A pilot study on psychosocial factors and perceptions of organizational health among a sample of U.S. waste workers.

Solid waste workers encounter a number of occupational hazards that are likely to induce stress. Thus, there are likely to be psychosocial factors that also contribute to their overall perceptions of organizational health. However, attitudes regarding the aforementioned among solid waste workers' have not been assessed. This descriptive, cross-sectional pilot study operationalized the INPUTS Survey to determine workers' perceptions of organizational health and other psychosocial factors of work. Percentage and mean responses to each INPUTS domain are presented in accordance with their survey manual. Pearson's chi-squared tests were run on count data; Fisher's exact tests were run for count data with fewer than five samples. ANOVAs were run on the continuous items. Due to a relatively low sample size (N = 68), two-sided p values < 0.1 were considered statistically significant. Most solid waste worker participants reported high decision authority, that they perceived their management to prioritize workplace health and safety, and had high job satisfaction. However, perceptions of support for health outside of the realm of occupational safety and health was lower. Addressing traditional occupational health hazards continues to take precedence in this industry, with less of a focus on how the social determinants of health may impact workplace health.

Risk perception or hazard perception? Examining misperceptions of miners' personal exposures to noise.

While perceptions of risk have been examined in the workplace to understand safety behavior, hazard perception has been overlooked, particularly for chemical, physical, and biological agents. This study sought to establish the prevalence of one type of mismatch in hazard perception, - noise misperception - among miners, to examine whether different types of noisy environments (e.g., continuous, highly variable, etc.) alter workers' misperception of their noise exposures, and to evaluate whether noise misperception is associated with hearing protection device (HPD) use behavior. In this cross-sectional study across 10 surface mines in the USA, 135 normal-hearing participants were surveyed on their perceptions of exposure to noise at work and were monitored for three shifts, each with personal noise dosimetry, to examine which workers had a mismatch in perceived versus true noise exposure by 8-hr, time-weighted average, NIOSH exposure limits (TWANIOSH). Mixed effects logistic regression and probit Bayesian Kernel Machine Regression (BKMR) models examining on the odds of noise misperception associated with four different noise metrics (kurtosis, crest factor, variability, and number of peaks >135 dB) were used to determine which types of noisy environments may influence noise misperception. The relationship between noise misperception and odds of not wearing HPDs during a work shift was further examined. Our findings showed that nearly 1 in 3 workers underestimated their exposure to noise when their true exposure was in fact hazardous (TWANIOSH≥85 dBA) for at least one shift, and 6% misperceived hazardous exposures for all shifts. Work shifts with highly kurtotic noise distributions (>3) had 3.1 (95% CI: 1.1 to 8.4) times significantly higher odds of resulting in misperceived noise; no other noise metric was significantly associated with noise misperception. BKMR modeling provided further evidence that kurtosis dominates this relationship, with an IQR increase in kurtosis significantly associated with 1.68 (95% CI: 1.13 to 2.50) higher odds of noise misperception. Although not statistically significant, misperception of hazardous noise exposure was associated with 3.2 (95% CI: 0.8 to 12.5) times higher odds of not using earplugs during a work shift. Misperception of noise occurs in the workplace, and likely occurs for other physical, chemical, and biological exposures. This hazard misperception may influence risk perceptions and worker behavior and reduce the effectiveness of behavior-related training. Elimination, substitution, or engineering controls of exposures is the best way to prevent hazard misperceptions and exposure-related diseases.

Occupational exposure to noise and dust in Swedish soft paper mills and mortality from ischemic heart disease and ischemic stroke: a cohort study.

OBJECTIVE: To elucidate whether occupational noise exposure increases the mortality from ischemic heart disease (IHD) and stroke, and if exposure to paper dust modified the risks. METHODS: We studied 6686 workers from soft paper mills, with occupational noise exposure, < 85 dBA, 85-90 dBA and > 90 dBA, and high (> 5 mg/m3) exposure to paper dust. Person-years 1960-2019 were stratified according to gender, age, and calendar-year. Expected numbers of deaths were calculated using the Swedish population as the reference and standardized mortality ratios (SMR) with 95% confidence intervals (95% CI) were assessed. RESULTS: SMR for IHD was 1.12 (95% CI 0.88-1.41) for noise < 85 dBA, 1.18 (95% CI 0.90-1.55) for 85-90 dBA, and 1.27 (95% CI 1.10-1.47) among workers exposed > 90 dBA. Joint exposure to high noise exposure and high exposure to paper dust resulted in slightly higher IHD mortality (SMR 1.39, 95% CI 1.15-1.67). SMR for ischemic stroke was 0.90 (95% CI 0.37-2.15) for noise < 85 dBA, 1.08 (95% CI 0.45-2.59) for 85-90 dBA, and 1.48 (95% CI 0.99-2.00) among workers exposed > 90 dBA. High noise exposure and high exposure to paper dust resulted in higher ischemic stroke mortality (SMR 1.83, 95% CI 1.12-2.98). CONCLUSION: Noise levels > 90 dBA was associated with increased IHD mortality. Combined exposures of noise and paper dust may further increase the risks. Our results do not provide support for a causal relationship for ischemic stroke. Residual confounding from smoking has to be considered. Workers need to be protected from occupational noise levels exceeding 90 dBA.

Cancer incidence among workers in soft paper mills: A cohort study.

OBJECTIVES: To elucidate whether occupational exposure to soft paper dust increases the incidence of cancer. METHODS: We studied 7988 workers in Swedish soft paper mills from 1960 to 2008, of whom 3233 (2 187 men and 1046 women) had more than 10 years of employment. They were divided into high exposure (>5 mg/m3 for >1 year) or lower exposure to soft paper dust based on a validated job-exposure matrix. They were followed from 1960 to 2019, and person-years at risk were stratified according to gender, age, and calendar-year. The expected numbers of incident tumors were calculated using the Swedish population as the reference, and standardized incidence ratios (SIR) with 95% confidence intervals (95% CI) were assessed. RESULTS: Among high-exposure workers with more than 10 years of employment, there was an increased incidence of colon cancer (SIR 1.66, 95% CI 1.20-2.31), small intestine cancer (SIR 3.27, 95% CI 1.36-7.86), and thyroid gland cancer (SIR 2.68, 95% CI 1.11-6.43), as well as lung cancer (SIR 1.56, 95% CI 1.12-2.19). Among the lower-exposed workers there was an increased incidence of connective tissue tumors (sarcomas) (SIR 2.26, 95% CI 1.13-4.51) and pleural mesothelioma (SIR 3.29, 95% CI 1.37-7.91). CONCLUSION: Workers in soft paper mills with high exposure to soft paper dust have an increased incidence of large and small intestine tumors. Whether the increased risk is caused by paper dust exposure or some unknown associated factors is unclear. The increased incidence of pleural mesothelioma is probably linked to asbestos exposure. The reason for increased incidence of sarcomas is unknown.

Associations between Poorer Mental Health with Work-Related Effort, Reward, and Overcommitment among a Sample of Formal US Solid Waste Workers during the COVID-19 Pandemic.

Background: Effort-reward imbalance (ERI) and overcommitment at work have been associated poorer mental health. However, nonlinear and nonadditive effects have not been investigated previously. Methods: The association between effort, reward, and overcommitment with odds of poorer mental health was examined among a sample of 68 formal United States waste workers (87% male). Traditional, logistic regression and Bayesian Kernel machine regression (BKMR) modeling was conducted. Models controlled for age, education level, race, gender, union status, and physical health status. Results: The traditional, logistic regression found only overcommitment was significantly associated with poorer mental health (IQR increase: OR = 6.7; 95% CI: 1.7 to 25.5) when controlling for effort and reward (or ERI alone). Results from the BKMR showed that a simultaneous IQR increase in higher effort, lower reward, and higher overcommitment was associated with 6.6 (95% CI: 1.7 to 33.4) times significantly higher odds of poorer mental health. An IQR increase in overcommitment was associated with 5.6 (95% CI: 1.6 to 24.9) times significantly higher odds of poorer mental health when controlling for effort and reward. Higher effort and lower reward at work may not always be associated with poorer mental health but rather they may have an inverse, U-shaped relationship with mental health. No interaction between effort, reward, or overcommitment was observed. Conclusion: When taking into the consideration the relationship between effort, reward, and overcommitment, overcommitment may be most indicative of poorer mental health. Organizations should assess their workers' perceptions of overcommitment to target potential areas of improvement to enhance mental health outcomes.

Characterization of perceived biohazard exposures, personal protective equipment, and training resources among a sample of formal U.S. solid waste workers: A pilot study.

In the United States, the majority of waste workers work with solid waste. In solid waste operations, collection, sorting, and disposal can lead to elevated biohazard exposures (e.g., bioaerosols, bloodborne and other pathogens, human and animal excreta). This cross-sectional pilot study aimed to characterize solid waste worker perception of biohazard exposures, as well as worker preparedness and available resources (e.g., access to personal protective equipment, level of training) to address potential biohazard exposures. Three sites were surveyed: (1) a family-owned, small-scale waste disposal facility, (2) a county-level, recycling-only facility, and (3) an industrial-sized, large-scale facility that contains a hauling and landfill division. Survey items characterized occupational biohazards, resources to mitigate and manage those biohazards, and worker perceptions of biohazard exposures. Descriptive statistics were generated. The majority of workers did not report regularly coming into contact with blood, feces, and bodily fluids (79%). As such, less than one-fifth were extremely concerned about potential illness from biological exposures (19%). Yet, most workers surveyed (71%) reported an accidental laceration/cut that would potentially expose workers to biohazards. This study highlights the need for additional research on knowledge of exposure pathways and perceptions of the severity of exposure among this occupational group.

Linking environmental injustices in Detroit, MI to institutional racial segregation through historical federal redlining.

OBJECTIVES: To identify the most pervasive environmental exposures driving environmental disparities today associated with historical redlining in Detroit. METHODS: We overlaid Detroit's 1939 Home Owners' Loan Corporation (HOLC) shapefile from the Mapping Inequality project onto the EPA EJScreen and the DOT National Transportation Noise maps to analyze differences in current demographic and environmental indicators between historically redlined (D-grade) and non-redlined neighborhoods using simple linear regression and a boosted classification tree algorithm. RESULTS: Historically redlined neighborhoods in Detroit experienced significantly higher environmental hazards than non-redlined neighborhoods in the form of 12.1% (95% CI: 7.2-17.1%) higher levels of diesel particulate matter (PM), 32.2% (95% CI: 3.3-69.3%) larger traffic volumes, and 65.7% (95% CI: 8.6-152.8%) higher exposure to hazardous road noise (LEQ(24h) >70 dBA). Historically redlined neighborhoods were situated near 1.7-times (95% CI: 1.4-2.1) more hazardous waste sites and twice as many (95% CI: 1.5-2.7) risk management plan (RMP) sites than non-redlined neighborhoods. The lifetime cancer risk from inhalation of air toxics was 4.4% (95% CI: 2.9-6.6%) higher in historically redlined communities, and the risk of adverse respiratory health outcomes from air toxics was 3.9% (95% CI: 2.1-5.6%) higher. All factors considered together, among the environmental hazards considered, the most pervasive hazards in historically redlined communities are proximity to RMP sites, hazardous road noise, diesel PM, and cancer risk from air pollution. CONCLUSIONS: Historically redlined neighborhoods may have a disproportionately higher risk of developing cancer and adverse respiratory health outcomes from air toxics. Policies targeting air and noise pollution from transportation sources, particularly from sources of diesel exhaust, in historically redlined neighborhoods may ameliorate some of the impacts of structural environmental racism from historical redlining in Detroit.

Evaluating Occupational Noise Exposure as a Contributor to Injury Risk among Miners.

OBJECTIVES: This study: (i) assessed the relationship between noise exposure and injury risk, comprehensively adjusting for individual factors, psychosocial stressors, and organizational influences; (ii) determined the relative importance of noise on injuries; (iii) estimated the lowest observed adverse effect level (LOAEL) of noise on injury risk to determine the threshold of noise considered hazardous to injuries; and (iv) quantified the fraction of injuries that could be attributed to hazardous noise exposure. METHODS: In this cross-sectional study at 10 US surface mine sites, traditional mixed effects, Poisson regression, and boosted regression tree (BRT) models were run on the number of reported work-related injuries in the last year. The LOAEL of noise on injuries was identified by estimating the percent increase in work-related injuries at different thresholds of noise exposure using a counterfactual estimator through the BRT model. A population attributable fraction (PAF) was quantified with this counterfactual estimator to predict reductions in injuries at the LOAEL. RESULTS: Among 18 predictors of work-related injuries, mine site, perceived job safety, age, and sleepiness were the most important predictors. Occupational noise exposure was the seventh most important predictor. The LOAEL of noise for work-related injuries was a full-shift exposure of 88 dBA. Exposure ≥88 dBA was attributed to 20.3% (95% CI: 11.2%, 29.3%) of reported work-related injuries in the last year among the participants. CONCLUSIONS: This study further supports hypotheses of a dose-response relationship between occupational noise exposure and work-related injuries, and suggests that exposures ≥88 dBA may increase injury risk in mining.

Effort-Reward Imbalance among a Sample of Formal US Solid Waste Workers.

Background: Solid waste workers are exposed to a plethora of occupational hazards and may also experience work-related stress. Our study had three specific hypotheses: (1) waste workers experience effort−reward imbalance (ERI) with high self-reported effort but low reward, (2) unionized workers experience greater ERI, and (3) workers with higher income have lower ERI. Methods: Waste workers from three solid waste sites in Michigan participated in this cross-sectional study. We characterized perceived work stress using the short-version ERI questionnaire. Descriptive statistics and linear tests for trend were assessed for each scale. Linear regression models were constructed to examine the relationship between structural factors of work stress and ERI. Gradient-boosted regression trees evaluated which factors of effort or reward best characterize workers' stress. Results: Among 68 participants, 37% of workers reported high effort and low reward from work (ERI > 1). Constant pressure due to heavy workload was most indicative of ERI among the solid waste workers. Union workers experienced 79% times higher ERI than non-unionized workers, while no significant differences were observed by income, after adjusting for confounders. Conclusions: Organizational-level interventions, such as changes related to workload, consideration of fair compensation, and increased support from supervisors, can decrease work stress.

Beware the Grizzlyman: A comparison of job- and industry-based noise exposure estimates using manual coding and the NIOSH NIOCCS machine learning algorithm.

Recently, the National Institute for Occupational Safety and Health (NIOSH) released an updated version of the NIOSH Industry and Occupation Computerized Coding System (NIOCCS), which uses supervised machine learning to assign industry and occupational codes based on provided free-text information. However, no efforts have been made to externally verify the quality of assigned industry and job titles when the algorithm is provided with inputs of varying quality. This study sought to evaluate whether the NIOCCS algorithm was sufficiently robust with low-quality inputs and how variable quality could impact subsequent job estimated exposures in a large job-exposure matrix for noise (NoiseJEM). Using free-text industry and job descriptions from >700,000 noise measurements in the NoiseJEM, three files were created and input into NIOCCS: (1) N1, "raw" industries and job titles; (2) N2, "refined" industries and "raw" job titles; and (3) N3, "refined" industries and job titles. Standardized industry and occupation codes were output by NIOCCS. Descriptive statistics of performance metrics (e.g., misclassification/discordance of occupation codes) were evaluated for each input relative to the original NoiseJEM dataset (N0). Across major Standardized Occupational Classifications (SOC), total discordance rates for N1, N2, and N3 compared to N0 were 53.6%, 42.3%, and 5.0%, respectively. The impact of discordance on the major SOC group varied and included both over- and under-estimates of average noise exposure compared to N0. N2 had the most accurate noise exposure estimates (i.e., smallest bias) across major SOC groups compared to N1 and N3. Further refinement of job titles in N3 showed little improvement. Some variation in classification efficacy was seen over time, particularly prior to 1985. Machine learning algorithms can systematically and consistently classify data but are highly dependent on the quality and amount of input data. The greatest benefit for an end-user may come from cleaning industry information before applying this method for job classification. Our results highlight the need for standardized classification methods that remain constant over time.

Noise exposure and mental workload: Evaluating the role of multiple noise exposure metrics among surface miners in the US Midwest.

This study examined associations between metrics of noise exposure and mental workload. In this cross-sectional study, five occupational noise metrics computed from full-shift dosimetry were evaluated among surface mine workers in the US Midwest. Mental workload was evaluated using a modified, raw NASA-TLX and clustered with a k-means clustering algorithm. Mixed effects logistic regression and Bayesian Kernel Machine Regression (BKMR) was utilized for analysis. Average noise exposure, the difference between peak and mean noise exposure, and the number of peaks >135 dB were each strongly associated with mental workload, while the kurtosis and standard deviation of noise throughout a shift were not. An exposure-response relationship between average noise exposure and mental workload may exist, with elevated risk of high mental workload beginning at 80 dBA. These results suggest that high noise exposure may be an independent risk factor of high mental workload, and impulse events and the difference between the peak and mean noise exposure may have interactive effects with average noise exposure.

Toward a better understanding of nonoccupational sound exposures and associated health impacts: Methods of the Apple Hearing Study.

Globally, noise exposure from occupational and nonoccupational sources is common, and, as a result, noise-induced hearing loss affects tens of millions of people. Occupational noise exposures have been studied and regulated for decades, but nonoccupational sound exposures are not well understood. The nationwide Apple Hearing Study, launched using the Apple research app in November 2019 (Apple Inc., Cupertino, CA), is characterizing the levels at which participants listen to headphone audio content, as well as their listening habits. This paper describes the methods of the study, which collects data from several types of hearing tests and uses the Apple Watch noise app to measure environmental sound levels and cardiovascular metrics. Participants, all of whom have consented to participate and share their data, have already contributed nearly 300 × 106 h of sound measurements and 200 000 hearing assessments. The preliminary results indicate that environmental sound levels have been higher, on average, than headphone audio, about 10% of the participants have a diagnosed hearing loss, and nearly 20% of the participants have hearing difficulty. The study's analyses will promote understanding of the overall exposures to sound and associated impacts on hearing and cardiovascular health. This study also demonstrates the feasibility of collecting clinically relevant exposure and health data outside of traditional research settings.

Monitoring SARS-CoV-2 in air and on surfaces and estimating infection risk in buildings and buses on a university campus.

BACKGROUND: Evidence is needed on the presence of SARS-CoV-2 in various types of environmental samples and on the estimated transmission risks in non-healthcare settings on campus. OBJECTIVES: The objective of this research was to collect data on SARS-CoV-2 viral load and to examine potential infection risks of people exposed to the virus in publicly accessible non-healthcare environments on a university campus. METHODS: Air and surface samples were collected using wetted wall cyclone bioaerosol samplers and swab kits, respectively, in a longitudinal environmental surveillance program from August 2020 until April 2021 on the University of Michigan Ann Arbor campus. Quantitative rRT-PCR with primers and probes targeting gene N1 were used for SARS-CoV-2 RNA quantification. The RNA concentrations were used to estimate the probability of infection by quantitative microbial risk assessment modeling and Monte-Carlo simulation. RESULTS: In total, 256 air samples and 517 surface samples were collected during the study period, among which positive rates were 1.6% and 1.4%, respectively. Point-biserial correlation showed that the total case number on campus was significantly higher in weeks with positive environmental samples than in non-positive weeks (p = 0.001). The estimated probability of infection was about 1 per 100 exposures to SARS-CoV-2-laden aerosols through inhalation and as high as 1 per 100,000 exposures from contacting contaminated surfaces in simulated scenarios. SIGNIFICANCE: Viral shedding was demonstrated by the detection of viral RNA in multiple air and surface samples on a university campus. The low overall positivity rate indicated that the risk of exposure to SARS-CoV-2 at monitored locations was low. Risk modeling results suggest that inhalation is the predominant route of exposure compared to surface contact, which emphasizes the importance of protecting individuals from airborne transmission of SARS-CoV-2 and potentially other respiratory infectious diseases. IMPACT: Given the reoccurring epidemics caused by highly infectious respiratory viruses in recent years, our manuscript reinforces the importance of monitoring environmental transmission by the simultaneous sampling and integration of multiple environmental surveillance matrices for modeling and risk assessment.

Retrospective assessment of the association between noise exposure and nonfatal and fatal injury rates among miners in the United States from 1983 to 2014.

BACKGROUND: Mining is a significant economic force in the United States but has historically had among the highest nonfatal injury rates across all industries. Several factors, including workplace hazards and psychosocial stressors, may increase injury and fatality risk. Mining is one of the noisiest industries; however, the association between injury risk and noise exposure has not been evaluated in this industry. In this ecological study, we assessed the association between noise exposure and nonfatal and fatal occupational injury rates among miners. METHODS: Federal US mining accident, injury, and illness data sets from 1983 to 2014 were combined with federal quarterly mining employment and production reports to quantify annual industry rates of nonfatal injuries and fatalities. An existing job-exposure matrix for occupational noise was used to estimate annual industry time-weighted average (TWA, dBA) exposures. Negative binomial models were used to assess relationships between noise, hearing conservation program (HCP) regulation changes in 2000, year, and mine type with incidence rates of injuries and fatalities. RESULTS: Noise, HCP regulation changes, and mine type were each independently associated with nonfatal injuries and fatalities. In multivariate analysis, each doubling (5 dB increase) of TWA was associated with 1.08 (95% confidence interval: 1.05, 1.11) and 1.48 (1.23, 1.78) times higher rate of nonfatal injuries and fatalities, respectively. HCP regulation changes were associated with 0.61 (0.54, 0.70) and 0.49 (0.34, 0.71) times lower nonfatal injury and fatality rates, respectively. CONCLUSION: Noise may be a significant independent risk factor for injuries and fatalities in mining.

Dust Exposures in Swedish Soft Tissue Paper Mills.

OBJECTIVES: Paper dust has previously been linked to adverse health effects. However, a comprehensive dataset of paper dust exposures does not appear to have been published previously. Our study was intended to address this need by describing a large dataset of measurements made in Swedish soft tissue paper mills. METHODS: We compiled personal and area total dust exposure measurements collected from a range of operations by our research staff at four soft tissue paper mills in Sweden. We also compiled measurements made by the occupational health staff at each mill and the Swedish Work Environment Authority. We analyzed these measurements to describe patterns and trends in exposures and used mixed-effects regression models to identify measurement characteristics that predicted exposure levels. RESULTS: We compiled 1578 measurements from 1971 to 2009, of which 1026 (65%) were personal samples. Statistically significant differences were found between measurements made by research, mill, and Swedish Work Environment Authority staff, as well as between personal and area measurements. The measurement data suggest that, beginning in the 1980s, exposures declined at three of the four mills, but that overexposures were still common at the end of the period. Papermaking and converting operations had the highest observed dust exposures. One mill had significantly lower exposures than the others. Type of measurement (personal versus area) and source of measurement (research staff, company, or regulatory agency) were not significant predictors of measured total dust exposure after controlling for mill, operation, and time. CONCLUSIONS: Our analysis of measured paper dust exposures may be useful for historical and contemporary exposure assessment in our own and other epidemiological studies. We have identified specific characteristics (i.e. papermaking operations and mill) and time trends that are important data features to consider, and documented continuing overexposure situations. Our results highlight the ongoing need for application of exposure controls to reduce paper dust exposures in the soft tissue paper industry.

Work Task Association with Lead Urine and Blood Concentrations in Informal Electronic Waste Recyclers in Thailand and Chile.

The informal recycling of electronic waste ("e-waste") is a lucrative business for workers in low- and middle-income countries across the globe. Workers dismantle e-waste to recover valuable materials that can be sold for income. However, workers expose themselves and the surrounding environment to hazardous agents during the process, including toxic metals like lead (Pb). To assess which tools, tasks, and job characteristics result in higher concentrations of urine and blood lead levels among workers, ten random samples of 2 min video clips were analyzed per participant from video recordings of workers at e-waste recycling sites in Thailand and Chile to enumerate potential predictors of lead burden. Blood and urine samples were collected from participants to measure lead concentration. Boosted regression trees (BRTs) were run to determine the relative importance of video-derived work variables and demographics, and their relationship with the urine and blood concentrations. Of 45 variables considered, five job characteristics consisting of close-toed shoes (relative importance of 43.9%), the use of blunt striking instruments (14%), bending the back (5.7%), dismantling random parts (4.4%), and bending the neck (3.5%) were observed to be the most important predictors of urinary Pb levels. A further five job characteristics, including lifting objects <20 lbs. (6.2%), the use of screwdrivers (4.2%), the use of pliers/scissors (4.2%), repetitive arm motion (3.3%), and lifting objects >20 pounds (3.2%) were observed to be among the most important factors of blood Pb levels. Overall, our findings indicate ten job characteristics that may strongly influence Pb levels in e-waste recycling workers' urine and blood.

Metal Exposures, Noise Exposures, and Audiometry from E-Waste Workers in Agbogbloshie, Ghana.

Metals, such as lead, may be ototoxic, but this property is not well understood, especially in conjunction with noise. This cross-sectional study investigated hearing, noise, and metal biomarkers in informal electronic waste (e-waste) recycling workers in Accra, Ghana. Workers (N = 58) participated in audiometric testing, a survey, blood collection, and personal noise dosimetry. Sixty percent of participants displayed audiometric notches indicative of noise-induced hearing loss (NIHL). Most workers (86%) reported high noise while working. Daily average noise levels were in the range 74.4-90.0 dBA. Linear regression models indicated participants who lived at Agbogbloshie Market for longer periods were significantly associated with worse hearing thresholds at 4 and 6 kHz. The models did not identify blood levels of lead, mercury, or cadmium as significant predictors of worse hearing thresholds or larger noise notches, but increased levels of selenium were significantly associated with better hearing at 6 kHz. Models of thresholds at 4 and 6 kHz were improved by including an interaction term between the maximum noise exposure and the level of zinc in whole blood, suggesting that zinc may protect hearing at lower noise levels, but not at higher levels. Further study of the relationships between elements, noise, and NIHL is needed.

Pesticide Spraying and Reduced Cholinesterase Activity among Hill Tribe Farmers in Thailand.

BACKGROUND: Farming is an important occupation in Thai hill tribe communities, which are often remote, and lack other economic opportunities along with basic educational, health care, and occupational health and safety services. Additionally, these communities have a unique culture and language. OBJECTIVES: The present study was conducted in northern Thailand to evaluate pesticide exposures and associated health impacts among hill tribe farmers, and to compare them to Thai farmers. METHODS: Lahu hill tribe farmers in a mountain community were recruited by public health hospital staff, along with a reference group of lowland Thai farmers. Participants completed a survey on demographic factors and work practices, and blood and urine samples were collected by a trained nurse. Acetylcholinesterase activity (AChE) was quantified to assess pesticide exposure, whereas liver and kidney functions were evaluated using clinical biomarkers. RESULTS: A large fraction (nearly 50%) of Lahu farmers were illiterate and could not speak Thai. Thai farmers worked fewer hours per week (39.4) than did Lahu farmers. Among Lahu farmers, AChE levels were significantly lower (worse) than those of Thai farmers. However, other health outcomes in these populations were similar. Formal education and language skills were not associated with pesticide exposures or health outcomes. Pesticide spraying was found to be a significant predictor of reduced AChE (OR=8.5, 95% CI 1.1-69.6). CONCLUSIONS: Pesticide exposures are a significant occupational health hazard among Thai hill tribe farmers. Training, potentially delivered by community health volunteers, is needed to communicate safe pesticide work practices to these farmers. PARTICIPANT CONSENT: Obtained. ETHICS APPROVAL: The study protocol was approved by the Institutional Review Board of Mae Fah Luang University (REH-61080). COMPETING INTERESTS: The authors declare no competing financial interests.

Road safety situation of electric bike riders: A cross-sectional study in courier and take-out food delivery population.

OBJECTIVE: Almost all courier and take-out food delivery riders in China use electric bikes as the main transport mode. This study aims to understand their riding behaviors and road traffic injury information of this population. METHODS: A cross-sectional field study focused on this population was conducted, including roadside observation and face-to-face retrospective street intercept interviews. RESULTS: Six hundred target delivery riders were observed and 480 were interviewed. The rate of overspeeding was 91.3%, and windshield use during winter was 91.2%. Traffic violation behaviors observed included riding in the motor vehicle lane (32.8%), not waiting behind the white line at a red light (23.3%), and using cell phone when riding (21.2%). Helmet use was significantly more common during the day (73.0%) than at night (64.7%; P = .028). About 46.5% of respondents rode an e-bike more than 8 h per day. In addition, 76.5% of interviewees had been involved in a traffic crash at least once. About 13.9% of crashes happened in motor vehicle lanes and 8.2% on sidewalks. Logistic regression analysis indicated that compared with uninjured riders, injured riders showed significantly greater odds ratios of unsafe behaviors for running red lights (odds ratio [OR] = 1.75) and protective factors for wearing a helmet (OR = 0.56). CONCLUSIONS: The courier and take-out food delivery population is a vulnerable occupational group and road traffic injuries related to e-bike use require more attention.