Does recall bias explain the association of mood disorders with workplace harassment?

Purpose: To determine the contribution of recall bias to the observed excess in mental ill-health in those reporting harassment at work. Methods: A prospective cohort of 1885 workers in welding and electrical trades was contacted every six months for up to 5 years, asking whether they were currently anxious or depressed and whether this was made worse by work. Only at the end of the study did we ask about any workplace harassment they had experienced at work. We elicited sensitivity and specificity of self-reported bullying from published reliability studies and formulated priors that reflect the possibility of over-reporting of workplace harassment (exposure) by those whose anxiety or depression was reported to be made worse by work (cases). We applied the resulting misclassification models to probabilistic bias analysis (PBA) of relative risks. Results: We observe that PBA implies that it is unlikely that biased misclassification due to the study subjects' states of mind could have caused the entire observed association. Indeed, the results demonstrated that doubling of risk of anxiety or depression following workplace harassment is plausible, with the unadjusted relative risk attenuated with understated uncertainty. Conclusions: It seems unlikely that risk of anxiety or depression following workplace harassment can be explained by the form of recall bias that we proposed.

Work Characteristics, Workplace Support, and Mental Ill-Health in a Canadian Cohort of Healthcare Workers During the COVID-19 Pandemic.

OBJECTIVE: The aim of the study was to identify determinants of mental health in healthcare workers (HCW) during the COVID-19 pandemic. METHODS: A cohort of Canadian HCW completed four questionnaires giving details of work with patients, ratings of workplace supports, a mental health questionnaire, and substance use. Principal components were extracted from 23 rating scales. Risk factors were examined by Poisson regression. RESULTS: A total of 4854 (97.8%) of 4964 participants completed ratings and mental health questionnaires. Healthcare workers working with patients with COVID-19 had high anxiety and depression scores. One of three extracted components, 'poor support,' was related to work with infected patients and to anxiety, depression, and substance use. Availability of online support was associated with feelings of better support and less mental ill-health. CONCLUSIONS: Work with infected patients and perceived poor workplace support were related to anxiety and depression during the pandemic.

Excess risk of COVID-19 infection and mental distress in healthcare workers during successive pandemic waves: Analysis of matched cohorts of healthcare workers and community referents in Alberta, Canada.

OBJECTIVES: To investigate changes in risk of infection and mental distress in healthcare workers (HCWs) relative to the community as the COVID-19 pandemic progressed. METHODS: HCWs in Alberta, Canada, recruited to an interprovincial cohort, were asked consent to link to Alberta's administrative health database (AHDB) and to information on COVID-19 immunization and polymerase chain reaction (PCR) testing. Those consenting were matched to records of up to five community referents (CRs). Physician diagnoses of COVID-19 were identified in the AHDB from the start of the pandemic to 31 March 2022. Physician consultations for mental health (MH) conditions (anxiety, stress/adjustment reaction, depressive) were identified from 1 April 2017 to 31 March 2022. Risks for HCW relative to CR were estimated by fitting wave-specific hazard ratios. RESULTS: Eighty percent (3050/3812) of HCWs consented to be linked to the AHDB; 97% (2959/3050) were matched to 14,546 CRs. HCWs were at greater risk of COVID-19 overall, with first infection defined from either PCR tests (OR=1.96, 95%CI 1.76-2.17) or physician records (OR=1.33, 95%CI 1.21-1.45). They were also at increased risk for each of the three MH diagnoses. In analyses adjusted for confounding, risk of COVID-19 infection was higher than for CRs early in the pandemic and during the fifth (Omicron) wave. The excess risk of stress/adjustment reactions (OR=1.52, 95%CI 1.35-1.71) and depressive conditions (OR=1.39, 95%CI 1.24-1.55) increased with successive waves during the epidemic, peaking in the fourth wave. CONCLUSION: HCWs were at increased risk of both COVID-19 and mental ill-health with the excess risk continuing late in the pandemic.

RéSUMé: OBJECTIFS: Étudier l'évolution du risque d'infection et de problèmes de santé mentale (PSM) chez les travailleurs de la santé (TdS), comparé à la population générale, au cours de la pandémie de COVID-19. MéTHODES: Certains TdS de l'Alberta (Canada) participant à une cohorte interprovinciale, ont consenti à ce que la base administrative de santé de l'Alberta (AHDB) nous transmette leurs données de vaccination contre la COVID-19 et de tests d'amplification des acides nucléiques (TAAN). Ceux ayant consenti ont été appariés à un maximum de cinq témoins de population générale. Les diagnostics médicaux (par médecins) de COVID-19 ont été identifiés dans l'AHDB du début de la pandémie jusqu'au 31 mars 2022. Les consultations médicales pour PSM (anxiété, stress/troubles de l'adaptation, dépression) ont été identifiées entre le 1er avril 2017 et le 31 mars 2022. Les rapports de cotes (RC) comparant les TdS aux témoins de la population générale ont été estimés pour chaque vague d'infection. RéSULTATS: Quatre-vingts pourcent (80 %; 3050/3812) des TdS ont donné leur consentement à ce que leurs données nous soient transmises par l'AHDB; 97 % d'entre eux (2959/3050) ont été appariés à 14 546 témoins. Dans l'ensemble, les TdS étaient plus à risque de COVID-19, avec une première infection identifiée soit par les TANN (RC=1,96, IC de 95% 1,76-2,17), soit via les dossiers médicaux (RC=1,33, IC de 95% 1,21-1,45). Ils étaient également plus à risque pour chacun des trois problèmes de SM. Le risque de COVID-19 ajustés pour les facteurs de confusion était plus élevé que chez les témoins au début de la pandémie et durant la cinquième vague (variant Omicron). Les excès de risque de stress/troubles de l'adaptation (RC=1,52, IC de 95% 1,35-1,71) et de dépression (RC=1,39, IC de 95% 1,24-1,55) ont augmenté au fil des vagues de l'épidémie, avec un pic à la quatrième vague. CONCLUSION: Les TdS étaient plus à risque d'infection de COVID-19 et de troubles de santé mentale avec cet excès de risque se prolongeant plus tard dans la pandémie.

Determinants of SARS-CoV-2 IgG response and decay in Canadian healthcare workers: A prospective cohort study.

INTRODUCTION: Healthcare workers (HCWs) from an interprovincial Canadian cohort gave serial blood samples to identify factors associated with anti-receptor binding domain (anti-RBD) IgG response to the SARS-CoV-2 virus. METHODS: Members of the HCW cohort donated blood samples four months after their first SARS-CoV-2 immunization and again at 7, 10 and 13 months. Date and type of immunizations and dates of SARS-CoV-2 infection were collected at each of four contacts, together with information on immunologically-compromising conditions and current therapies. Blood samples were analyzed centrally for anti-RBD IgG and anti-nucleocapsid IgG (Abbott Architect, Abbott Diagnostics). Records of immunization and SARS-CoV-2 testing from public health agencies were used to assess the impact of reporting errors on estimates from the random-effects multivariable model fitted to the data. RESULTS: 2752 of 4567 vaccinated cohort participants agreed to donate at least one blood sample. Modelling of anti-RBD IgG titer from 8903 samples showed an increase in IgG with each vaccine dose and with first infection. A decrease in IgG titer was found with the number of months since vaccination or infection, with the sharpest decline after the third dose. An immunization regime that included mRNA1273 (Moderna) resulted in higher anti-RBD IgG. Participants reporting multiple sclerosis, rheumatoid arthritis or taking selective immunosuppressants, tumor necrosis factor inhibitors, calcineurin inhibitors and antineoplastic agents had lower anti-RBD IgG. Supplementary analyses showed higher anti-RBD IgG in those reporting side-effects of vaccination, no relation of anti-RBD IgG to obesity and lower titers in women immunized in early or mid-pregnancy. Sensitivity analysis results suggested no important bias in the self-report data. CONCLUSION: Creation of a prospective cohort was central to the credibility of results presented here. Serial serology assessments, with longitudinal analysis, provided effect estimates with enhanced accuracy and a clearer understanding of medical and other factors affecting response to vaccination.

Parkinson's disease and occupational exposure to organic solvents in Finland: a nationwide case-control study.

OBJECTIVE: This study aimed to investigate the association between Parkinson's disease (PD) and occupational exposure to organic solvents generally and chlorinated hydrocarbons (CHC) in particular. METHODS: We assembled a Finland-wide case-control study for birth years 1930-1950 by identifying incident PD cases from the register of Reimbursement of Medical Costs and drawing two controls per case using incidence density sampling from the Population Information System, matched on sex, birth year, and residency in Finland in 1980-2014. Occupation and socioeconomic status (SES) were identified from national censuses. We assessed cumulative occupational exposures via FINJEM job-exposure matrix. Smoking was based on occupation-specific prevalence by sex from national surveys. We estimated confounder-adjusted PD incidence rate ratios (IRR) via logistic regression and evaluated their sensitivity to errors in FINJEM through probabilistic bias analysis (PBA). RESULTS: Among ever-employed, we identified 17 187 cases (16.0% potentially exposed to CHC) and 35 738 matched controls. Cases were more likely to not smoke and belong to higher SES. Cumulative exposure (CE) to CHC (per 100 ppm-years, 5-year lag) was associated with adjusted IRR 1.235 (95% confidence interval 0.986-1.547), with stronger associations among women and among persons who had more census records. Sensitivity analyses did not reveal notable associations, but stronger effects were seen in the younger birth cohort (1940-1950). PBA produced notably weaker associations, yielding a median IRR 1.097 (95% simulation interval 0.920-1.291) for CHC. CONCLUSION: Our findings imply that PD is unlikely to be related to typical occupational solvent exposure in Finland, but excess risk cannot be ruled out in some highly exposed occupations.

Does adjustment for non-differential misclassification of dichotomous exposure induce positive bias if there is no true association?

This article is a response to an off-the-record discussion that I had at an international meeting of epidemiologists more than decade ago. It centered on a concern, perhaps widely spread, that adjustment for exposure misclassification can induce a false positive result. I trace the possible history of this supposition and test it in a simulated case-control study under the assumption of non-differential misclassification of binary exposure, in which a Bayesian adjustment is applied. Probabilistic bias analysis is also briefly considered. The main conclusion is that adjustment for the presumed non-differential exposure misclassification of dichotomous does not "induce" positive associations, especially if the focus of the interpretation of the result is taken away from the point estimate. The misconception about positive bias induced by adjustment for exposure misclassification, if more clearly explained during the training of epidemiologists, may promote appropriate (and wider) use of the adjustment techniques. The simple message that can be derived from this paper is: "Exposure misclassification as a tractable problem that deserves much more attention than just a typical qualitative throw-away discussion".

Cohort profile: recruitment and retention in a prospective cohort of Canadian healthcare workers during the COVID-19 pandemic.

PURPOSE: Healthcare workers were recruited early in 2020 to chart effects on their health as the COVID-19 pandemic evolved. The aim was to identify modifiable workplace risk factors for infection and mental ill health. PARTICIPANTS: Participants were recruited from four Canadian provinces, physicians (medical doctors, MDs) in Alberta, British Columbia, Ontario and Quebec, registered nurses (RNs), licensed practical nurses (LPNs) and healthcare aides (HCAs) in Alberta and personal support workers (PSWs) in Ontario. Volunteers gave blood for serology testing before and after vaccination. Cases with COVID-19 were matched with up to four referents in a nested case-referent study. FINDINGS TO DATE: Overall, 4964/5130 (97%) of those recruited joined the longitudinal cohort: 1442 MDs, 3136 RNs, 71 LPNs, 235 PSWs, 80 HCAs. Overall, 3812 (77%) were from Alberta. Prepandemic risk factors for mental ill health and respiratory illness differed markedly by occupation. Participants completed questionnaires at recruitment, fall 2020, spring 2021, spring 2022. By 2022, 4837 remained in the cohort (127 had retired, moved away or died), for a response rate of 89% (4299/4837). 4567/4964 (92%) received at least one vaccine shot: 2752/4567 (60%) gave postvaccine blood samples. Ease of accessing blood collection sites was a strong determinant of participation. Among 533 cases and 1697 referents recruited to the nested case-referent study, risk of infection at work decreased with widespread vaccination. FUTURE PLANS: Serology results (concentration of IgG) together with demographic data will be entered into the publicly accessible database compiled by the Canadian Immunology Task Force. Linkage with provincial administrative health databases will permit case validation, investigation of longer-term sequelae of infection and comparison with community controls. Analysis of the existing dataset will concentrate on effects on IgG of medical condition, medications and stage of pregnancy, and the role of occupational exposures and supports on mental health during the pandemic.

A participatory approach to designing and implementing an occupational health intervention for the nail salon community in the Greater Philadelphia region.

BACKGROUND: The nail salon industry in the US comprises mostly immigrant-owned, small mom-and-pop salons that employ primarily first-generation immigrant workers from Asia. Because of the cultural and language barriers, both owners and workers may not avail themselves of the occupational safety resources. We formed an academic-community partnership to co-design a feasibility study and multi-level occupational health intervention for Vietnamese-speaking salon owners, workers, and community-based organization. METHODS: The intervention for each salon included (i) 2-h in-person training covering chemical safety, infection control, musculoskeletal prevention, and workers' rights for both the owners and their employees, (ii) a tailored recommendation report for the owner, and (iii) check-ins with the owner during the 3-month follow-up. Community partner was trained to deliver the in-language training with technical assistance from the research team. Baseline and post-intervention individual data about health symptoms and behaviors, as well as personal chemical exposures were collected and analyzed. RESULTS: A total of 44 participants from 12 consented salons enrolled in the study. One salon dropped out at follow-up due to change of ownership. Analysis of the differences between post-and pre-intervention showed a tendency toward reduction in some self-reported symptoms in the respiratory system, skin, and eyes, neurotoxicity score, as well as chemical exposures. We could not rule out seasonality as an explanation for these trends. Increase in self-efficacy in some areas was observed post-intervention. CONCLUSIONS: Our study demonstrated a successful academic-community partnership to engage community members in the intervention study. While the intervention effects from this feasibility study should be interpreted with caution, our preliminary results indicated that our community-based intervention is a promising approach to reduce work-related exposures among Asian American nail salon workers.

Changes in Anxiety and Depression Over the First Year of COVID-19 Pandemic in Philadelphia, PA: Work Characteristics and Mental Health Supports.

OBJECTIVE: We investigated the change in anxiety and depression in a general population cohort over the first year of COVID-19 pandemic in relation to work characteristics and mental health support. METHODS: We administered questionnaires to a convenience sample in Greater Philadelphia, in summer of 2020 and a year later. With more than 60% response rate, 461 people had repeated measurements. RESULTS: Anxiety declined but depression increased in the cohort after a year of COVID-19 pandemic. Perceived increase in support from family and trade unions, stable employment, and professional mental health support were protective. Depression scores worsened mostly in healthcare, higher education, and manufacturing industries. CONCLUSIONS: We observed that while anxiety dissipated over the first year of COVID-19 pandemic, depression worsened, perhaps more so in some industries and where mental health support faltered over time.

Smokers' utilization of quitting methods and vaping during pregnancy: an empirical cluster analysis of 2016-2018 Pregnancy Risk Assessment Monitoring System (PRAMS) data in seven US states.

BACKGROUND: Patterns of utilization of numerous smoking cessation methods among pregnant women amidst the increasing popularity of vaping (use of e-cigarettes) remains unknown. METHODS: This study included 3,154 mothers who self-reported smoking around the time of conception and delivered live births in 2016-2018 in seven US states. Latent class analysis was used to identify subgroups of smoking women based on their utilization of 10 surveyed quitting methods and vaping during pregnancy. RESULTS: We identified four subgroups of smoking mothers with different utilization patterns of quitting methods during pregnancy: 22.0% reported "not trying to quit"; 61.4% tried to "quit on my own" without any behavioral or pharmacological assistance; 3.7% belonged to the "vaping" subgroup; and 12.9% utilized "wide-ranging methods" with higher use rate of multiple approaches, such as quit line and nicotine patch. Compared to mothers "not trying to quit," the subgroup trying to "quit on my own" were more likely to be abstinent (adjusted OR 4.95, 95% CI 2.82-8.35) or to reduce the number of cigarettes smoked daily (adjusted OR 2.46, 95% CI 1.31-4.60) in late pregnancy, and these improvements lasted into early postpartum. We did not observe a measurable reduction in smoking among the "vaping" subgroup or women trying to quit with "wide-ranging methods". CONCLUSIONS: We identified four subgroups of smoking mothers with different utilization patterns of eleven quitting methods during pregnancy. Pre-pregnancy smokers who tried to "quit on my own" were most likely to be abstinent or to reduce smoking amount.

Prerequisite for Imputing Non-detects among Airborne Samples in OSHA's IMIS Databank: Prediction of Sample's Volume.

INTRODUCTION: The US Integrated Management Information System (IMIS) contains workplace measurements collected by Occupational Safety and Health Administration (OSHA) inspectors. Its use for research is limited by the lack of record of a value for the limit of detection (LOD) associated with non-detected measurements, which should be used to set censoring point in statistical analysis. We aimed to remedy this by developing a predictive model of the volume of air sampled (V) for the non-detected results of airborne measurements, to then estimate the LOD using the instrument detection limit (IDL), as IDL/V. METHODS: We obtained the Chemical Exposure Health Data from OSHA's central laboratory in Salt Lake City that partially overlaps IMIS and contains information on V. We used classification and regression trees (CART) to develop a predictive model of V for all measurements where the two datasets overlapped. The analysis was restricted to 69 chemical agents with at least 100 non-detected measurements, and calculated sampling air flow rates consistent with workplace measurement practices; undefined types of inspections were excluded, leaving 412,201/413,515 records. CART models were fitted on randomly selected 70% of the data using 10-fold cross-validation and validated on the remaining data. A separate CART model was fitted to styrene data. RESULTS: Sampled air volume had a right-skewed distribution with a mean of 357 l, a median (M) of 318, and ranged from 0.040 to 1868 l. There were 173,131 measurements described as non-detects (42% of the data). For the non-detects, the V tended to be greater (M = 378 l) than measurements characterized as either 'short-term' (M = 218 l) or 'long-term' (M = 297 l). The CART models were complex and not easy to interpret, but substance, industry, and year were among the top three most important classifiers. They predicted V well overall (Pearson correlation (r) = 0.73, P < 0.0001; Lin's concordance correlation (rc) = 0.69) and among records captured as non-detects in IMIS (r = 0.66, P < 0.0001l; rc = 0.60). For styrene, CART built on measurements for all agents predicted V among 569 non-detects poorly (r = 0.15; rc = 0.04), but styrene-specific CART predicted it well (r = 0.87, P < 0.0001; rc = 0.86). DISCUSSION: Among the limitations of our work is the fact that samples may have been collected on different workers and processes within each inspection, each with its own V. Furthermore, we lack measurement-level predictors because classifiers were captured at the inspection level. We did not study all substances that may be of interest and did not use the information that substances measured on the same sampling media should have the same V. We must note that CART models tend to over-fit data and their predictions depend on the selected data, as illustrated by contrasting predictions created using all data vs. limited to styrene. CONCLUSIONS: We developed predictive models of sampled air volume that should enable the calculation of LOD for non-detects in IMIS. Our predictions may guide future work on handling non-detects in IMIS, although it is advisable to develop separate predictive models for each substance, industry, and year of interest, while also considering other factors, such as whether the measurement evaluated long-term or short-term exposure.

The evolution of workplace risk for Covid-19 in Canadian healthcare workers and its relation to vaccination: A nested case-referent study.

BACKGROUND: During the early months of the Covid-19 pandemic, studies demonstrated that healthcare workers (HCWs) were at increased risk of infection. Few modifiable risks were identified. It is largely unknown how these evolved over time. METHODS: A prospective case-referent study was established and nested within a cohort study of Canadian HCWs. Cases of Covid-19, confirmed by polymerase chain reaction, were matched with up to four referents on job, province, gender, and date of first vaccination. Cases and referents completed a questionnaire reporting exposures and experiences in the 21 days before case date. Participants were recruited from October 2020 to March 2022. Workplace factors were examined by mixed-effects logistic regression allowing for competing exposures. A sensitivity analysis was limited to those for whom family/community transmission seemed unlikely. RESULTS: 533 cases were matched with 1697 referents. Among unvaccinated HCWs, the risk of infection was increased if they worked hands-on with patients with Covid-19, on a ward designated for care of infected patients, or handled objects used by infected patients. Sensitivity analysis identified work in residential institutions and geriatric wards as high risk for unvaccinated HCWs. Later, with almost universal HCW vaccination, risk from working with infected patients was much reduced but cases were more likely than referents to report being unable to access an N95 mask or that decontaminated N95 masks were reused. CONCLUSIONS: These results suggest that, after a rocky start, the risks of Covid-19 infection from work in health care are now largely contained in Canada but with need for continued vigilance.

Automated Coding of Job Descriptions From a General Population Study: Overview of Existing Tools, Their Application and Comparison.

OBJECTIVES: Automatic job coding tools were developed to reduce the laborious task of manually assigning job codes based on free-text job descriptions in census and survey data sources, including large occupational health studies. The objective of this study is to provide a case study of comparative performance of job coding and JEM (Job-Exposure Matrix)-assigned exposures agreement using existing coding tools. METHODS: We compared three automatic job coding tools [AUTONOC, CASCOT (Computer-Assisted Structured Coding Tool), and LabourR], which were selected based on availability, coding of English free-text into coding systems closely related to the 1988 version of the International Standard Classification of Occupations (ISCO-88), and capability to perform batch coding. We used manually coded job histories from the AsiaLymph case-control study that were translated into English prior to auto-coding to assess their performance. We applied two general population JEMs to assess agreement at exposure level. Percent agreement and PABAK (Prevalence-Adjusted Bias-Adjusted Kappa) were used to compare the agreement of results from manual coders and automatic coding tools. RESULTS: The coding per cent agreement among the three tools ranged from 17.7 to 26.0% for exact matches at the most detailed 4-digit ISCO-88 level. The agreement was better at a more general level of job coding (e.g. 43.8-58.1% in 1-digit ISCO-88), and in exposure assignments (median values of PABAK coefficient ranging 0.69-0.78 across 12 JEM-assigned exposures). Based on our testing data, CASCOT was found to outperform others in terms of better agreement in both job coding (26% 4-digit agreement) and exposure assignment (median kappa 0.61). CONCLUSIONS: In this study, we observed that agreement on job coding was generally low for the three tools but noted a higher degree of agreement in assigned exposures. The results indicate the need for study-specific evaluations prior to their automatic use in general population studies, as well as improvements in the evaluated automatic coding tools.

Duration of employment within occupations and incident stroke in a US general population cohort 45 years of age or older (REGARDS study).

BACKGROUND: The work environment can contribute to the risk of cardiovascular diseases (CVD) including stroke. Our objective was to identify occupations with elevated risk of stroke within the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort. METHODS: We analyzed incident stroke outcomes (ischemic and hemorrhagic strokes) from 2003 to 2020 and employment characteristics of 13,659 adults aged ≥45 years enrolled in a national population-based cohort study. Using a modified Poisson regression approach, we estimated the relative risks (RRs) and the associated 95% confidence intervals (CI) of stroke in relation to years of employment within each occupation coded using the US Census two-digit Standard Occupation Code. Models were adjusted for Framingham Stroke Risk Score, region, race, age, and body mass index. We conducted stratified analysis by sex, employment time period (pre-1975 vs. post-1975), and region. RESULTS: Workers in the following occupations had a greater risk of stroke with longer duration of employment (per decade): protective service (RR: 2.35, 95% CI: 1.11, 4.97), food preparation and service (RR: 1.51, 95% CI: 1.05, 2.19), and transportation and material moving (RR: 1.30, 95% CI: 1.00, 1.69). The stroke risk in these occupations was disproportionately elevated in men, and differed by region and employment time period. CONCLUSIONS: Longer employment in protective service, food preparation and serving, and transportation and materials moving occupations may increase the risk of stroke. Surveillance may uncover specific work-related risk factors in these occupations, leading to interventions to reduce the burden of stroke among US workers.

Association of polycyclic aromatic hydrocarbons in moss with blood biomarker among nearby residents in Portland, Oregon.

Polycyclic aromatic hydrocarbons (PAHs) are air pollutants that are costly to measure using traditional air-quality monitoring methods. We used an epiphytic bio-indicator (moss genus: Orthotrichum) to cost-effectively evaluate atmospheric deposition of PAHs in Portland, Oregon in May 2013. However, it is unclear if measurements derived from these bioindicators are good proxies for human exposure. To address this question, we simultaneously, measured PAH-DNA adducts in blood samples of non-smokers residing close to the sites of moss measurements. We accounted for individual determinants of PAH uptake that are not related to environmental air quality through questionnaires, e.g., wood fires, consumption of barbecued and fried meats. Spearman rank correlation and linear regression (to control for confounders from the lifestyle factors) evaluated the associations. We did not observe evidence of an association between PAH levels in moss and PAH-DNA adducts in blood of nearby residents (e.g., all correlations p≥0.5), but higher level of adducts were evident in those who used wood fire in their houses in the last 48 hours. It remains to be determined whether bio-indicators in moss can be used for human health risk assessment.

Data Quality in Electronic Health Record Research: An Approach for Validation and Quantitative Bias Analysis for Imperfectly Ascertained Health Outcomes Via Diagnostic Codes.

It is incumbent upon all researchers who use the electronic health record (EHR), including data scientists, to understand the quality of such data. EHR data may be subject to measurement error or misclassification that have the potential to bias results, unless one applies the available computational techniques specifically created for this problem. In this article, we begin with a discussion of data-quality issues in the EHR focusing on health outcomes. We review the concepts of sensitivity, specificity, positive and negative predictive values, and demonstrate how the imperfect classification of a dichotomous outcome variable can bias an analysis, both in terms of prevalence of the outcome, and relative risk of the outcome under one treatment regime (aka exposure) compared to another. This is then followed by a description of a generalizable approach to probabilistic (quantitative) bias analysis using a combination of regression estimation of the parameters that relate the true and observed data and application of these estimates to adjust the prevalence and relative risk that may have existed if there was no misclassification. We describe bias analysis that accounts for both random and systematic errors and highlight its limitations. We then motivate a case study with the goal of validating the accuracy of a health outcome, chronic infection with hepatitis C virus, derived from a diagnostic code in the EHR. Finally, we demonstrate our approaches on the case study and conclude by summarizing the literature on outcome misclassification and quantitative bias analysis.

Pride and adversity among nurses and physicians during the pandemic in two US healthcare systems: a mixed methods analysis.

BACKGROUND: Our aims were to examine themes of the most difficult or distressing events reported by healthcare workers during the first wave of COVID-19 pandemic in two US health care systems in order to identify common themes and then to relate them to both behavioral theory and measures of anxiety and depression. METHODS: We conducted a cross-sectional survey of nurses and physicians during the early phases of the COVID-19 pandemic in the US. An emailed recruitment letter was sent, with about half choosing to supply open-ended responses relevant to thematic analysis. We measured symptoms of anxiety and depression separately, captured demographics, and asked two open-ended questions regarding events that were the most difficult or stressful, and reinforced pride. We reported descriptive statistics and coded thematic categories for their continuum "pride" and "distress" the factors related to fostering well-being according to the Self-Determination Theory. RESULTS: Themes that emerged from these narratives were congruent with prediction of Self-Determination theory that autonomy-supportive experiences will foster pride, while autonomy-thwarting experiences will cause distress. Those who reported distressful events were more anxious and depressed compared to those who did not. Among those who reported incidences that reinforced pride in the profession, depression was rarer compared to those who did not. These trends were evident after allowing for medical history and other covariates in logistic regressions. CONCLUSION: Causal claims from our analysis should be made with caution due to the cross-sectional research design. Understanding perceptions of the pandemic by nurses and physicians may help identify and manage sources of distress, and suggest means of mitigating the risk of mental health distress through autonomy-supportive policies.

Exposure-response analysis of the association of maternal smoking and use of electronic cigarettes (vaping) in relation to preterm birth and small-for-gestational-age in a national US sample, 2016-2018.

Introduction: The US experienced a surge in use of e-cigarettes. Smoking women may consider e-cigarettes during pregnancy as an alternative to smoking. E-cigarettes typically contain nicotine, an established cause of reduction in fetal growth in animal studies. Methods: This cohort study included 99,201 mothers who delivered live singletons in 2016-2018 from the Pregnancy Risk Assessment Monitoring System. We created exposure categories based on self-reported number of cigarettes smoked per day and vaping frequency and evaluated their associations with preterm birth and small-for-gestational-age (SGA) birth (two established cigarette smoking-related risks). Results: Dual users in late pregnancy were a heterogeneous group: 29% lightly smoked and occasionally vaped; 19% lightly smoked and frequently vaped; 36% heavily smoked and occasionally vaped; and 15% heavily smoked and frequently vaped. While dual users who heavily smoked and occasionally vaped had the highest adjusted OR for SGA (3.4, 95% CI 2.0, 5.7), all the dual users had, on average, about twice the odds of having SGA than non-users. While the risks of preterm birth were higher among sole light smokers (adjusted OR 1.3, 95% CI 1.1, 1.5) and sole heavy smokers (adjusted OR 1.5. 95% CI 1.2, 1.8) than non-users, the adjusted odds of preterm birth for dual users were not noticeably higher than those of non-users. Conclusion: Relative to non-users, both smoking and vaping during pregnancy appear to increase risk of SGA, but excess risk of preterm birth appears to be primarily attributable to smoking alone. Higher levels of exposure tended to confer more risk.