased BLLs. Mother's lower education, father's occupation (as professional worker) and parental smoking at home were associated with increased BLLs. This study shows that children in this area still have relatively high BLLs even after the phasing out of leaded gasoline. Both children's and parental factors and community condition are associated with increased BLLs. Future efforts are needed to identify other sources of exposure and develop targeted prevention strategies.
authors.affiliation: School of Nursing, University of Pennsylvania, Philadelphia 19104-6096, USA. jhliu@nursing.upenn.edu
authors.forename: Jianghong
authors.initials: J
authors.lastname: Liu
authors.forename: Yuexian
authors.initials: Y
authors.lastname: Ai
authors.forename: Linda
authors.initials: L
authors.lastname: McCauley
authors.forename: Jennifer
authors.initials: J
authors.lastname: Pinto-Martin
authors.forename: Chonghuai
authors.initials: C
authors.lastname: Yan
authors.forename: Xiaoming
authors.initials: X
authors.lastname: Shen
authors.forename: Herbert
authors.initials: H
authors.lastname: Needleman
mesh_terms: D000293:Adolescent; D000328:Adult; D002675:Child, Preschool; D002681:China / Q000453:epidemiology; D015331:Cohort Studies; D004781:Environmental Exposure / Q000009:adverse effects*; D005260:Female; D006801:Humans; D007854:Lead / Q000097:blood*; D007855:Lead Poisoning / Q000453:epidemiology* / Q000209:etiology; D008297:Male; D012044:Regression Analysis; D012307:Risk Factors; D012959:Socioeconomic Factors; D055815:Young Adult
chemical_list: D007854:Lead