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BACKGROUND AND AIMS: Studies of self-reported coffee consumption and smoking on risk of dementia have shown results conflicting with two-sample Mendelian randomization studies. We tested the hypotheses that coffee consumption and smoking influence risk of dementia using observational and one-sample Mendelian randomization designs with individual level data.METHODS: We included 114,551 individuals from two Danish general population cohorts (median age 58 years). First, we tested whether high self-reported coffee consumption/smoking were associated with risk of dementia. Second, whether genetically predicted high coffee consumption/smoking due to variation near CYP1A1/AHR/CHRNA3 genes were associated with risk of dementia.RESULTS: We observed 3,784 dementia events. Moderate self-reported coffee consumption was associated with low risk of all dementia and non-Alzheimer's dementia, with a similar trend for Alzheimer's disease. Genetically predicted high coffee consumption was associated with high risk of all dementia (hazard ratio [95% confidence interval] per +1 cup/day: 1.20 [1.01-1.42]), with a similar trend for non-Alzheimer's dementia (1.23 [0.95-1.53]). High self-reported smoking was associated with high risk of non-Alzheimer's dementia. High genetically predicted smoking was associated with a trend towards high risk of all dementia and Alzheimer's disease (hazard ratios per +1 pack-year: 1.04 [0.96-1.11]) and 1.06 [0.97-1.16]).CONCLUSIONS: Moderate self-reported coffee consumption was associated with low risk of all and non-Alzheimer's dementia, while high genetically predicted coffee consumption was associated with a trend towards the opposite. High self-reported smoking was associated with high risk of non-Alzheimer's dementia, with a similar trend for genetically predicted smoking on all dementia and Alzheimer's disease.

BACKGROUND: Although smoking is associated with several postoperative complications, a possible association with surgical bleeding remains unclear. We examined if smoking is associated with a higher risk of surgical bleeding. STUDY DESIGN AND METHODS: We included patients from the American College of Surgeons National Surgical Quality Improvement Program 2007-2016 from 680 hospitals across the United States. Patients with information on age, sex, surgical specialty, and smoking status were included. Surgical bleeding was defined as 1 or more red blood cell (RBC) units transfused intraoperatively to 72 hours postoperatively. The association between smoking and surgical bleeding was examined using logistic regressions adjusted for age, sex, body mass index, ethnicity, comorbidities, laboratory values, American Society of Anesthesiologists score, type of anesthesia, duration of surgery, work relative value unit (surrogate for operative complexity), surgical specialty, and procedure year. RESULTS: A total of 5,452,411 cases were recorded, of whom 19% smoked and 6% received transfusion. Odds ratios for transfusion were 1.06 (95% confidence interval [CI], 1.05-1.07) for smokers versus nonsmokers and 1.06 (95% CI, 1.04-1.09) for current smokers versus never-smokers. Odds ratios for cumulative smoking were 0.97 (95% CI, 0.95-1.00) for greater than 0 to 20 versus 0 pack-years, 1.04 (95% CI, 1.01-1.07) for greater than 20 to 40, and 1.12 (95% CI, 1.09-1.15) for greater than 40 (p for trend < 0.001). Hazard ratios for reoperations due to any cause and to bleeding were 1.28 (95% CI, 1.27-1.31) and 0.99 (95% CI, 0.93-1.04). CONCLUSION: Smoking was associated with a higher risk of RBC transfusion as a proxy for surgical bleeding across all surgical specialties combined.

Background: There is evidence for a positive relationship between cigarette and coffee consumption in smokers. Cigarette smoke increases metabolism of caffeine, so this may represent a causal effect of smoking on caffeine intake.Methods: We performed Mendelian randomization analyses in the UK Biobank ( N = 114 029), the Norwegian HUNT study ( N = 56 664) and the Copenhagen General Population Study (CGPS) ( N = 78 650). We used the rs16969968 genetic variant as a proxy for smoking heaviness in all studies and rs4410790 and rs2472297 as proxies for coffee consumption in UK Biobank and CGPS. Analyses were conducted using linear regression and meta-analysed across studies.Results: Each additional cigarette per day consumed by current smokers was associated with higher coffee consumption (0.10 cups per day, 95% CI: 0.03, 0.17). There was weak evidence for an increase in tea consumption per additional cigarette smoked per day (0.04 cups per day, 95% CI: -0.002, 0.07). There was strong evidence that each additional copy of the minor allele of rs16969968 (which increases daily cigarette consumption) in current smokers was associated with higher coffee consumption (0.16 cups per day, 95% CI: 0.11, 0.20), but only weak evidence for an association with tea consumption (0.04 cups per day, 95% CI: -0.01, 0.09). There was no clear evidence that rs16969968 was associated with coffee or tea consumption in never or former smokers or that the coffee-related variants were associated with cigarette consumption.Conclusions: Higher cigarette consumption causally increases coffee intake. This is consistent with faster metabolism of caffeine by smokers, but could also reflect a behavioural effect of smoking on coffee drinking.

Background: Coffee has been associated with modestly lower risk of cardiovascular disease and all-cause mortality in meta-analyses; however, it is unclear whether these are causal associations. We tested first whether coffee intake is associated with cardiovascular disease and all-cause mortality observationally; second, whether genetic variations previously associated with caffeine intake are associated with coffee intake; and third, whether the genetic variations are associated with cardiovascular disease and all-cause mortality. Methods: First, we used multivariable adjusted Cox proportional hazard regression models evaluated with restricted cubic splines to examine observational associations in 95 366 White Danes. Second, we estimated mean coffee intake according to five genetic variations near the AHR (rs4410790; rs6968865) and CYP1A1/2 genes (rs2470893; rs2472297; rs2472299). Third, we used sex- and age adjusted Cox proportional hazard regression models to examine genetic associations with cardiovascular disease and all-cause mortality in 112 509 Danes. Finally, we used sex and age-adjusted logistic regression models to examine genetic associations with ischaemic heart disease including the Cardiogram and C4D consortia in a total of up to 223 414 individuals. We applied similar analyses to ApoE genotypes associated with plasma cholesterol levels, as a positive control. Results: In observational analyses, we observed U-shaped associations between coffee intake and cardiovascular disease and all-cause mortality; lowest risks were observed in individuals with medium coffee intake. Caffeine intake allele score (rs4410790 + rs2470893) was associated with a 42% higher coffee intake. Hazard ratios per caffeine intake allele were 1.02 (95% confidence interval: 1.00-1.03) for ischaemic heart disease, 1.02 (0.99-1.02) for ischaemic stroke, 1.02 (1.00-1.03) for ischaemic vascular disease, 1.02 (0.99-1.06) for cardiovascular mortality and 1.01 (0.99-1.03) for all-cause

Background: Coffee is one of the most widely consumed beverages. We tested the hypothesis that genetically high coffee intake is associated with low risk of obesity, metabolic syndrome and type 2 diabetes, and with related components thereof. Methods: We included 93 179 individuals from two large general population cohorts in a Mendelian randomization study. We tested first whether high coffee intake is associated with low risk of obesity, metabolic syndrome and type 2 diabetes, and with related components thereof, in observational analyses; second, whether five genetic variants near the CYP1A1, CYP1A2 and AHR genes are associated with coffee intake; and third, whether the genetic variants are associated with obesity, metabolic syndrome and type 2 diabetes, and with related components thereof. Finally, we tested the genetic association with type 2 diabetes in a meta-analysis including up to 78 021 additional individuals from the DIAGRAM consortium. Results: Observationally, high coffee intake was associated with low risk of obesity, metabolic syndrome and type 2 diabetes. Further, high coffee intake was associated with high body mass index, waist circumference, weight, height, systolic/diastolic blood pressure, triglycerides and total cholesterol and with low high-density lipoprotein cholesterol, but not with glucose levels. In genetic analyses, 9–10 vs 0–3 coffee-intake alleles were associated with 29% higher coffee intake. However, genetically derived high coffee intake was not associated convincingly with obesity, metabolic syndrome, type 2 diabetes, body mass index, waist circumference, weight, height, systolic/diastolic blood pressure, triglycerides, total cholesterol, high-density lipoprotein cholesterol or glucose levels. Per-allele meta-analysed odds ratios for type 2 diabetes were 1.01 (0.98–1.04) for AHR rs4410790, 0.98 (0.95–1.01) for AHR rs6968865, 1.01 (0.99–1.03) for CYP1A1/2 rs2470893, 1.01 (0.98–1.03) for CYP1A1/2 rs2472297 and 0.98, BACKGROUND: Coffee is one of the most widely consumed beverages. We tested the hypothesis that genetically high coffee intake is associated with low risk of obesity, metabolic syndrome and type 2 diabetes, and with related components thereof.METHODS: We included 93,179 individuals from two large general population cohorts in a Mendelian randomization study. We tested first whether high coffee intake is associated with low risk of obesity, metabolic syndrome and type 2 diabetes, and with related components thereof, in observational analyses; second, whether five genetic variants near the CYP1A1, CYP1A2 and AHR genes are associated with coffee intake; and third, whether the genetic variants are associated with obesity, metabolic syndrome and type 2 diabetes, and with related components thereof. Finally, we tested the genetic association with type 2 diabetes in a meta-analysis including up to 78,021 additional individuals from the DIAGRAM consortium.RESULTS: Observationally, high coffee intake was associated with low risk of obesity, metabolic syndrome and type 2 diabetes. Further, high coffee intake was associated with high body mass index, waist circumference, weight, height, systolic/diastolic blood pressure, triglycerides and total cholesterol and with low high-density lipoprotein cholesterol, but not with glucose levels. In genetic analyses, 9-10 vs 0-3 coffee-intake alleles were associated with 29% higher coffee intake. However, genetically derived high coffee intake was not associated convincingly with obesity, metabolic syndrome, type 2 diabetes, body mass index, waist circumference, weight, height, systolic/diastolic blood pressure, triglycerides, total cholesterol, high-density lipoprotein cholesterol or glucose levels. Per-allele meta-analysed odds ratios for type 2 diabetes were 1.01 (0.98-1.04) for AHR rs4410790, 0.98 (0.95-1.01) for AHR rs6968865, 1.01 (0.99-1.03) for CYP1A1/2 rs2470893, 1.01 (0.98-1.03) for CYP1A1/2 rs2472297 and 0.98 (0