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[Sampling methods and errors appearing in the China National Human Biomonitoring Program].

Z J Cao1, Y L Qu, F Zhao

  • 1Department of Environmental Epidemiology, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.

Zhonghua Liu Xing Bing Xue Za Zhi = Zhonghua Liuxingbingxue Zazhi
|December 21, 2018
PubMed
Summary
This summary is machine-generated.

The China National Human Biomonitoring Program (HBP) uses a multistage sampling method. While precise in Guizhou, it requires further study to address non-sampling errors in large-scale public health monitoring.

Keywords:
Human biomonitoringMultistage samplingSampling error

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Area of Science:

  • Environmental Health
  • Public Health Surveillance
  • Biomonitoring

Background:

  • The China National Human Biomonitoring Program (HBP) is crucial for assessing population exposure to environmental contaminants.
  • Evaluating the accuracy and efficiency of HBP's sampling methodology is essential for reliable health data.
  • Understanding sampling errors is key to interpreting biomonitoring results.

Purpose of the Study:

  • To analyze the sampling methodology employed in the China National Human Biomonitoring Program (HBP).
  • To identify and quantify sampling errors within the HBP framework.
  • To assess the overall study design concerning sampling procedures.

Main Methods:

  • Utilized a multistage sampling approach for the HBP.
  • Applied multistage unequal probability sampling error calculations.
  • Analyzed sampling data from Guizhou province as a case study, calculating sampling error and coefficient of variation.

Main Results:

  • The HBP involved 152 sites and 21,888 residents across 31 provinces.
  • Replacement rates at different sampling stages were 5.26%, 6.35%, and 40.6%.
  • Guizhou province exhibited a sampling error of 3,207,594 with a coefficient of variation of 0.097.

Conclusions:

  • The multistage unequal probability sampling method demonstrated high precision with low variability in Guizhou.
  • The current method overlooks the adjustment for non-sampling errors like missing population data and response rates.
  • Further research is needed on calculating multistage sampling errors for large public health monitoring initiatives.