title: Associations of lead biomarkers with renal function in Korean lead workers.
abstract: OBJECTIVE
  To compare associations of lead biomarkers with renal function in current and former lead workers.
  
  
  METHODS
  Cross sectional analysis of first year results from a longitudinal study of 803 lead workers and 135 controls in South Korea. Clinical renal function was assessed by blood urea nitrogen (BUN), serum creatinine, and measured and calculated creatinine clearance. Urinary N-acetyl-beta-D-glucosaminidase (NAG) and retinol-binding protein were also measured.
  
  
  RESULTS
  Mean (SD) tibia lead, blood lead, and DMSA chelatable lead levels in lead workers were 37.2 (40.4) micro g/g bone mineral, 32.0 (15.0) micro g/dl, and 767.8 (862.1) micro g/g creatinine, respectively. Higher lead measures were associated with worse renal function in 16/42 models. When influential outliers were removed, higher lead measures remained associated with worse renal function in nine models. An additional five associations were in the opposite direction. Effect modification by age was observed. In 3/16 models, associations between higher lead measures and worse clinical renal function in participants in the oldest age tertile were significantly different from associations in those in the youngest age tertile which were in the opposite direction. Mean urinary cadmium (CdU) was 1.1 micro g/g creatinine (n = 191). Higher CdU levels were associated with higher NAG.
  
  
  CONCLUSIONS
  These data suggest that lead has an adverse effect on renal function in the moderate dose range, particularly in older workers. Associations between higher lead measures and lower BUN and serum creatinine and higher creatinine clearances may represent lead induced hyperfiltration. Environmental cadmium may also have an adverse renal impact, at least on NAG.
authors.affiliation: Division of Occupational and Environmental Health, Department of Environmental Health Sciences, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.
authors.forename: V M
authors.initials: VM
authors.lastname: Weaver
authors.forename: B-K
authors.initials: BK
authors.lastname: Lee
authors.forename: K-D
authors.initials: KD
authors.lastname: Ahn
authors.forename: G-S
authors.initials: GS
authors.lastname: Lee
authors.forename: A C
authors.initials: AC
authors.lastname: Todd
authors.forename: W F
authors.initials: WF
authors.lastname: Stewart
authors.forename: J
authors.initials: J
authors.lastname: Wen
authors.forename: D J
authors.initials: DJ
authors.lastname: Simon
authors.forename: P J
authors.initials: PJ
authors.lastname: Parsons
authors.forename: B S
authors.initials: BS
authors.lastname: Schwartz
mesh_terms: D000293:Adolescent; D000328:Adult; D015415:Biomarkers / Q000097:blood / Q000652:urine; D002104:Cadmium / Q000009:adverse effects; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D007674:Kidney Diseases / Q000097:blood / Q000139:chemically induced* / Q000652:urine; D007723:Korea / Q000453:epidemiology; D007854:Lead / Q000009:adverse effects / Q000378:metabolism*; D016014:Linear Models; D008137:Longitudinal Studies; D008297:Male; D008669:Metallurgy; D008875:Middle Aged; D016273:Occupational Exposure / Q000009:adverse effects*
chemical_list: D015415:Biomarkers; D002104:Cadmium; D007854:Lead