Synergistic and Non-synergistic Associations for Cigarette Smoking and Non-tobacco Risk Factors for Cardiovascular Disease Incidence in the Atherosclerosis Risk In Communities (ARIC) Study

Cigarette smoking, various metabolic and lipid-related factors and hypertension are well-recognized cardiovascular disease (CVD) risk factors. Since smoking affects many of these factors, use of a single imprecise smoking metric, e.g., ever or never smoked, may allow residual confounding and explain inconsistencies in current assessments of interactions. Using a comprehensive model in pack-years and cigarettes/day for the complex smoking-related relative risk (RR) of CVD to reduce residual confounding, we evaluated interactions with non-tobacco risk factors, including additive (non-synergistic) and multiplicative (synergistic) forms. Data were from the prospective Atherosclerosis Risk in Communities (ARIC) Study from four areas of the U.S. recruited in 1987-89 with follow-up through 2008. Analyses included 14,127 participants, 207,693 person-years and 2,857 CVD events. Analyses revealed distinct interactions with smoking: including statistical consistency with additive (body mass index, waist to hip ratio, diabetes mellitus, glucose, insulin, high density lipoproteins [HDL] and HDL(2)); and multiplicative (hypertension, total cholesterol, low density lipoproteins, apolipoprotein B, total cholesterol to HDL ratio and HDL(3)) associations, as well as indeterminate (apolipoprotein A-I and triglycerides) associations. The forms of the interactions were revealing but require confirmation. Improved understanding of joint associations may help clarify the public health burden of smoking for CVD, links between etiologic factors and biological mechanisms, and the consequences of joint exposures, whereby synergistic associations highlight joint effects and non-synergistic associations suggest distinct contributions. Joint associations for cigarette smoking and non-tobacco risk factors were distinct, revealing synergistic/multiplicative (hypertension, TC, LDL, apoB, TC/HDL, HDL(3)), non-synergistic/additive (BMI, WHR, DM, glucose, insulin, HDL, HDL(2)) and indeterminate (apoA-I and TRIG) associations. If confirmed, these results may help better define the public health burden of smoking on CVD risk and identify links between etiologic factors and biologic mechanisms, where synergistic associations highlight joint impacts and non-synergistic associations suggest distinct contributions from each factor

Висновок експерта в криміналістичних технологіях

Досліджується висновок експерта в аспекті технологій експертних та технологій слідчих. Встановлюються умови технологічності цього процесуального документу. Конкретизуються критерії та дії експерта з забезпечення процесуальних вимог при складанні висновку за результатами проведених досліджень, та операції з оцінки висновку експерта слідчим.Исследуется заключение эксперта в аспекте технологий экспертных и технологий следственных. Устанавливаются условия технологичности этого процессуального документа. Конкретизируются критерии и действия эксперта по обеспечению процессуальных требований при составлении заключения по результатам проведенных исследований, и операции по оценке заключения эксперта следователем.The expert's conclusion is investigated in the aspect of expertise technologies and investigation technologies . The conditions for manufacturability of this procedural document are established. The criteria and expert's actions providing the procedural requirements while preparation of the report on the research results, and the operation on the assessment of the expert conclusion by investigator are concretized

The Diesel Exhaust in Miners Study: V. Evaluation of the Exposure Assessment Methods

Exposure to respirable elemental carbon (REC), a component of diesel exhaust (DE), was assessed for an epidemiologic study investigating the association between DE and mortality, particularly from lung cancer, among miners at eight mining facilities from the date of dieselization (1947–1967) through 1997. To provide insight into the quality of the estimates for use in the epidemiologic analyses, several approaches were taken to evaluate the exposure assessment process and the quality of the estimates. An analysis of variance was conducted to evaluate the variability of 1998–2001 REC measurements within and between exposure groups of underground jobs. Estimates for the surface exposure groups were evaluated to determine if the arithmetic means (AMs) of the REC measurements increased with increased proximity to, or use of, diesel-powered equipment, which was the basis on which the surface groups were formed. Estimates of carbon monoxide (CO) (another component of DE) air concentrations in 1976–1977, derived from models developed to predict estimated historical exposures, were compared to 1976–1977 CO measurement data that had not been used in the model development. Alternative sets of estimates were developed to investigate the robustness of various model assumptions. These estimates were based on prediction models using: (i) REC medians rather AMs, (ii) a different CO:REC proportionality than a 1:1 relation, and (iii) 5-year averages of historical CO measurements rather than modeled historical CO measurements and DE-related determinants. The analysis of variance found that in three of the facilities, most of the between-group variability in the underground measurements was explained by the use of job titles. There was relatively little between-group variability in the other facilities. The estimated REC AMs for the surface exposure groups rose overall from 1 to 5 μg m−3 as proximity to, and use of, diesel equipment increased. The alternative estimates overall were highly correlated (∼0.9) with the primary set of estimates. The median of the relative differences between the 1976–1977 CO measurement means and the 1976–1977 estimates for six facilities was 29%. Comparison of estimated CO air concentrations from the facility-specific prediction models with historical CO measurement data found an overall agreement similar to that observed in other epidemiologic studies. Other evaluations of components of the exposure assessment process found moderate to excellent agreement. Thus, the overall evidence suggests that the estimates were likely accurate representations of historical personal exposure levels to DE and are useful for epidemiologic analyses

The Diesel Exhaust in Miners Study: IV. Estimating Historical Exposures to Diesel Exhaust in Underground Non-metal Mining Facilities

We developed quantitative estimates of historical exposures to respirable elemental carbon (REC) for an epidemiologic study of mortality, including lung cancer, among diesel-exposed miners at eight non-metal mining facilities [the Diesel Exhaust in Miners Study (DEMS)]. Because there were no historical measurements of diesel exhaust (DE), historical REC (a component of DE) levels were estimated based on REC data from monitoring surveys conducted in 1998–2001 as part of the DEMS investigation. These values were adjusted for underground workers by carbon monoxide (CO) concentration trends in the mines derived from models of historical CO (another DE component) measurements and DE determinants such as engine horsepower (HP; 1 HP = 0.746 kW) and mine ventilation. CO was chosen to estimate historical changes because it was the most frequently measured DE component in our study facilities and it was found to correlate with REC exposure. Databases were constructed by facility and year with air sampling data and with information on the total rate of airflow exhausted from the underground operations in cubic feet per minute (CFM) (1 CFM = 0.0283 m3 min−1), HP of the diesel equipment in use (ADJ HP), and other possible determinants. The ADJ HP purchased after 1990 (ADJ HP1990+) was also included to account for lower emissions from newer, cleaner engines. Facility-specific CO levels, relative to those in the DEMS survey year for each year back to the start of dieselization (1947–1967 depending on facility), were predicted based on models of observed CO concentrations and log-transformed (Ln) ADJ HP/CFM and Ln(ADJ HP1990+). The resulting temporal trends in relative CO levels were then multiplied by facility/department/job-specific REC estimates derived from the DEMS surveys personal measurements to obtain historical facility/department/job/year-specific REC exposure estimates. The facility-specific temporal trends of CO levels (and thus the REC estimates) generated from these models indicated that CO concentrations had been generally greater in the past than during the 1998–2001 DEMS surveys, with the highest levels ranging from 100 to 685% greater (median: 300%). These levels generally occurred between 1970 and the early 1980s. A comparison of the CO facility-specific model predictions with CO air concentration measurements from a 1976–1977 survey external to the modeling showed that our model predictions were slightly lower than those observed (median relative difference of 29%; range across facilities: 49 to –25%). In summary, we successfully modeled past CO concentration levels using selected determinants of DE exposure to derive retrospective estimates of REC exposure. The results suggested large variations in REC exposure levels both between and within the underground operations of the facilities and over time. These REC exposure estimates were in a plausible range and were used in the investigation of exposure–response relationships in epidemiologic analyses

Lung Cancer and Occupation in a Population-based Case-Control Study

The authors examined the relation between occupation and lung cancer in the large, population-based Environment And Genetics in Lung cancer Etiology (EAGLE) case-control study. In 2002–2005 in the Lombardy region of northern Italy, 2,100 incident lung cancer cases and 2,120 randomly selected population controls were enrolled. Lifetime occupational histories (industry and job title) were coded by using standard international classifications and were translated into occupations known (list A) or suspected (list B) to be associated with lung cancer. Smoking-adjusted odds ratios and 95% confidence intervals were calculated with logistic regression. For men, an increased risk was found for list A (177 exposed cases and 100 controls; odds ratio = 1.74, 95% confidence interval: 1.27, 2.38) and most occupations therein. No overall excess was found for list B with the exception of filling station attendants and bus and truck drivers (men) and launderers and dry cleaners (women). The authors estimated that 4.9% (95% confidence interval: 2.0, 7.8) of lung cancers in men were attributable to occupation. Among those in other occupations, risk excesses were found for metal workers, barbers and hairdressers, and other motor vehicle drivers. These results indicate that past exposure to occupational carcinogens remains an important determinant of lung cancer occurrence

Epidemiologic Evaluation of Measurement Data in the Presence of Detection Limits

Quantitative measurements of environmental factors greatly improve the quality of epidemiologic studies but can pose challenges because of the presence of upper or lower detection limits or interfering compounds, which do not allow for precise measured values. We consider the regression of an environmental measurement (dependent variable) on several covariates (independent variables). Various strategies are commonly employed to impute values for interval-measured data, including assignment of one-half the detection limit to nondetected values or of “fill-in” values randomly selected from an appropriate distribution. On the basis of a limited simulation study, we found that the former approach can be biased unless the percentage of measurements below detection limits is small (5–10%). The fill-in approach generally produces unbiased parameter estimates but may produce biased variance estimates and thereby distort inference when 30% or more of the data are below detection limits. Truncated data methods (e.g., Tobit regression) and multiple imputation offer two unbiased approaches for analyzing measurement data with detection limits. If interest resides solely on regression parameters, then Tobit regression can be used. If individualized values for measurements below detection limits are needed for additional analysis, such as relative risk regression or graphical display, then multiple imputation produces unbiased estimates and nominal confidence intervals unless the proportion of missing data is extreme. We illustrate various approaches using measurements of pesticide residues in carpet dust in control subjects from a case–control study of non-Hodgkin lymphoma

Retro American

Diesel exhaust is a suggested risk factor for ischemic heart disease (IHD), but evidence from cohorts using quantitative exposure metrics is limited. We examined the impact of respirable elemental carbon (REC), a key surrogate for diesel exhaust, and respirable dust (RD) on IHD mortality, using data from the Diesel Exhaust in Miners Study in the United States. Using data from a cohort of male workers followed from 1948–1968 until 1997, we fitted Cox proportional hazards models to estimate hazard ratios for IHD mortality for cumulative and average intensity of exposure to REC and RD. Segmented linear regression models allowed for nonmonotonicity. Hazard ratios for cumulative and average REC exposure declined relative to the lowest exposure category before increasing to 0.79 and 1.25, respectively, in the highest category. Relative to the category containing the segmented regression change points, hazard ratios for the highest category were 1.69 and 1.54 for cumulative and average REC exposure, respectively. Hazard ratios for RD exposure increased across the full exposure range to 1.33 and 2.69 for cumulative and average RD exposure, respectively. Tests for trend were statistically significant for cumulative REC exposure (above the change point) and for average RD exposure. Our findings suggest excess risk of IHD mortality in relation to increased exposure to REC and RD. © 2018 Oxford University Press. All Rights Reserved

Estimating Water Supply Arsenic Levels in the New England Bladder Cancer Study

Background: Ingestion of inorganic arsenic in drinking water is recognized as a cause of bladder cancer when levels are relatively high (≥ 150 µg/L). The epidemiologic evidence is less clear at the low-to-moderate concentrations typically observed in the United States. Accurate retrospective exposure assessment over a long time period is a major challenge in conducting epidemiologic studies of environmental factors and diseases with long latency, such as cancer. Objective: We estimated arsenic concentrations in the water supplies of 2,611 participants in a population-based case–control study in northern New England. Methods: Estimates covered the lifetimes of most study participants and were based on a combination of arsenic measurements at the homes of the participants and statistical modeling of arsenic concentrations in the water supply of both past and current homes. We assigned a residential water supply arsenic concentration for 165,138 (95%) of the total 173,361 lifetime exposure years (EYs) and a workplace water supply arsenic level for 85,195 EYs (86% of reported occupational years). Results: Three methods accounted for 93% of the residential estimates of arsenic concentration: direct measurement of water samples (27%; median, 0.3 µg/L; range, 0.1–11.5), statistical models of water utility measurement data (49%; median, 0.4 µg/L; range, 0.3–3.3), and statistical models of arsenic concentrations in wells using aquifers in New England (17%; median, 1.6 µg/L; range, 0.6–22.4). Conclusions: We used a different validation procedure for each of the three methods, and found our estimated levels to be comparable with available measured concentrations. This methodology allowed us to calculate potential drinking water exposure over long periods

Atrazine and cancer incidence among pesticide applicators in the agricultural health study (1994-2007).

Atrazine is a triazine herbicide used widely in the United States. Although it is an animal carcinogen, the mechanism in rodents does not appear to operate in humans. Few epidemiologic studies have provided evidence for an association