• Component Description
• Eligible Sample
• Description of Laboratory Methodology
• Laboratory Quality Assurance and Monitoring
• Data Processing and Editing
• Analytic Notes
• References
• Codebook
  • SEQN - Respondent sequence number
  • WTSSBI2Y - Surplus specimen B 15-16 2 year weights
  • SSIMID - Imidacloprid (ug/L)
  • SSIMIDLC - Imidacloprid (ug/L) Cmt code
  • SSACET - Acetamiprid (ug/L)
  • SSACETLC - Acetamiprid (ug/L) Cmt code
  • SSCLOT - Clothianidin (ug/L)
  • SSCLOTLC - Clothianidin (ug/L) Cmt code
  • SSTHIA - Thiacloprid (ug/L)
  • SSTHIALC - Thiacloprid (ug/L) Cmt code
  • SSOHIM - 5-Hydroxyimidacloprid (ug/L)
  • SSOHIMLC - 5-Hydroxyimidacloprid (ug/L)Cmt code
  • SSAND - N-Desmethylacetamiprid (ug/L)
  • SSANDLC - N-Desmethylacetamiprid (ug/L) Cmt code

National Health and Nutrition Examination Survey

2015-2016 Data Documentation, Codebook, and Frequencies

Neonicotinoids - Urine - Surplus (SSNEON_I)

Data File: SSNEON_I.xpt

First Published: January 2019

Last Revised: April 2022

Component Description

Neonicotinoids  are a class of insecticides used in growing genetically-modified corn, soybeans, cotton, sunflowers, and canola, as well as various other genetically-modified and non-genetically-modified vegetables and fruits (Cimino et al. 2017). Approximately 90% of the corn and 50% of the soybeans planted in the USA have been treated with neonicotinoids (Douglas 2015). Neonicotinoid insecticides are also used in lawn treatment and in pet collars (Tomizawa 2005).

The neonicotinoid family includes acetamiprid, clothianidin, imidacloprid, nitenpyram, nithiazine, thiacloprid and thiamethoxam; imidacloprid is the world’s single most widely applied insecticide. Neonics have neurotoxic action on the nicotinic acetylcholine receptor; neonicotinoids have received increased scrutiny because they may adversely affect pollinators and are linked to colony collapse disorder in bees (Hladik et al. 2014) and the decline of insectivorous birds (Hallmann, 2014). Additionally, neonicotinoids are persistent in the environment and have been detected in streams and food, among other environmental matrices (Chen et al. 2014, Hladik et al. 2014). For example, multiple neonicotinoids were detected in 72% of fruits and 45% of vegetables procured in 2012 from Boston neighborhood grocery stores, with imidacloprid present in about 70% of fruits and vegetables (Chen et al. 2014).

To better understand exposure to some of the most commonly used neonicotinoids we  measured Imidacloprid, 5-Hydroxy imidacloprid, Acetamiprid, N-desmethyl Acetamiprid, Clothianidin and Thiacloprid in one third subsample of participants 3+ years of age from NHANES 2015-2016. 

Eligible Sample

All participants aged 3-5 years old and an one-third sample of participants aged 6 and older from NHANES 2015-2016 with stored urine.

Description of Laboratory Methodology

The method uses 0.2 mL urine and is based on enzymatic hydrolysis of urinary conjugates of the target analytes, online solid phase extraction, reversed phase high-performance liquid chromatography separation, and isotope dilution-electrospray ionization tandem mass spectrometry detection (Baker 2018, in preparation).

Laboratory Quality Assurance and Monitoring

The analytical measurements were conducted following strict quality control/quality assurance CLIA guidelines. Along with the study samples, each analytical run included high- and low-concentration quality control materials (QCs) and reagent blanks to assure the accuracy and reliability of the data. The concentrations of the high-concentration QCs and the low-concentration QCs, averaged to obtain one measurement of high-concentration QC and low-concentration QC for each run, were evaluated using standard statistical probability rules (Caudill et al. 2008).

Data Processing and Editing

Data were received after all analyses were complete. The data were not edited.    

Data Access: All data are publicly available.

Analytic Notes

Detection Limits

The detection limits were constant for all of the analytes in the data set. Two variables are provided for each analyte. The variable name ending in “L” (ex., SSECBAL) indicates whether the result was below the limit of detection: the value “0” means that the result was at or above the limit of detection, “1” indicates that the result was below the limit of detection. For analytes with analytic results below the limit of detection (ex.,SSECBAL=1), an imputed fill value was placed in the analyte results field. This value is the limit of detection divided by square root of 2 (LOD/√2). The other variable prefixed SS (ex., SSECBA) provides the analytic result for that analyte.

The limit of detection (LOD, in µg/L) for IMID, ACET, CLOT, THIA, OHIM, and AND:

 

Interferences:

Blanks in an analyte results field represent missing values in cases when the presence of interferences precluded obtaining a valid numeric result for a given analyte.

Subsample Weights

Sample weights are required to analyze these data properly. Specific sample weights for this subsample are included in this data file and should be used when analyzing these data. Previous versions of this dataset included a sample weight variable (WTSB2YR) but when observations were removed from this data file, a new sample weight was created, and a new sample weight variable was added to this data file (WTSSBI2Y). Please refer to the NHANES Analytic Guidelines and the on-line NHANES Tutorial for further details on the use of sample weights and other analytic issues.

References

• Baker SE, Bishop Serafim A, Morales-Agudelo P, Vidal M, Ospina M, and Calafat AM. Quantification of DEET and Neonicotinoid Pesticide Biomarkers in Human Urine by Online Solid Phase Extraction-High Performance Liquid Chromatography-Tandem Mass Spectrometry-Manuscript in Preparation.
• Caudill SP, Schleicher RL, Pirkle JL. 2008. Multi-rule quality control for the age-related eye disease study. Statist Med 27: 4094-4106.
• Chen M, Tao L, McLean J. and Lu C. Quantitative Analysis of Neonicotinoid Insecticide Residues in Foods: Implication for Dietary Exposures J. Agric. Food Chem. 2014, 62, 6082−6090.
• Cimino AM, Boyles AL, Thayer KA, Perry MJ. 2017. Effects of Neonicotinoid Pesticide Exposure on Human Health: A Systematic Review. Environ Health Perspect 125:155-162
• Douglas MR and Tooker JF. (2015) Large-Scale Deployment of Seed Treatments Has Driven Rapid Increase in Use of Neonicotinoid Insecticides and Preemptive Pest Management in U.S. Field Crops. Environ. Sci. Technol. 49, 5088−5097.
• Hallmann CA, Foppen RP, van Turnhout CA, de Kroon H, Jongejans E. 2014. Declines in insectivorous birds are associated with high neonicotinoid concentrations. Nature, 511, (7509), 341-343.
• Hladik ML, Kolpin DW, Kuivila KM. 2014. Widespread occurrence of neonicotinoid insecticides in streams in a high corn and soybean producing region, USA. Environ Pollut 193:189-196.
• Tomizawa, M and Casida JE. 2005. Neonicotinoid Insecticide Toxicology: Mechanisms of Selective Action Annu. Rev. Pharmacol. Toxicol. 2005. 45:247–68.

Codebook and Frequencies