Background Polycyclic aromatic hydrocarbons (PAHs) are potent atmospheric pollutants produced by incomplete combustion of organic materials. Pre-clinical and occupational studies have reported a positive association of PAHs with oxidative stress, inflammation and subsequent development of atherosclerosis, a major underlying risk factor for cardiovascular disease (CVD). The aim of the current study is to estimate the association between levels of PAH biomarkers and CVD in a national representative sample of United States (US) adults. Methods We examined adult participants (≥20 years of age) from the merged US National Health and Nutrition Examination Survey 2001–2010. Logistic regression models were used to estimate the associations of each urinary PAH biomarker and CVD. Post-exploratory structural equation modeling was then used to address the interdependent response variables (angina, heart attack, stroke and coronary heart disease) as well as the interdependencies of PAH biomarkers. Results PAH biomarkers were positively associated with cardiovascular disease in multiple logistic regression models, although some associations were not statistically robust. Using structural equation modelling, latent PAH exposure variable was positively associated with latent CVD level variable in the multivariable adjusted model (β = 0.12; 95% CI: 0.03, 0.20). Conclusion A modest association between levels of PAH biomarkers and CVD was detected in US adults. Further prospective studies with adequate sample size are needed to replicate or refute our findings.
Background Polycyclic aromatic hydrocarbons (PAHs) are potent atmospheric pollutants, occurring from anthropogenic and natural sources. Several animal studies have reported a positive association of PAHs with inflammation. However, it is not clear if lower background exposure to PAHs is associated with inflammation in humans, independent of smoking, a major source of PAHs. Methods We examined participants from the National Health and Nutrition Examination Survey 2001– 2002, 2003–2004, and 2005–2006. Our exposures of interest were eight urinary monohydroxy polycyclic aromatic hydrocarbon biomarkers. Our outcomes were serum markers of inflammation; C-reactive protein (CRP) (≤10 mg/L) and total white blood cell (WBC) count (4000–12,000 cells/µL). Results Compared to participants with summed biomarkers of low-molecular weight (LMW) PAHs in the lowest quartile, the multivariable odds ratios (95% confidence interval) of high serum CRP (≥3 mg/L) and high total WBC count (defined as at or above the 95 percentile of total WBC distribution) among participants in the highest exposure quartile were 1.77 (1.13, 2.76) and 1.34 (1.12, 1.60) respectively. Urinary 1-hydroxypyrene, the biomarker of the higher molecular weight pyrene, was positively associated with total WBC count, and to lesser extent with serum CRP. In subsequent analyses, the positive association between LMW PAHs and serum CRP and total WBC count was found to be present within the stratified subgroups, independent of smoking and other potential confounders. The positive association was more evident among adult males when compared to females. Conclusions Urinary PAH biomarkers were found to be positively associated with serum CRP and total WBC count independent of smoking and other potential confounders. The association was more evident in men.
Objective The aim of the current study is to investigate the association of polycyclic aromatic hydrocarbons (PAHs), a group of environmental pollutants, with diabetes mellitus. Animal studies link PAHs to inflammation and subsequent development of diabetes mellitus. In addition, occupational studies suggest that exposure to other aromatic hydrocarbons such as dioxins may be associated with diabetes risk in humans. Design We examined participants from the merged National Health and Nutrition Examination Survey 2001–2002, 2003–2004 and 2005–2006. Exposures of interest were eight urinary monohydroxy-PAHs. Our outcome was diabetes mellitus defined as a glycohemoglobin level (HbA1c) ≥6.5%, a self-reported physician diagnosis of diabetes or use of oral hypoglycaemic medication or insulin. Analyses were adjusted for age, sex, body mass index, race, alcohol consumption, poverty–income ratio, total cholesterol and serum cotinine. Results We observed a positive association between urinary biomarkers of 1 and 2-hydroxynapthol, 2-hydroxyphenanthrene and summed low molecular weight (LMW) PAH biomarkers, and diabetes mellitus. Compared with participants with summed LMW PAH biomarkers in the lowest quartile, the multivariable-adjusted OR of diabetes mellitus among those in the highest quartile was 3.1 (95% CI 1.6 to 5.8). Conclusions Urinary biomarkers of 1 and 2-hydroxynapthol, 2-hydroxyphenanthrene and summed LMW PAH biomarkers are associated with diabetes mellitus in US adults 20–65 years of age. The association of a one-time biomarker of PAH exposure has limitations commonly associated with cross-sectional studies, yet is consistent with experimental animal data and is worthy of additional consideration.
Background Globally, the most widely used set of compounds among the internationally regulated drugs is cannabis. Objective To review evidence from epidemiological research on cannabis, organized in relation to this field’s five main rubrics: quantity, location, causes, mechanisms, and prevention/control. Method The review covers a selection of evidence from standardized population surveys, official statistics, and governmental reports, as well as published articles and books identified via MEDLINE, Web of Science, and Google Scholar as of July 2016. Results In relation to quantity, an estimated 3% to 5% of the world population is thought to have tried a cannabis product, with at least one fairly recent use, mainly extra-medical and outside boundaries of prescribed use. Among cannabis users in the United States, roughly one in 7–8 has engaged in medical marijuana use. In relation to location, prevalence proportions reveal important variations across countries and between subgroups within countries. Regarding causes and mechanisms of starting to use cannabis, there is no compelling integrative and replicable conceptual model or theoretical formulation. Most studies of mechanisms have focused upon a ‘gateway sequence’ and person-to-person diffusion, with some recent work on disability-adjusted life years. A brief review of cannabis use consequences, as well as prevention and control strategies is also provided. Conclusion At present, we know much about the frequency and occurrence of cannabis use, with too little replicable definitive evidence with respect to the other main rubrics. Given a changing regulatory environment for cannabis products, new institutions such as an independent International Cannabis Products Safety Commission may be required to produce evidence required to weigh benefits versus costs. It is not clear that government sponsored research will be sufficient to meet consumer demand for balanced points of view and truly definitive evidence.
Background Pre-clinical studies indicate increased food intake and weight gain as cannabinoid effects. Cross-sectional epidemiological studies, however, indicate lower prevalence of obesity among cannabis users. Here, we aim to study the weight-gain research question in the prospectively conducted National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Methods NESARC was designed to produce nationally representative estimates for the US population. Participants (aged 18+) completed computer-assisted personal interviews on cannabis use, body weight and height at Waves 1 (W1, 2001–02) and 2 (W2, 2004–05). General linear modelling yields estimates for change in body mass index (BMI) regressed on cannabis-use status, with covariate adjustment based on a conceptual model for BMI determinants (n = 33 000). Results At W2, 77% of the participants never used cannabis, 18% had discontinued use (‘quit’), 3% were initiates and 2% were persistent users. Estimated W1-to-W2 BMI change shows an increase for all subgroups. Compared with never-users (reference), inverse slope estimates and attenuated change (%) in BMI between W1 and W2 are seen for cannabis-use subgroups: quitters [β = –0.81; 95% confidence interval (CI) = –1.01, –0.60], initiates (β = –0.97; 95% CI = –1.36, –0.57) and persistent users (β = –1.26; 95% CI = –1.81, –0.72). Conclusion This new prospective study builds from anecdotes, pre-clinical studies and cross-sectional evidence on inverse associations linking cannabis use and obesity and shows an inverse cannabis–BMI increase association. Confirmatory studies with rigorous cannabis and BMI assays will be needed.
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