Hypothetical exposure limits for oil-based metalworking fluids and cardiovascular mortality in a cohort of autoworkers: structural accelerated failure time models in a public health framework

Cardiovascular disorders and exposure to chemical pollutants

Introduction

Exposure with some chemical can cause cardiovascular disorders. Occupational exposures with chemicals are modifiable risk factors for cardiovascular diseases. The Objective of this study was the determination of cardiovascular disorders in industries with occupational exposures.

Materials and methods

Study was a cross-sectional method and was done on workers of related industries. The study was done with a physical examination and checklist by getting health and illness history and clinical tests about the risk factors and cardiovascular disorders. According to exposures the population of the study was divided into 3 groups. Data were analyzed with SPSS 16, by considering p < 0.05 as significant.

Results

The frequency of unstable angina and stable angina were the most in group 1. The relative risk for unstable angina was 1.55 (1.46-1.61) in group 1 and for stable angina was 1.54 (1.47-1.62) in this group. The risk of thrombophlebitis was 8.48 (7.07-10.17) in group 2.

Conclusions

Workers in industry with chemical pollutants had cardiovascular disorders. The occupational exposures, especially chemical agents are effective on cardiovascular system.

Circadian epidemiology: Structuring circadian causes of disease and practical implications

That disruptions of the body's internal clockwork can lead to negative health consequences, including cancer, is a plausible hypothesis. Yet, despite strong mechanistic and animal support, the International Agency for Research on Cancer (IARC) experts considered epidemiological evidence as limited regarding the carcinogenicity of "shift-work involving circadian disruption" (2007) and "night shift work" (2019). We use directed acyclic graphs (DAGs) to outline a concept of circadian causes that discloses challenges when choosing appropriate exposure variables. On this basis, we propose to move beyond shift-work alone as a direct cause of disease. Instead, quantifying chronodisruption as individual doses can lead to interpretable circadian epidemiology. The hypothesis is that doses of chronodisruption cause disrupted circadian organisation by leading to desynchronization of circadian rhythms. Chronodisruption can be conceptualized as the split physiological nexus of internal and external times. Biological (or internal) night - an individual's intrinsically favoured sleep time window - could be the backbone of circadian epidemiology. In practice, individual doses that cause disrupted circadian organisation are derived from the intersection of time intervals of being awake and an individual's biological night. After numerous studies counted work shifts, chronobiology may now advance circadian epidemiology with more specific dose estimation - albeit with greater challenges in measurement (time-dependent individual data) and analysis (time-dependent confounding).

Metalworking Fluid Exposure and Stroke Mortality Among US Autoworkers

Although air pollution is an important risk factor for stroke, few studies have considered the impact of workplace exposure to particulate matter (PM). We examined implications of exposure to PM composed of metalworking fluids (MWFs) for stroke mortality in the United Autoworkers-General Motors cohort. Cox proportional hazards models with age as the timescale were used to estimate the association of cumulative straight, soluble, and synthetic MWF exposure with stroke mortality, controlling for sex, race, plant, calendar year, and hire year. Among 38,553 autoworkers followed during 1941-1995, we identified 114 ischemic stroke deaths and 113 hemorrhagic stroke deaths. Overall stroke mortality risk was increased among workers in the middle exposure category for straight MWF (hazard ratio (HR) = 1.31, 95% confidence interval (CI): 0.87, 1.98) and workers in the highest exposure category for synthetic MWF (HR = 1.94, 95% CI: 1.13, 3.16) compared with workers who had no direct exposure. Ischemic stroke mortality risk was increased among workers in the highest exposure categories for straight MWF (HR = 1.45, 95% CI: 0.83, 2.52) and synthetic MWF (HR = 2.39, 95% CI: 1.39, 4.50). We observed no clear relationship between MWF exposure and hemorrhagic stroke mortality. Our results support a potentially important role for occupational PM exposures in stroke mortality and indicate the need for further studies of PM exposure and stroke in varied occupational settings.

Lung Cancer Mortality and Styrene Exposure in the Reinforced-Plastics Boatbuilding Industry: Evaluation of Healthy Worker Survivor Bias

The evidence for styrene's being a human lung carcinogen has been inconclusive. Occupational cohorts within the reinforced-plastics industry are an ideal population in which to study this association because of their relatively high levels of exposure to styrene and lack of concomitant exposures to other known carcinogens. However, healthy worker survivor bias (HWSB), where healthier workers stay employed longer and thus have higher exposure potential, is a likely source of confounding bias for exposure-response associations, in part due to styrene's acute effects. Through December 31, 2016, we studied a cohort of 5,163 boatbuilders exposed to styrene in Washington State who were employed between 1959 and 1978; prior regression analyses had demonstrated little evidence for an exposure-response relationship between styrene exposure and lung cancer mortality. Based on estimates of necessary components of HWSB, we found evidence for a potentially large HWSB. Using g-estimation of a structural nested model to account for HWSB, we estimated that 1 year of styrene exposure at more than 30 parts per million accelerated time to lung cancer death by 2.29 years (95% confidence interval: 1.53, 2.94). Our results suggest possibly strong HWSB in our small cohort and indicate that large, influential studies of styrene-exposed workers may suffer from similar biases, warranting a reassessment of the evidence of long-term health effects of styrene exposure.

Circulating purification of cutting fluid: an overview

Cutting fluid has cooling and lubricating properties and is an important part of the field of metal machining. Owing to harmful additives, base oils with poor biodegradability, defects in processing methods, and unreasonable emissions of waste cutting fluids, cutting fluids have serious pollution problems, which pose challenges to global carbon emissions laws and regulations. However, the current research on cutting fluid and its circulating purification technique lacks systematic review papers to provide scientific technical guidance for actual production. In this study, the key scientific issues in the research achievements of eco-friendly cutting fluid and waste fluid treatment are clarified. First, the preparation and mechanism of organic additives are summarized, and the influence of the physical and chemical properties of vegetable base oils on lubricating properties is analyzed. Then, the process characteristics of cutting fluid reduction supply methods are systematically evaluated. Second, the treatment of oil mist and miscellaneous oil, the removal mechanism and approach of microorganisms, and the design principles of integrated recycling equipment are outlined. The conclusion is concluded that the synergistic effect of organic additives, biodegradable vegetable base oils and recycling purification effectively reduces the environmental pollution of cutting fluids. Finally, in view of the limitations of the cutting fluid and its circulating purification technique, the prospects of amino acid additive development, self-adapting jet parameter supply system, matching mechanism between processing conditions and cutting fluid are put forward, which provides the basis and support for the engineering application and development of cutting fluid and its circulating purification.

Fitting Marginal Structural and G-Estimation Models Under Complex Treatment Patterns: Investigating the Association Between De Novo Vitamin D Supplement Use After Breast Cancer Diagnosis and All-Cause Mortality Using Linked Pharmacy Claim and Registry Data

Studies have shown that accounting for time-varying confounding through time-dependent Cox proportional hazards models may provide biased estimates of the causal effect of treatment when the confounder is also a mediator. We explore 2 alternative approaches to addressing this problem while examining the association between vitamin D supplementation initiated after breast cancer diagnosis and all-cause mortality. Women aged 50-80 years were identified in the National Cancer Registry Ireland (n = 5,417) between 2001 and 2011. Vitamin D use was identified from linked prescription data (n = 2,570). We sought to account for the time-varying nature of vitamin D use and time-varying confounding by bisphosphonate use using 1) marginal structural models (MSMs) and 2) G-estimation of structural nested accelerated failure-time models (SNAFTMs). Using standard adjusted Cox proportional hazards models, we found a reduction in all-cause mortality in de novo vitamin D users compared with nonusers (hazard ratio (HR) = 0.84, 95% confidence interval (CI): 0.73, 0.99). Additional adjustment for vitamin D and bisphosphonate use in the previous month reduced the hazard ratio (HR = 0.45, 95% CI: 0.33, 0.63). Results derived from MSMs (HR = 0.44, 95% CI: 0.32, 0.61) and SNAFTMs (HR = 0.45, 95% CI: 0.34, 0.52) were similar. Utilizing MSMs and SNAFTMs to account for time-varying bisphosphonate use did not alter conclusions in this example.

The Healthy Worker Survivor Effect: Target Parameters and Target Populations

PURPOSE OF REVIEW

We offer an in-depth discussion of the time-varying confounding and selection bias mechanisms that give rise to the healthy worker survivor effect (HWSE).

RECENT FINDINGS

In this update of an earlier review, we distinguish between the mechanisms collectively known as the HWSE and the statistical bias that can result. This discussion highlights the importance of identifying both the target parameter and the target population for any research question in occupational epidemiology. Target parameters can correspond to hypothetical workplace interventions; we explore whether these target parameters' true values reflect the etiologic effect of an exposure on an outcome or the potential impact of enforcing an exposure limit in a more realistic setting. If a cohort includes workers hired before the start of follow-up, HWSE mechanisms can limit the transportability of the estimates to other target populations. We summarize recent publications that applied g-methods to control for the HWSE, focusing on their target parameters, target populations, and hypothetical interventions.

Straight Metalworking Fluids and All-Cause and Cardiovascular Mortality Analyzed by Using G-Estimation of an Accelerated Failure Time Model With Quantitative Exposure: Methods and Interpretations

Straight metalworking fluids have been linked to cardiovascular mortality in analyses using binary exposure metrics, accounting for healthy worker survivor bias by using g-estimation of accelerated failure time models. A cohort of 38,666 Michigan autoworkers was followed (1941-1994) for mortality from all causes and ischemic heart disease. The structural model chosen here, using continuous exposure, assumes that increasing exposure from 0 to 1 mg/m(3) in any single year would decrease survival time by a fixed amount. Under that assumption, banning the fluids would have saved an estimated total of 8,468 (slope-based 95% confidence interval: 2,262, 28,563) person-years of life in this cohort. On average, 3.04 (slope-based 95% confidence interval: 0.02, 25.98) years of life could have been saved for each exposed worker who died from ischemic heart disease. Estimates were sensitive to both model specification for predicting exposure (multinomial or logistic regression) and characterization of exposure as binary or continuous in the structural model. Our results provide evidence supporting the hypothesis of a detrimental relationship between straight metalworking fluids and mortality, particularly from ischemic heart disease, as well as an instructive example of the challenges in obtaining and interpreting results from accelerated failure time models using a continuous exposure in the presence of competing risks.

Occupational Diesel Exposure, Duration of Employment, and Lung Cancer: An Application of the Parametric G-Formula

BACKGROUND

If less healthy workers terminate employment earlier, thus accumulating less exposure, yet remain at greater risk of the health outcome, estimated health effects of cumulative exposure will be biased downward. If exposure also affects termination of employment, then the bias cannot be addressed using conventional methods. We examined these conditions as a prelude to a reanalysis of lung cancer mortality in the Diesel Exhaust in Miners Study.

METHODS

We applied an accelerated failure time model to assess the effect of exposures to respirable elemental carbon (a surrogate for diesel) on time to termination of employment among nonmetal miners who ever worked underground (n = 8,307). We then applied the parametric g-formula to assess how possible interventions setting respirable elemental carbon exposure limits would have changed lifetime risk of lung cancer, adjusting for time-varying employment status.

RESULTS

Median time to termination was 36% shorter (95% confidence interval = 33%, 39%), per interquartile range width increase in respirable elemental carbon exposure. Lung cancer risk decreased with more stringent interventions, with a risk ratio of 0.8 (95% confidence interval = 0.5, 1.1) comparing a limit of ≤25 µg/m respirable elemental carbon to no intervention. The fraction of cases attributable to diesel exposure was 27% in this population.

CONCLUSIONS

The g-formula controlled for time-varying confounding by employment status, the signature of healthy worker survivor bias, which was also affected by diesel exposure. It also offers an alternative approach to risk assessment for estimating excess cumulative risk, and the impact of interventions based entirely on an observed population.

Invited commentary: Estimating population impact in the presence of competing events

The formal approach in the field of causal inference has enabled epidemiologists to clarify several complications that arise when estimating the effect of an intervention on a health outcome of interest. When the outcome is a failure time or longitudinal process, researchers must often deal with competing events. In this issue of the Journal, Picciotto et al. (Am J Epidemiol. 2015;181(8):563-570) use structural nested failure time models to assess potential population effects of hypothetical interventions and censor competing events. In the present commentary, we discuss 2 interpretations that result from treating competing events as censored observations and how they relate to measures of public health impact. We also comment on 2 alternative approaches for handling competing events: an inverse probability weighting estimator of the survivor average causal effect and the parametric g-formula, which can be used to estimate a functional of the subdistribution of the event of interest. We argue that careful consideration of the tradeoff between the interpretation of the parameters from each approach and the assumptions required to estimate these parameters should guide researchers on the various ways to handle competing events in epidemiologic research.