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Biomonitoring of chromium for residents of areas with a high density of electroplating factories

A Corrigendum to this article was published on 18 April 2008

Abstract

The high density of electroplating factories in the geographic middle of Taiwan has prompted concern over the potential for exposure to harmful metals. The present study aimed to determine the levels of chromium in whole blood (B-Cr) of residents living in the high vs. low factory-density areas, and to examine the relations to gender and age. A total of 660 residents who had not moved within the 5 years preceding the study were sampled according to the stratified random sampling approach, at ages 35–44, 45–54, and 55–64 years, for both genders. Chromium determinations (n=641) were made using a graphite furnace atomic absorption spectrometer. The geometric mean (95% C.I.) of B-Cr was 0.357 (0.34–0.38) μg/l. The International Federation of Clinical Chemistry (IFCC) nonparametric 0.95 reference limits of B-Cr was estimated to be <0.905 μg/l. B-Cr levels decreased with increasing age. Subjects in the areas with a high density (0.38 μg/l, 95% C.I.: 0.36–0.40) of electroplating factories had significantly higher B-Cr levels, compared to residents of the low-density (0.27, 0.25–0.30) areas and to the general population from western countries. The health significance of the elevated B-Cr remains to be determined.

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Acknowledgements

The financial support (No. DOH91-TD-B04) of Department of Health of the Republic of China is gratefully acknowledged. We thank the Changhua population for support and participation in this study. We thank Dr. S. H. Liou and Dennis P. H. Hsieh of the Division of Environmental Health and Occupational Medicine, National Health Research Institutes (Taiwan), for their valuable suggestions. We are highly indebted to the Changhua Christian Hospital, the Changhua Public Health Bureau and the public health nurses, and the Changhua Environmental Protection Bureau for their support. We thank Y.C. Wang, C.Y. Peng, C.J. Li and H.Y. Yu for their valuable assistance in collecting the samples, and to H.J. Wang for her technical assistance in analytical work.

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Correspondence to Shu-Li Wang.

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The scientific content of this manuscript has been reviewed and approved for publication by the Division of Environmental Health and Occupational Medicine of the National Health Research Institutes. Approval for publication does not necessarily signify that the content reflects the view and policies of the DEHOM/NHRI, or condemnation or endorsement and recommendation for use on this issue presented.

Appendix A

Appendix A

  1. 1

    According to our sample collection protocol, collect whole blood from 5 to 10 nonexposed healthy persons and mix the bloods collected.

  2. 2

    Take seven aliquots from the above whole blood mixture. Add chromium stock solution into each aliquot to prepare seven samples at the same concentration near one-fifth of the lowest-concentration calibration standard.

  3. 3

    Pretreat the seven samples and analyze them according to the standard operation procedure, which is the same as used for subject’s specimens.

  4. 4

    Calculate the standard deviation (Sα) of the seven readings.

  5. 5

    Take another seven aliquots from the above whole blood mixture. Add chromium stock solution into each aliquot to prepare seven samples at the same concentration of half of the last additive concentration. Repeat Steps 3 and 4 and calculate another SD (Sβ).

  6. 6

    Use F-test to evaluate the two SDs (let S1 and S2 be the larger and smaller ones between Sα and Sβ). If

    is less than 3.05, then use the following equation to calculate the pooled standard deviation, Spooled.

  7. 7

    If in Step 6 F is not less than 3.05, then repeat Steps 5 and 6 until F is less than 3.05.

  8. 8

    Method detection limit (MDL) = 2.681 Spooled/a. „a” is the slope of the calibration curve.

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Chang, FH., Wang, SL., Huang, YL. et al. Biomonitoring of chromium for residents of areas with a high density of electroplating factories. J Expo Sci Environ Epidemiol 16, 138–146 (2006). https://doi.org/10.1038/sj.jea.7500445

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