Exposure and illness among workers filing for COVID-19 related workers' compensation -- California, 2020.

OBJECTIVES: To characterize the incidence of SARS-CoV-2 exposure and COVID-19 infection among California workers' compensation claims in 2020 and examine risk factors for exposure. METHODS: Using a case-control approach, we combined machine learning techniques and job exposure matrices to assess associations between exposures and illness claims and clusters of claims within specific worksites over a 3-week period. RESULTS: Of the 117,125 COVID-19 claims, most were primarily among younger groups, of shorter tenure, and from healthcare occupations. Illness claims were among older groups with longer tenure. Jobs with very close physical proximity and high physical activity, along with transportation and warehousing industries, were associated with being part of a cluster of claims. CONCLUSIONS: The findings merit further study but indicate respiratory viral transmission and support efforts to systematically incorporate work-related variables into other California data sources.

Unmet Mental Health Needs Among California Workers Since the Start of the COVID-19 Pandemic.

OBJECTIVE: We sought to identify worker groups with high prevalence of unmet mental health needs to inform employer benefits programs and outreach to increase access to care. METHODS: We conducted a repeated cross-sectional study to understand unmet mental health needs among workers since the start of the COVID-19 pandemic using California Health Interview Survey data from 2013-2021. RESULTS: In 2021, 23.4% (CI: 22.4-24.4) reported unmet mental health needs, an absolute increase of 3.9% from 2019. Relative increases were highest among workers in the information industries (prevalence ratio [PR]: 1.89, CI: 1.4-2.5) and older workers (PR: 1.27, CI: 0.9-1.8). Increases in needing help were not met with comparable increases in seeking care. CONCLUSIONS: Unmet mental health needs increased for California workers during the pandemic. Employers should dedicate resources and implement strategies to increase access to care and promote worker well-being.

International study of childhood leukemia in residences near electrical transformer rooms.

OBJECTIVES: New epidemiologic approaches are needed to reduce the scientific uncertainty surrounding the association between extremely low frequency magnetic fields (ELF-MF) and childhood leukemia. While most previous studies focused on power lines, the Transformer Exposure study sought to assess this association using a multi-country study of children who had lived in buildings with built-in electrical transformers. ELF-MF in apartments above built-in transformers can be 5 times higher than in other apartments in the same building. This novel study design aimed to maximize the inclusion of highly exposed children while minimising the potential for selection bias. METHODS: We assessed associations between residential proximity to transformers and risk of childhood leukemia using registry based matched case-control data collected in five countries. Exposure was based on the location of the subject's apartment relative to the transformer, coded as high (above or adjacent to transformer), intermediate (same floor as apartments in high category), or unexposed (other apartments). Relative risk (RR) for childhood leukemia was estimated using conditional logistic and mixed logistic regression with a random effect for case-control set. RESULTS: Data pooling across countries yielded 16 intermediate and 3 highly exposed cases. RRs were 1.0 (95% CI: 0.5, 1.9) for intermediate and 1.1 (95% CI: 0.3, 3.8) for high exposure in the conditional logistic model. In the mixed logistic model, RRs were 1.4 (95% CI: 0.8, 2.5) for intermediate and 1.3 (95% CI: 0.4, 4.4) for high. Data of the most influential country showed RRs of 1.1 (95% CI: 0.5, 2.4) and 1.7 (95% CI: 0.4, 7.2) for intermediate (8 cases) and high (2 cases) exposure. DISCUSSION: Overall, evidence for an elevated risk was weak. However, small numbers and wide confidence intervals preclude strong conclusions and a risk of the magnitude observed in power line studies cannot be excluded.

Extreme Heat and Occupational Health Risks.

Climate change poses a significant occupational health hazard. Rising temperatures and more frequent heat waves are expected to cause increasing heat-related morbidity and mortality for workers across the globe. Agricultural, construction, military, firefighting, mining, and manufacturing workers are at particularly high risk for heat-related illness (HRI). Various factors, including ambient temperatures, personal protective equipment, work arrangements, physical exertion, and work with heavy equipment may put workers at higher risk for HRI. While extreme heat will impact workers across the world, workers in low- and middle-income countries will be disproportionately affected. Tracking occupational HRI will be critical to informing prevention and mitigation strategies. Renewed investment in these strategies, including workplace heat prevention programs and regulatory standards for indoor and outdoor workers, will be needed. Additional research is needed to evaluate the effectiveness of interventions in order to successfully reduce the risk of HRI in the workplace.

Temporal assessment of disparities in California COVID-19 mortality by industry: a population-based retrospective cohort study.

PURPOSE: To assess changes in the COVID-19 mortality rate and disparities over variants or waves by industry. METHODS: We identified COVID-19 deaths that occurred between January 2020 and May 2022 among California workers aged 18-64 years using death certificates, and estimated Californians at risk using the Current Population Survey. The waves in deaths were wave 1: March-June 2020, wave 2: July-November 2020, wave 3/Epsilon and Alpha variants: December 2020-May 2021, wave 4/Delta variant: June 2021-January 2022, and wave 5/Omicron variant: February-May 2022. We used Poisson regression to generate wave-specific mortality rate ratios (MRR) and included an interaction term between industry and wave in different models to assess significance of the change in MRR. RESULTS: In all waves of the pandemic, healthcare, other services, manufacturing, transportation, and retail trade industries had higher mortality rates than the professional, scientific, and technical industry. The healthcare industry had the highest relative rate earlier in the pandemic, while other services, utilities, and accommodation and food services industries had substantial increases in MRR in later waves. CONCLUSIONS: Industries that consistently had disproportionate COVID-19 mortality may have benefitted from protections that consider workers' increased exposure and vulnerability to severe outcomes.

Occupational COVID-19 Exposures and Illnesses among Workers in California-Analysis of a New Occupational COVID-19 Surveillance System.

Little is known about occupational SARS-CoV-2 exposures and COVID-19 outcomes. We established a Doctor's First Reports of Occupational Injury or Illness (DFR)-based surveillance system to study cases of work-related COVID-19 exposures and disease. The surveillance data included demographics, occupation, industry, exposure, and illness, details including hospitalization and lost work. We classified workers into 'healthcare', non-healthcare 'public-facing', or 'other' worker groups, and rural-urban commuting areas (RUCAs). We describe worker exposures and outcomes overall by worker group and RUCA. We analyzed 2848 COVID-19 DFRs representing workers in 22 detailed occupation groups and 19 industry groups. Most DFRs were for workers in metropolitan RUCAs (89%) and those in healthcare (42%) and public-facing (24%) worker groups. While DFRs were from 382 unique worksites, 52% were from four hospitals and one prison. Among 1063 DFRs with a suspected exposure, 73% suspected exposure to a patient or client. Few DFRs indicated hospitalization (3.9%); however, the proportion hospitalized was higher among nonmetropolitan (7.4%) and public-facing (6.7%) workers. While 56% of DFRs indicated some lost work time, the proportion was highest among public-facing (80%) workers. Healthcare and prison workers were the majority of reported occupational COVID-19 exposures and illnesses. The risk of COVID-19 hospitalization and lost work may be highest among nonmetropolitan and public-facing workers.

Evaluating the association between in-person work and the risk of SARS-CoV-2 infection through June 2021.

OBJECTIVES: Recent studies have evaluated COVID-19 outbreaks and excess mortality by occupation sectors. Studies on SARS-CoV-2 infection across occupation and occupation-related factors remain lacking. In this study, we estimate the effect of in-person work on SARS-CoV-2 infection risk and describe SARS-CoV-2 seroprevalence among working adults. METHODS: We used Wave 1 data (May to June 2021) from CalScope, a population-based seroprevalence study in California. Occupation data were coded using the National Institute for Occupational Safety and Health Industry and Occupation Computerized Coding System. Dried blood spot specimens were tested for antibodies to establish evidence of prior infection. We estimated the causal effect of in-person work on SARS-CoV-2 infection risk using the g-formula and describe SARS-CoV-2 seroprevalence across occupation-related factors. RESULTS: Among 4335 working adults, 53% worked in person. In-person work was associated with increased risk of prior SARS-CoV-2 infection (risk difference: 0.03; [95% CI: 0.02-0.04]) compared with working remotely. Workers that reported job loss or who were without medical insurance had higher evidence of prior infection. Amongst in-person workers, evidence of prior infection was highest within farming, fishing, and forestry (55%; [95% CI: 26%-81%]); installation, maintenance, and repair (23%; [12%-39%]); building and grounds cleaning and maintenance (23%; [13%-36%]); food preparation and serving related (22% [13%-35%]); and healthcare support (22%; [13%-34%]) occupations. Workers who identified as Latino, reported a household income of <$25K, or who were without a bachelor's degree also had higher evidence of prior infection. CONCLUSIONS: SARS-CoV-2 infection risk varies by occupation. Future vaccination strategies may consider prioritizing in-person workers.

Risk factors for COVID-19 among Californians working outside the home, November 2020 - May 2021.

BACKGROUND: Higher incidences of COVID-19 mortality and outbreaks have been found in certain industries and occupations. Workplace factors, including working in close proximity to others and contact with the public can facilitate SARS-CoV-2 transmission, especially without appropriate protective measures. Limited information is available about workers at highest risk for SARS-CoV-2 infection. METHODS: A phone-based, nonprobability study was conducted between November 2020 and May 2021 among California workers who were tested for SARS-CoV-2. Participants were asked about demographics and workplace factors, including industry, occupation, and implementation of COVID-19 mitigation measures. Using the SARS-CoV-2 occupational exposure matrix, three exposure metrics and a combination index were used to categorize occupations. We assessed the association between workplace risks and SARS-CoV-2 test positivity using adjusted logistic regression. RESULTS: We enrolled 451 (13%) of 3475 potentially eligible workers in the study: 212 with positive and 239 with negative SARS-CoV-2 test results. Those working very close to others and with the highest combined exposure index had a positive association with SARS-CoV-2 positivity. Primarily indoor workers had a lower odds of test positivity compared to those with any outdoor work. There was no association between public-facing occupations and test positivity. Participants with employers who implemented mitigation measures in all three control categories-engineering, administrative, and personal protective equipment-had lower odds of test positivity than those with fewer mitigation measures. CONCLUSIONS: Worker groups with higher risk factors should be prioritized for outreach. Assessment of occupational risk factors collectively can provide insight to inform preventative actions for workers, employers, and public health entities.

Increases in Prevalent Depressed Mood and Suicidal Ideation among Workers during the COVID-19 Pandemic-Findings from the California Health Interview Survey.

Limited data exist on COVID-19's mental health impact on non-healthcare workers. We estimated the prevalence of depressed mood and suicidal ideation experienced in the past year among California workers and assessed whether the prevalence changed during the COVID-19 pandemic. We analyzed 2013-2020 California Health Interview Survey data using survey-weighted methods to assess the change in the prevalence of depressed mood and suicidal ideation from 2019 to 2020 for working adults by demographics and occupational groups. We used trend-adjusted quasi-Poisson regressions and report rate ratios (RR), comparing the prevalence of outcomes during 2020 to the pre-pandemic period (2013-2019). We identified priority occupation groups with a higher-than-average outcome prevalence in 2020 and rate increases after adjusting for pre-pandemic trends. Our analysis included 168,768 respondents, of which 65% were workers. Production and service workers were the priority occupation groups for depressed mood (RR: 1.46, CI: 1.1-1.9; RR: 1.23, CI: 1.1-1.4) and suicidal ideation (RR: 1.86, CI: 1.0-3.6; RR: 1.47, CI: 1.1-1.9). Workers aged 45-65 years experienced over a 30% relative increase in both outcomes from 2019 to 2020. Depressed mood and suicidal ideation in the past year increased for production, service, and older workers during the pandemic. These groups should be considered for mental health interventions.

COVID-19 Outbreaks and Mortality Among Public Transportation Workers - California, January 2020-May 2022.

Work-related factors can contribute to risk for exposure to and infection with SARS-CoV-2, the virus that causes COVID-19, and subsequent COVID-19-attributable outcomes, including death. Comparing COVID-19 metrics across industries can help identify workers at highest risk. Elevated COVID-19 mortality rates have been reported among all transportation workers, as well as specifically in public transportation industries (1-3). The California Department of Public Health (CDPH) calculated public transportation industry-specific COVID-19 outbreak incidence during January 2020-May 2022 and analyzed all laboratory-confirmed COVID-19 deaths among working-age adults in California to calculate public transportation industry-specific mortality rates during the same period. Overall, 340 confirmed COVID-19 outbreaks, 5,641 outbreak-associated cases, and 537 COVID-19-associated deaths were identified among California public transportation industries. Outbreak incidence was 5.2 times as high (129.1 outbreaks per 1,000 establishments) in the bus and urban transit industry and 3.6 times as high in the air transportation industry (87.7) as in all California industries combined (24.7). Mortality rates were 2.1 times as high (237.4 deaths per 100,000 workers) in transportation support services and 1.8 times as high (211.5) in the bus and urban transit industry as in all industries combined (114.4). Workers in public transportation industries are at higher risk for COVID-19 workplace outbreaks and mortality than the general worker population in California and should be prioritized for COVID-19 prevention strategies, including vaccination and enhanced workplace protection measures.

Reported Exposures Among In-Person Workers With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection in 6 States, September 2020-June 2021.

BACKGROUND: Surveillance systems lack detailed occupational exposure information from workers with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The National Institute for Occupational Safety and Health partnered with 6 states to collect information from adults diagnosed with SARS-CoV-2 infection who worked in person (outside the home) in non-healthcare settings during the 2 weeks prior to illness onset. METHODS: The survey captured demographic, medical, and occupational characteristics and work- and non-work-related risk factors for SARS-CoV-2 infection. Reported close contact with a person known or suspected to have SARS-CoV-2 infection was categorized by setting as exposure at work, exposure outside of work only, or no known exposure/did not know. Frequencies and percentages of exposure types are compared by respondent characteristics and risk factors. RESULTS: Of 1111 respondents, 19.4% reported exposure at work, 23.4% reported exposure outside of work only, and 57.2% reported no known exposure/did not know. Workers in protective service occupations (48.8%) and public administration industries (35.6%) reported exposure at work most often. More than one third (33.7%) of respondents who experienced close contact with ≥10 coworkers per day and 28.8% of respondents who experienced close contact with ≥10 customers/clients per day reported exposures at work. CONCLUSIONS: Exposure to occupational SARS-CoV-2 was common among respondents. Examining differences in exposures among different worker groups can help identify populations with the greatest need for prevention interventions. The benefits of recording employment characteristics as standard demographic information will remain relevant as new and reemerging public health issues occur.

Close physical proximity on the job-An exposure matrix.

BACKGROUND: The workplace is a setting for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission via respiratory droplets and aerosols for those working in close proximity to others. Currently, limited methods exist for assessing SARS-CoV-2 exposure. Since occupation serves as a surrogate measure, job exposure matrices (JEMs) can be useful for population-based exposure assessment for a portion of exposure. METHODS: We developed a JEM to assess physical proximity at work. Scores for questions related to frequency of face-to-face discussions, working closely with others, and working with a team were extracted from a US-based, comprehensive source of descriptive occupational information (Occupational Information Network [O*NET]). We described score distributions using univariate analyses, devised thresholds, and assigned exposure levels for 968 O*NET occupations. Three exposure measures were constructed using combinations of O*NET data, with expert judgment, and accounting for telework. National and California employment estimates were used to assess the workforce proportions by proximity level and demographic characteristics. RESULTS: We categorized 535 US Census occupations (2010) into four-level ordinal exposure levels (not close to very close). Overall, an estimated 56% of the California workforce worked in very close proximity, which decreased to 46% when accounting for telework. The occupational groups working very close across all three measures were: healthcare support, healthcare practitioner, food preparation and serving, building and grounds cleaning and maintenance, and protective service occupations. Latinos and women were overrepresented within occupations working in very close physical proximity. CONCLUSION: JEMs can inform SARS-CoV-2 exposure assessment for epidemiologic studies, assist in resource allocation, and inform prevention strategies.

Disparities in COVID-19 fatalities among working Californians.

BACKGROUND: Information on U.S. COVID-19 mortality rates by occupation is limited. We aimed to characterize 2020 COVID-19 fatalities among working Californians to inform preventive strategies. METHODS: We identified laboratory-confirmed COVID-19 fatalities with dates of death in 2020 by matching death certificates to the state's COVID-19 case registry. Working status for decedents aged 18-64 years was determined from state employment records, death certificates, and case registry data and classified as "confirmed working," "likely working," or "not working." We calculated age-adjusted overall and occupation-specific COVID-19 mortality rates using 2019 American Community Survey denominators. RESULTS: COVID-19 accounted for 8,050 (9.9%) of 81,468 fatalities among Californians 18-64 years old. Of these decedents, 2,486 (30.9%) were matched to state employment records and classified as "confirmed working." The remainder were classified as "likely working" (n = 4,121 [51.2%]) or "not working" (n = 1,443 [17.9%]) using death certificate and case registry data. Confirmed and likely working COVID-19 decedents were predominantly male (76.3%), Latino (68.7%), and foreign-born (59.6%), with high school or less education (67.9%); 7.8% were Black. The overall age-adjusted COVID-19 mortality rate was 30.0 per 100,000 workers (95% confidence interval [CI], 29.3-30.8). Workers in nine occupational groups had age-adjusted mortality rates higher than this overall rate, including those in farming (78.0; 95% CI, 68.7-88.2); material moving (77.8; 95% CI, 70.2-85.9); construction (62.4; 95% CI, 57.7-67.4); production (60.2; 95% CI, 55.7-65.0); and transportation (57.2; 95% CI, 52.2-62.5) occupations. While occupational differences in mortality were evident across demographic groups, mortality rates were three-fold higher for male compared with female workers and three- to seven-fold higher for Latino and Black workers compared with Asian and White workers. CONCLUSION: Californians in manual labor and in-person service occupations experienced disproportionate COVID-19 mortality, with the highest rates observed among male, Latino, and Black workers; these occupational group should be prioritized for prevention.

Residential proximity to plant nurseries and risk of childhood leukemia.

BACKGROUND: Pesticides are a potential risk factor for childhood leukemia. Studies evaluating the role of prenatal and/or early life exposure to pesticides in the development of childhood leukemia have produced a range of results. In addition to indoor use of pesticides, higher risks have been reported for children born near agricultural crops. No studies have looked at pesticide exposure based on proximity of birth residence to commercial plant nurseries, even though nurseries are located much closer to residences than agricultural crops and can potentially result in chronic year-round pesticide exposure. OBJECTIVES: To evaluate whether risk of childhood leukemia is associated with pesticide use as determined by distance of residence at birth to commercial, outdoor plant nurseries. METHODS: We conducted a large statewide, record-based case-control study of childhood leukemia in California, which included 5788 childhood leukemia cases and an equal number of controls. Pesticide exposure was based on a spatial proximity model, which combined geographic information system data with aerial satellite imagery. RESULTS: Overall, the results supported an increased childhood leukemia risk only for birth residences very close to nurseries. For birth residences less than 75 m from plant nurseries, we found an increased risk of childhood leukemia (odds ratio (OR) 2.40, 95% confidence interval (CI) 0.99-5.82) that was stronger for acute lymphocytic leukemia (OR 3.09, 95% CI 1.14-8.34). DISCUSSION: The association was robust to choices of reference group, cut points and data quality. Our findings suggest that close proximity to plant nurseries may be a risk factor for childhood leukemia and that this relationship should be further evaluated.

Exploratory narrative text analysis to characterize tasks associated with injuries among electric utility line workers: EPRI Occupational Health and Safety Database 1995-2013.

BACKGROUND: Injury prevention is an important goal for electric utility line workers who are among the top 10 U.S. occupational groups sustaining fatal injuries on the job. METHODS: Using narrative text fields, we identified 10 high-risk tasks among electric utility line workers. We performed a case-control study of task-injury associations using data from the Electric Power Research Institute Occupational Health and Safety Database (1995-2013). RESULTS: Drawn from 12,323 line worker injuries, cases were individuals with a major injury (5 or more days lost work) matched to controls, individuals with a minor injury (less than 1 day lost work), on company and year of injury. Conditional logistic regression estimated adjusted odds ratios (OR) and 95% confidence intervals (95% CI). Some tasks associated with higher odds for major injuries among line workers included: climbing up/down ladder/stairs/elevator (OR = 4.3; 95% CI = 2.6, 7.4); climbing down poles and transmission towers (OR = 5.5; 95% CI = 3.6, 8.4); entering/stepping out/approaching utility trucks, bucket, or vaults (OR = 5.8; 95% CI = 4.0, 8.4); and performing repetitive work/overtime (OR = 5.5; 95% CI = 3.2, 9.5). CONCLUSIONS: Knowledge gained can be used to focus efforts and plan efficient preventive measures that reduce injury rates, time lost from work, and costs within the electric power industry.

Spatial and temporal assessment of radiofrequency electromagnetic fields emitted by smart meters and smart meter banks in urban environments.

This paper describes radiofrequency (RF) electromagnetic field (EMF) measurements in the vicinity of single and banks of advanced metering infrastructure (AMI) smart meters. The measurements were performed in a meter testing and distribution facility as well as in-situ at five urban locations. The measurements consisted of gauging the RF environment at the place of assessment, evaluating the worst-case electric-field levels at various positions around the assessed AMI meter configuration (spatial assessment), which ranged from a single meter to a bank of 81 m, and calculating the duty cycle of the system, i.e. the fraction of time that the AMI meters were actually transmitting (12-h temporal assessment). Both in-situ and in the meter facility, the maximum field levels at 0.3 m from the meter configurations were 10-13 V/m for a single meter and 18-38 V/m for meter banks with 20-81 m. Furthermore, 6-min average duty cycles of 0.01% (1 m) up to 13% (81-m bank) were observed. Next, two general statistical models (one for a single meter and one for a meter bank) were constructed to predict the electric-field strength as a function of distance to any configuration of the assessed AMI meters. For all scenarios, the measured exposure levels (at a minimum distance of 0.3 m) were well below the maximum permissible exposure limits issued by the International Commission on Non-Ionizing Radiation Protection (ICNIRP), the U.S. Federal Communications Commission (FCC), and the Institute of Electrical and Electronics Engineers (IEEE). Indeed, the worst-case time-average exposure level at a distance of 0.3 m from an AMI installation was 5.39% of the FCC/IEEE and 9.43% of the ICNIRP reference levels.

Emissions From Smart Meters and Other Residential Radiofrequency Sources.

The advent of the Internet of things comes with a huge increase in wirelessly communicating devices in our environment. For example, smart energy-consumption meters are being widely deployed in residences from which they communicate their state using radiofrequency networks. Accurate characterization of the radiofrequency emissions from emerging residential wireless solutions is important to inform the public about the potential impact on their exposure to radiofrequency electromagnetic fields. A new measurement procedure to determine the exposure from residential radiofrequency devices is proposed by assessing the peak emitted fields at various distances and the proportion of time they transmit (duty cycle). Radiofrequency emissions from 55 residential devices were measured in 10 residences (Belgium and France) and compared to environmental levels, emissions from 41 mobile phones, and international standards. Overall, residential levels of radiofrequency electromagnetic field exposure are low. In addition to the continuous environmental exposure, wireless access points (due to frequent use) and especially mobile phones and other personal communication devices (due to their use close to the body) continue to represent the bulk of the radiofrequency electromagnetic field exposure in the smart home. However, some residential devices can significantly increase the exposure if their duty cycles are high enough (>10%), especially when held or used close to the body. Individual smart meters, on the other hand, will contribute only little in general, despite emissions of up to 20 V m at 50 cm, due to their low duty cycles (maximum 1%) and locations.

Childhood leukemia risk in the California Power Line Study: Magnetic fields versus distance from power lines.

Pooled analyses have suggested a small increased risk of childhood leukemia associated with distance and with exposure to high magnetic fields from power transmission lines. Because magnetic fields are correlated with distance from lines, the question of whether the risk is due to magnetic fields exposure or to some other factor associated with distance from lines is unresolved. We used data from a large records-based case-control study to examine several research questions formulated to disentangle the relationships among magnetic fields, distance from high voltage lines, and childhood leukemia risk. In models examining an interaction between distance and magnetic fields exposure, we found that neither close proximity to high voltage lines alone nor exposure to high calculated fields alone were associated with childhood leukemia risk. Rather, elevated risk was confined to the group that was both very close to high voltage lines (<50 m) and had high calculated fields (≥0.4 µT) (odds ratio 4.06, 95% CI 1.16, 14.3). Further, high calculated fields (≥0.4 µT) that were due solely to lower voltage lines (<200 kV) were not associated with elevated risk; rather, risk was confined to high fields attributable to high voltage lines. Whilst other explanations are possible, our findings argue against magnetic fields as a sole explanation for the association between distance and childhood leukemia and in favor of some other explanation linked to characteristics of power lines.

Proximity to overhead power lines and childhood leukaemia: an international pooled analysis.

BACKGROUND: Although studies have consistently found an association between childhood leukaemia risk and magnetic fields, the associations between childhood leukaemia and distance to overhead power lines have been inconsistent. We pooled data from multiple studies to assess the association with distance and evaluate whether it is due to magnetic fields or other factors associated with distance from lines. METHODS: We present a pooled analysis combining individual-level data (29,049 cases and 68,231 controls) from 11 record-based studies. RESULTS: There was no material association between childhood leukaemia and distance to nearest overhead power line of any voltage. Among children living < 50 m from 200 + kV power lines, the adjusted odds ratio for childhood leukaemia was 1.33 (95% CI: 0.92-1.93). The odds ratio was higher among children diagnosed before age 5 years. There was no association with calculated magnetic fields. Odds ratios remained unchanged with adjustment for potential confounders. CONCLUSIONS: In this first comprehensive pooled analysis of childhood leukaemia and distance to power lines, we found a small and imprecise risk for residences < 50 m of 200 + kV lines that was not explained by high magnetic fields. Reasons for the increased risk, found in this and many other studies, remains to be elucidated.