Exploring the Association Between Exposure to Organochlorine Pesticides and Hearing Loss in American Adults

0

Study design and population

The NHANES is a national, cross-sectional, representative series of surveys containing information about the health of the general population of the United States. These ongoing surveys consist of interviews, physical measurements and laboratory tests on a selected sample of the non-institutionalized American population. The NHANES project was reviewed and approved by the National Center for Health Statistics Research Ethics Review Board, and informed consent was obtained from all participants. NHANES data and related documentation and protocols described in detail are publicly available on the NHANES website (https://www.cdc.gov/nchs/nhanes/Index.htm).

Participants in this report were recruited from the 2003-2004 NHANES cycle, which contains results of serum OCP concentrations and audiometric examinations of adults 20-69 years of age. Because analytical detection limits for serum OCPs varied widely in previous cycles and sample sizes from recent cycles were quite small, only data from the 2003-2004 cycle were used in our analysis. Figure 1 shows a flowchart for selecting participants for this study. Participants with missing data on hearing thresholds, otoscopic tests, tympanogram tests, or lipid-adjusted serum concentrations of selected OCPs were excluded. Individuals with abnormal otoscopic findings, poor quality tympanogram results, or tympanograms with ≤0.3 mL compliance were also excluded to avoid analyzing conductive or mixed LH data24.25. Finally, 366 participants were included in this study.

Figure 1

Participant selection flowchart. Abbreviations: p, p’-DDE, p, p’-dichlorodiphenyldichloroethylene.

Measurement of exposure to OCPs

Serum blood concentrations of 13 OCPs and metabolites were measured in a random one-third subsample of participants aged 12 years and older using high-resolution gas chromatography/high-resolution mass spectrometry at isotope dilution at the US Centers for Disease Control and Prevention (CDC). ) National Center for Environmental Health. Four OCPs detected in ≥ 80% of the samples were selected for analysis in our study: HCB, p, p’-DDE, trans-nonachlor and dieldrin. We used the limit of detection (LOD) divided by the square root of two for any sample below the LOD. Additionally, lipid-adjusted serum concentrations (ng/g lipid) of the four OCPs were used in our study and log-transformed to normalize for the skewed distribution prior to analysis.

Audiometric measurement

The detailed procedure and audiometric examination protocol has been described in the online NHANES Audiometry Procedures Manual26 and previous articles27.28. Briefly, half of the sample of US adults aged 20-69 underwent audiometric component testing. Trained examiners conducted hearing threshold examinations in a quiet, soundproof audiometry room. The examination of the hearing threshold was carried out at seven frequencies from 500 to 8000 Hz using an AD226 audiometer (Interacoustics). In this study, low-frequency HL was defined as PTA calculated by averaging the thresholds at 500, 1000, and 2000 Hz ≥ 20 dB HL in the better ear; speech frequency HL has been defined as PTA at 500, 1000, 2000, and 4000 Hz ≥ 20 dB HL in the better ear, which is consistent with the definition used by the World Health Organization1; and high-frequency HL was defined as PTA at 4000, 6000, and 8000 Hz ≥ 20 dB HL in the better ear.

Otoscopic examination of both ears was performed using a Welch Allyn otoscope (model 25020). Tympanometry was performed using an Earscan Acoustic Impedance tympanometer (Micro Audiometrics) to assess middle ear function. Inference of sensorineural HL was based on the results of normal otoscopic examinations and on results of good or adequate quality of the tympanogram with a compliance > 0.3 ml. Individuals who did not meet the standards were excluded from further analysis.

Covariates

The following variables were considered as potential covariates in the analysis: age and BMI as continuous variables, and sex, race/ethnicity, education level, BMI (categorical), diabetes, hypertension, serum cotinine level, gunshot exposure, and noise/noise/music exposure as categorical variables. Information on demographic variables, noise exposure, and current medical conditions, such as diabetes and hypertension, were obtained from self-reported questionnaires. Firearm exposure was defined as “exposure to gunshot noise outside of work for an average of at least once a month for one year”29. Exposure to loud noise/music was defined as “exposure to other types of loud noise, such as noise from power tools or loud music, outside of work, on average at least once a months for a year. Diabetes was defined by a ‘yes’ or ‘borderline’ response to the question ‘other than during pregnancy, have you been told by a doctor or health care professional that they have diabetes or diabetes mellitus’.30. Hypertension was defined as “a doctor or other healthcare professional has ever told you that they have high blood pressure, also called high blood pressure.”30. BMI was obtained by physical examination. Serum cotinine, a marker of active and passive tobacco exposure, was tested by isotope dilution-high performance liquid chromatography/atmospheric pressure tandem mass spectrometry31.

statistical analyzes

Weighted statistical differences in demographic and potential hearing-related variables between individuals grouped by sex were assessed, with categorical data presented as percentages and continuous data as the mean ± SD. The P continuous and categorical data values ​​were estimated using a weighted linear regression model and a weighted chi-square test, respectively. We distributed log-transformed lipid-adjusted OCP levels to tertiles before performing univariate analysis to estimate potential variables. Multivariate linear regression analysis was used to determine regression coefficients (β) and 95% CIs between the four OCPs and hearing threshold changes, and multivariate logistic regression analysis was used to estimate ORs and 95% CIs between the four OCPs and HL, adjusting for age. , gender, race/ethnicity, education level, BMI (categorical), diabetes, hypertension, serum cotinine level, exposure to gunshot sound and exposure to loud noise/music, instead of using sampling weight. This adjustment is considered to be a good compromise between efficiency and bias32.33. We assessed the influence of interactions between OCPs and age on HL. Stratified multivariate linear and logistic regression analyzes by age (P– value

Share.

Comments are closed.