Systemic glucocorticoid exposure and postoperative infection risk in 143,782 appendectomy patients-a Danish longitudinal nationwide study.

BACKGROUND: Glucocorticoids are conventionally associated with increased postoperative infection risk. It is necessary to clarify if preoperative glucocorticoid exposure is associated with postoperative infection in appendectomy patients and if the association is different for open and laparoscopic appendectomies. METHODS: A Danish nationwide study of appendectomy patients between 1996 and 2018. Exposures were defined as high (≥ 5 mg) versus no/low (< 5 mg) glucocorticoid exposure in milligram prednisone-equivalents/day preoperatively. The main outcome was any postoperative infection. Then, 90-day cumulative incidences (absolute risk) and adjusted hazard ratios (relative risk) of the outcome were calculated for high versus no/low glucocorticoid exposure within all appendectomies and within open and laparoscopic subgroups. Propensity-score matching was used for sensitivity analysis. RESULTS: Of 143,782 patients, median age was 29 years, 74,543 were female, and 7654 experienced at least one infection during the 90-day follow-up. The 90-day cumulative incidence for postoperative infection was 5.3% within the no/low glucocorticoid exposure group and 10.0% within the high glucocorticoid exposure group. Compared to no/low glucocorticoid exposure, adjusted hazard ratios for 90-day postoperative infection with high glucocorticoid exposure were 1.25 [95% CI 1.02-1.52; p = 0.03] for all appendectomies, 1.59 [1.16-2.18; p = 0.004] for laparoscopic appendectomies, and 1.09 [0.85-1.40; p = 0.52] for open appendectomies (pinteraction < 0.001). The results were robust to sensitivity analyses. CONCLUSION: Preoperative high (≥ 5 mg/day) glucocorticoid exposure was associated with increased absolute risk of postoperative infections in open and laparoscopic appendectomies. The relative risk increase was significant for laparoscopic but not open appendectomies, possibly due to lower absolute risk with no/low glucocorticoid exposure in the laparoscopic subgroup.

Causal relationship from coffee consumption to diseases and mortality: a review of observational and Mendelian randomization studies including cardiometabolic diseases, cancer, gallstones and other diseases.

PURPOSE: High coffee consumption is associated with low risk of mortality and morbidity, but the causality remains unclear. This review aims to discuss findings from observational studies on coffee consumption in context of Mendelian randomization studies. METHODS: The PubMed database was searched for all Mendelian randomization studies on coffee consumption and corresponding observational studies. RESULTS: High coffee consumption is associated with low risk of all-cause and cardiovascular mortality in observational studies (HRs of 0.85-0.90 vs. no/low consumers), with no support of causality in Mendelian randomization studies. Moderate/high consumption is associated with low risk of cardiometabolic diseases, including ischemic heart disease (HRs of 0.85-0.90 vs. no/low consumption), stroke (HRs of approximately 0.80 vs. no/low consumption), type 2 diabetes (HRs of approximately 0.70 vs. no/low consumption) and obesity in observational studies, but not in Mendelian randomization studies. High consumption is associated with low risk of endometrial cancer and melanoma and high risk of lung cancer in observational studies, but with high risk of colorectal cancer in Mendelian randomization studies. In observational and Mendelian randomization studies, high coffee consumption is associated with low risk of gallstones (HRs of 0.55-0.70 for high vs. no/low self-reported and 0.81 (0.69-0.96) for highest vs. lowest genetic consumption). CONCLUSION: High coffee consumption is associated with low risk of mortality, cardiometabolic diseases, some cancers and gallstones in observational studies, with no evidence to support causality from Mendelian randomization studies for most diseases except gallstones.

The Obesity Paradox in Elderly Patients Undergoing Emergency Surgery: A Nationwide Analysis.

BACKGROUND: Obesity has long been considered a risk factor for postoperative adverse events in surgery. We sought to study the impact of body mass index (BMI) on the clinical outcomes of the high-risk emergency general surgery (EGS) elderly patients. METHODS: All EGS ≥65 years old patients in the 2007-2016 ACS-NSQIP database, identified using the variables 'emergency' and 'surgspec,' were included. Patients were classified into five groups: normal weight: BMI <25 kg/m2, overweight: BMI ≥25 kg/m2 and <30 kg/m2, Class I: BMI ≥30 kg/m2 and <35 kg/m2, Class II: BMI ≥35 kg/m2 and <40 kg/m2, and Class III: BMI ≥40 kg/m2. Patients with BMI<18.5 kg/m2 were excluded. Multivariable logistic regression models were built to assess the relationship between obesity and 30-day postoperative mortality, overall morbidity, and individual postoperative complications after adjusting for demographics (e.g., age, gender), comorbidities (e.g., diabetes mellitus, heart failure), laboratory tests (e.g., white blood cell count, albumin), and operative complexity (e.g., ASA classification). RESULTS: A total of 78,704 patients were included, of which 26,011 were overweight (33.1%), 13,897 (17.6%) had Class I obesity, 5904 (7.5%) had Class II obesity, and 4490 (5.7%) had Class III obesity. On multivariable analyses, compared to the nonobese, patients who are overweight or with Class I-III obesity paradoxically had a lower risk of mortality, bleeding requiring transfusion, pneumonia, stroke and myocardial infarction (MI). Additionally, the incidence of MI and stroke decreased in a stepwise fashion as BMI progressed from overweight to severely obese (MI: OR: 0.84 [0.73-0.95], OR: 0.73 [0.62-0.86], OR: 0.66 [0.52-0.83], OR: 0.51 [0.38-0.68]; stroke: OR: 0.80 [0.65-0.99], OR: 0.79 [0.62-1.02], OR: 0.71 [0.50-1.00], OR: 0.43 [0.28-0.68]). CONCLUSION: In our study of elderly EGS patients, overweight and obese patients had a lower risk of mortality, bleeding requiring transfusion, pneumonia, reintubation, stroke, and MI. Further studies are needed to confirm and investigate the obesity paradox in this patient population.

Opioids After Surgery in the United States Versus the Rest of the World: The International Patterns of Opioid Prescribing (iPOP) Multicenter Study.

OBJECTIVE: The International Patterns of Opioid Prescribing study compares postoperative opioid prescribing patterns in the United States (US) versus the rest of the world. SUMMARY OF BACKGROUND DATA: The US is in the middle of an unprecedented opioid epidemic. Diversion of unused opioids contributes to the opioid epidemic. METHODS: Patients ≥16 years old undergoing appendectomy, cholecystectomy, or inguinal hernia repair in 14 hospitals from 8 countries during a 6-month period were included. Medical records were systematically reviewed to identify: (1) preoperative, intraoperative, and postoperative characteristics, (2) opioid intake within 3 months preoperatively, (3) opioid prescription upon discharge, and (4) opioid refills within 3 months postoperatively. The median/range and mean/standard deviation of number of pills and OME were compared between the US and non-US patients. RESULTS: A total of 4690 patients were included. The mean age was 49 years, 47% were female, and 4% had opioid use history. Ninety-one percent of US patients were prescribed opioids, compared to 5% of non-US patients (P < 0.001). The median number of opioid pills and OME prescribed were 20 (0-135) and 150 (0-1680) mg for US versus 0 (0-50) and 0 (0-600) mg for non-US patients, respectively (both P < 0.001). The mean number of opioid pills and OME prescribed were 23.1 ±â€Š13.9 in US and 183.5 ±â€Š133.7 mg versus 0.8 ±â€Š3.9 and 4.6 ±â€Š27.7 mg in non-US patients, respectively (both P < 0.001). Opioid refill rates were 4.7% for US and 1.0% non-US patients (P < 0.001). CONCLUSIONS: US physicians prescribe alarmingly high amounts of opioid medications postoperatively. Further efforts should focus on limiting opioid prescribing and emphasize non-opioid alternatives in the US.

Smoking and risk of surgical bleeding: nationwide analysis of 5,452,411 surgical cases.

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.

Self-reported and genetically predicted coffee consumption and smoking in dementia: A Mendelian randomization study.

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.

The Geriatric Nutritional Risk Index is a powerful predictor of adverse outcome in the elderly emergency surgery patient.

BACKGROUND: The degree to which malnutrition impacts perioperative outcomes in the elderly emergency surgery (ES) patient remains unknown. We aimed to study the relationship between malnutrition, as measured by the Geriatric Nutritional Risk Index (GNRI), and postoperative outcomes in elderly patients undergoing ES. METHODS: Using the 2007 to 2016 American College of Surgeons National Surgical Quality Improvement Program database, all patients 65 years or older undergoing ES were included in our study. The GNRI, defined as (1.489 × albumin [g/L]) + (41.7 × [weight/ideal weight]) was calculated for each patient in the database. Patients with missing height, weight, or preoperative albumin data were excluded. Patients were divided into four malnutrition groups: very severe (GNRI < 73), severe (GNRI, 73-82), moderate (GNRI, 82-92), and mild (GNRI, 92-98). Geriatric Nutritional Risk Index greater than 98 constituted the normal nutrition group. Risk-adjusted multivariable logistic regressions were performed to study the relationship between malnutrition-measured using either GNRI, albumin level, or body mass index less than 18.5 kg/m-and the following postoperative outcomes: 30-day mortality, 30-day morbidity (including infectious and noninfectious complications), and hospital length of stay. The relationship between GNRI score and 30-day mortality for six common ES procedures was then assessed. RESULTS: A total of 82,725 patients were included in the final analyses. Of these, 55,214 were malnourished with GNRI less than 98 (66.74%). Risk-adjusted multivariable analyses showed that, as malnutrition worsened from mild to very severe, the risk of mortality, morbidity, and the hospital length of stay progressively increased (all p < 0.05). Patients with very severe malnutrition had at least a twofold increased likelihood of mortality (odds ratio [OR], 2.79; 95% confidence interval [CI], 2.57-3.03), deep vein thrombosis (OR, 2.07; 95% CI, 1.77-2.42), and respiratory failure (OR, 1.95; 95% CI, 1.81-2.11). Geriatric Nutritional Risk Index predicted mortality better than albumin or body mass index alone for ES. CONCLUSION: Malnutrition, measured using GNRI, is a strong independent predictor of adverse outcomes in the elderly ES patient and could be used to assess the nutrition status and counsel patients (and families) preoperatively. LEVEL OF EVIDENCE: Prognostic study, Level IV.

Most of the variation in length of stay in emergency general surgery is not related to clinical factors of patient care.

BACKGROUND: Hospital length of stay (LOS) is currently recognized as a key quality indicator. We sought to investigate how much of the LOS variation in the high-risk group of patients undergoing Emergency general surgery could be explained by clinical versus nonclinical factors. METHODS: Using the 2007 to 2015 American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database, we included all patients who underwent an emergency appendectomy, cholecystectomy, colectomy, small intestine resection, enterolysis, or hernia repair. American College of Surgeons National Surgical Quality Improvement Program defines emergency surgery as one that is performed no later than 12 hours after admission or symptom onset. Using all the ACS-NSQIP demographic, preoperative (comorbidities, laboratory variables), intraoperative (e.g., duration of surgery, wound classification), and postoperative variables (i.e., complications), we created multivariable linear regression models to predict LOS. LOS was treated as a continuous variable, and the degree to which the models could explain the variation in LOS for each type of surgery was measured using the coefficient of determination (R). RESULTS: A total of 215,724 patients were included. The mean age was 47.1 years; 52.0% were female. In summary, the median LOS ranged between 1 day for appendectomies (n = 124, 426) and cholecystectomies (n = 21,699) and 8 days for colectomies (n = 19,557) and small intestine resections (n = 7,782). The R for all clinical factors ranged between 0.28 for cholecystectomy and 0.44 for hernia repair, suggesting that 56% to 72% of the LOS variation for each of the six procedures studied cannot be explained by the wide range of clinical factors included in ACS-NSQIP. CONCLUSION: Most of the LOS variation is not explained by clinical factors and may be explained by nonclinical factors (e.g., logistical delays, insurance type). Further studies should evaluate these nonclinical factors to identify target areas for quality improvement. LEVELS OF EVIDENCE: Epidemiological study, level III.

Life after 90: Predictors of mortality and performance of the ACS-NSQIP risk calculator in 4,724 nonagenarian patients undergoing emergency general surgery.

BACKGROUND: The decision to emergently operate on nonagenarian patients (NONAs) can be complex due to the uncertainty about outcomes and goals of care at this advanced age. We sought to study: (1) the outcomes and predictors of mortality for NONAs undergoing emergency general surgery (EGS) and (2) the accuracy of ACS-NSQIP mortality risk calculator in this special population. METHODS: Using the 2007 to 2015 ACS-NSQIP database, we included all patients older than 90 years of age who underwent an emergent operation with a Current Procedural Terminology (CPT) code for "digestive system." Multivariable logistic regression analyses were performed to identify independent predictors of 30-day mortality. NONAs' mortality rates for different combinations of risk factors were also studied and compared to the ACS-NSQIP calculator-predicted mortality rates. RESULTS: Out of a total of 4,456,809 patients, 4,724 NONAs were included. The overall 30-day patient mortality and morbidity rates were 21% and 45%, respectively. In multivariable analyses, several independent predictors of 30-day mortality were identified, including recent history of weight loss, history of steroid use, smoking, functional dependence, hypoalbuminemia and sepsis or septic shock. The mortality among NONAs with a history of steroid use and a recent history of weight loss was 100%. Similarly, the mortality of NONAs with recent history of weight loss who presented with preoperative septic shock was 93%. The ACS-NSQIP calculator significantly and consistently underestimated the risk of mortality in all NONAs undergoing EGS. CONCLUSION: Most NONAs undergoing EGS survive the hospital stay and the first 30 postoperative days, even in the presence of significant preexisting comorbidities. However, the combination of recent weight loss with either steroid use or septic shock nearly ensures mortality and should be used in the discussions with patients and families before a decision to operate is made. The ACS-NSQIP surgical risk calculator should be used with caution in these high-risk patients. LEVEL OF EVIDENCE: Prognostic study, level III.

Obesity as protective against, rather than a risk factor for, postoperative Clostridium difficile infection: A nationwide retrospective analysis of 1,426,807 surgical patients.

BACKGROUND: Recent studies suggest that obesity is a risk factor for Clostridium difficile infection, possibly due to disruptions in the intestinal microbiome composition. We hypothesized that body mass index (BMI) is associated with increased incidence of C. difficile infection in surgical patients. METHODS: In this nationwide retrospective cohort study in 680 American College of Surgeons National Surgical Quality Improvement Program participating sites across the United States, the occurrence of C. difficile infection within 30 days postoperatively between different BMI groups was compared. All American College of Surgeons National Surgical Quality Improvement Program patients between 2015 and 2016 were classified as underweight, normal-weight, overweight, or obese class I-III if their BMI was less than 18.5, 18.5 to 25, 25 to 30, 30 to 35, 35 to 40 or greater than 40, respectively. RESULTS: A total of 1,426,807 patients were included; median age was 58 years, 43.4% were male, and 82.9% were white. The postoperative incidence of C. difficile infection was 0.42% overall: 1.11%, 0.56%, 0.39%, 0.35%, 0.33% and 0.36% from the lowest to the highest BMI group, respectively (p < 0.001 for trend). In univariate then multivariable logistic regression analyses, adjusting for patient demographics (e.g., age, sex), comorbidities (e.g., diabetes, systemic sepsis, immunosuppression), preoperative laboratory values (e.g., albumin, white blood cell count), procedure complexity (work relative unit as a proxy) and procedure characteristics (e.g., emergency, type of surgery [general, vascular, other]), compared with patients with normal BMI, high BMI was inversely and incrementally correlated with the postoperative occurrence of C. difficile infection. The underweight were at increased risk (odds ratio, 1.15 [1.00-1.32]) while the class III obese were at the lowest risk (odds ratio, 0.73 [0.65-0.81]). CONCLUSION: In this nationwide retrospective cohort study, obesity is independently and in a stepwise fashion associated with a decreased risk of postoperative C. difficile infection. Further studies are warranted to explore the potential and unexpected association. LEVEL OF EVIDENCE: Prognostic/Epidemiologic, Level IV.

Emergency Surgery Score Accurately Predicts the Risk of Post-Operative Infection in Emergency General Surgery.

BACKGROUND: The Emergency Surgery Score (ESS) was validated recently as an accurate and user-friendly post-operative mortality risk calculator specific for Emergency General Surgery (EGS). ESS is calculated by adding one to three integer points for each of 22 pre-operative variables (demographics, co-morbidities, and pre-operative laboratory values); increasing scores accurately and gradually predict higher mortality rates. We sought to evaluate whether ESS can predict the occurrence of post-operative infectious complications in EGS patients. PATIENTS AND METHODS: Using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database from 2007-2015, all EGS patients were identified by using the "emergent" ACS-NSQIP variable and a concomitant surgery Current Procedural Terminology code for "digestive system." Patients with any missing ESS variables or those who died within 72 hours from the surgical procedure were excluded. A composite variable, post-operative infection, was created and defined as the post-operative occurrence of one or more of the following: superficial, deep incisional or organ/space surgical site infection, surgical site disruption, pneumonia, sepsis, septic shock, or urinary tract infection. ESS was calculated for all included patients, and the correlation between ESS and post-operative infection was examined using c-statistics. RESULTS: Of a total of 4,456,809 patients, 90,412 patients were included. The mean age of the population was 56 years, 51% were female, and 70% were white; 22% developed one or more post-operative infections, most commonly sepsis/septic shock (12.2%), surgical site infection (9%), and pneumonia (5.7%). The ESS gradually and consistently predicted infectious complications; post-operative infections developed in 7%, 24%, and 49% of patients with an ESS of 1, 5, and 10, respectively. The c-statistics for overall post-operative infection, post-operative sepsis/septic shock, and pneumonia were 0.73, 0.75, and 0.80, respectively. CONCLUSION: The ESS accurately predicts the occurrence of post-operative infectious complications in EGS patients and could be used for pre-operative clinical decision-making as well as quality benchmarking of infection rates in EGS.

Variation of Opioid Prescribing Patterns among Patients undergoing Similar Surgery on the Same Acute Care Surgery Service of the Same Institution: Time for Standardization?

BACKGROUND: Diversion of unused prescription opioids is a major contributor to the current United States opioid epidemic. We aimed to study the variation of opioid prescribing in emergency surgery. METHODS: Between October 2016 and March 2017, all patients undergoing laparoscopic appendectomy, laparoscopic cholecystectomy, or inguinal hernia repair in the acute care surgery service of 1 academic center were included. For each patient, we systematically reviewed the electronic medical record and the prescribing pharmacy platform to identify: (1) history of opioid abuse, (2) opioid intake 3 months preoperatively, (3) number of opioid pills prescribed, (4) prescription of nonopioid pain medications (eg, acetaminophen, ibuprofen), and (5) the need for opioid prescription refills. The mean and range of opioid pills prescribed, as well as their oral morphine equivalent, were calculated. RESULTS: A total of 255 patients were included (43.5% laparoscopic appendectomy, 44.3% laparoscopic cholecystectomy, and 12.1% inguinal hernia repair). The mean age was 47.5 years, 52.1% were female, 11.4% had a history of opioid use, and 92.5% received opioid prescriptions upon hospital discharge. Only 70.9% of patients were instructed to use nonopioid pain medications. The mean and range of opioid pills prescribed were 17.4; 0-56 (laparoscopic appendectomy), 17.1; 0-75 (laparoscopic cholecystectomy), and 20.9; 0-50 (inguinal hernia repair), while the range of prescribed oral morphine equivalent was 0-600 mg for laparoscopic appendectomy/laparoscopic cholecystectomy and 0-375 mg for inguinal hernia repair. No patients required any opioid medication refills. CONCLUSION: Even within the same surgical service, wide variation of opioid prescription was observed. Guidelines that standardize pain management may help prevent opioid overprescribing.

The effect of resuscitation strategy on the longitudinal immuno-inflammatory response to blunt trauma.

INTRODUCTION: Resuscitation strategies following blunt trauma have been linked to immuno-inflammatory complications leading to systemic inflammatory syndrome (SIRS), sepsis and multiple organ failure (MOF). The effect of resuscitation strategy on longitudinal inflammation marker trajectories is, however, unknown. We hypothesized that the effect of resuscitation strategy extends beyond the trauma-related coagulopathy, perhaps affecting the longitudinal immuno-inflammatory response to injury. METHODS: We analyzed data prospectively collected for the Inflammation and Host Response to Injury (Glue Grant) study. Blood sampling for inflammation marker analyses from blunt trauma patients was done on admission days 0, 1, 4, 7, 14, 21 and 28 where applicable. Total volume transfused of packed red blood cells (PRBC), fresh frozen plasma (FFP), platelets (PLT), and crystalloids during the initial 48h was extracted, along with an analysis for an array of cytokines by Enzyme Linked Immunosorbent Assay (ELISA) technique. A within patient concentration change (WPCC) was calculated to quantify longitudinal alterations in cytokine levels, while controlling for potential confounders. To account for the multiple comparisons performed, p-values obtained from the multivariate regression model were post-hoc corrected by the false detection rate (FDR) q-value. RESULTS: No longitudinal trajectories of inflammatory markers were found to be associated with PRBC- or PLT transfusion. Three proinflammatory cytokines (Il-1ß, MIP-1ß, and TNFR2) were negatively associated with volume of FFP transfused (q=0.02, q<0.001 and q=0.007 respectively), and one proinflammatory cytokine (MIP-1ß) was positively associated with crystalloid infusion (q=0.005). CONCLUSIONS: Resuscitation strategy employed following blunt trauma has limited association to longitudinal inflammation marker trajectories, with a potential association between the strategy employed and IL-1ß, TNFR2, and MIP-1ß trajectories, respectively.

Heavier smoking increases coffee consumption: findings from a Mendelian randomization analysis.

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.

Coffee intake, cardiovascular disease and all-cause mortality: observational and Mendelian randomization analyses in 95 000-223 000 individuals.

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 mortality. Including international consortia, odds ratios per caffeine intake allele for ischaemic heart disease were 1.00 (0.98-1.02) for rs4410790, 1.01 (0.99-1.03) for rs6968865, 1.02 (1.00-1.04) for rs2470893, 1.02 (1.00-1.04) for rs2472297 and 1.03 (0.99-1.06) for rs2472299. Conversely, 5% lower cholesterol level caused by ApoE genotype had a corresponding odds ratio for ischaemic heart disease of 0.93 (0.89-0.97). Conclusions: Observationally, coffee intake was associated with U-shaped lower risk of cardiovascular disease and all-cause mortality; however, genetically caffeine intake was not associated with risk of cardiovascular disease or all-cause mortality.

Coffee intake and risk of obesity, metabolic syndrome and type 2 diabetes: a Mendelian randomization study.

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 (0.95-1.01) for CYP1A1 rs2472299. CONCLUSIONS: High coffee intake was associated observationally with low risk of obesity, metabolic syndrome and type 2 diabetes, and was associated observationally with related components thereof, but with no genetic evidence to support corresponding causal relationships.