Transcriptomic responses in the blood and sputum of cigarette smokers compared to e-cigarette vapers.

RATIONALE: Electronic (e)-cigarettes are popular among youth and cigarette smokers attempting to quit. Studies to date have focused on the utility of e-cigarettes as a smoking cessation tool, but the biological effects are largely unknown. OBJECTIVES: To identify transcriptomic differences in the blood and sputum of e-cigarette users compared to conventional cigarettes smokers and healthy controls and describe biological pathways affected by these tobacco products. METHODS: Cross-sectional analysis of whole blood and sputum RNA-sequencing data from 8 smokers, 9 e-cigarette users (e-cigs) and 4 controls. Weighted gene co-network analysis (WGCNA) identified gene module associations. Ingenuity Pathway Analysis (IPA) identified canonical pathways associated with tobacco products. MAIN RESULTS: In blood, a three-group comparison showed 16 differentially expressed genes (DEGs); pair-wise comparison showed 7 DEGs between e-cigs and controls, 35 DEGs between smokers and controls, and 13 DEGs between smokers and e-cigs. In sputum, 438 DEGs were in the three-group comparison. In pair-wise comparisons, there were 2 DEGs between e-cigs and controls, 270 DEGs between smokers and controls, and 468 DEGs between smokers and e-cigs. Only 2 genes in the smokers vs. control comparison overlapped between blood and sputum. Most gene modules identified through WGCNA associated with tobacco product exposures also were associated with cotinine and exhaled CO levels. IPA showed more canonical pathways altered by conventional cigarette smoking than by e-cigarette use. CONCLUSION: Cigarette smoking and e-cigarette use led to transcriptomic changes in both blood and sputum. However, conventional cigarettes induced much stronger transcriptomic responses in both compartments.

Prospective predictors of electronic nicotine delivery system initiation in tobacco naive young adults: A machine learning approach.

The use of electronic nicotine delivery systems (ENDS) is increasing among young adults. However, there are few studies regarding predictors of ENDS initiation in tobacco-naive young adults. Identifying the risk and protective factors of ENDS initiation that are specific to tobacco-naive young adults will enable the creation of targeted policies and prevention programs. This study used machine learning (ML) to create predictive models, identify risk and protective factors for ENDS initiation for tobacco-naive young adults, and the relationship between these predictors and the prediction of ENDS initiation. We used nationally representative data of tobacco-naive young adults in the U.S drawn from the Population Assessment of Tobacco and Health (PATH) longitudinal cohort survey. Respondents were young adults (18-24 years) who had never used any tobacco products in Wave 4 and who completed Waves 4 and 5 interviews. ML techniques were used to create models and determine predictors at 1-year follow-up from Wave 4 data. Among the 2,746 tobacco-naive young adults at baseline, 309 initiated ENDS use at 1-year follow-up. The top five prospective predictors of ENDS initiation were susceptibility to ENDS, increased days of physical exercise specifically designed to strengthen muscles, frequency of social media use, marijuana use and susceptibility to cigarettes. This study identified previously unreported and emerging predictors of ENDS initiation that warrant further investigation and provided comprehensive information on the predictors of ENDS initiation. Furthermore, this study showed that ML is a promising technique that can aid ENDS monitoring and prevention programs.

E-Cigarette Use in Young Adult Never Cigarette Smokers with Disabilities: Results from the Behavioral Risk Factor Surveillance System Survey.

Young adult never cigarette smokers with disabilities may be at particular risk for adopting e-cigarettes, but little attention has been paid to these people. This study examines the associations between different types of disability and e-cigarette use in this population. Young adult never-smokers from the 2016-2017 Behavioral Risk Factor Surveillance System (BRFSS) survey who were either never or current e-cigarette users (n = 79,177) were selected for the analysis. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm was used to select confounders for multivariable logistic regression models. Multivariable logistic regression models were used to determine the associations between current e-cigarette use and different types of disability after incorporating BRFSS survey design and adjusting for confounders. Young adult never-smokers who reported any disability had increased odds (OR 1.44, 95% CI 1.18-1.76) of e-cigarette use compared to those who reported no disability. Young adult never-smokers who reported self-care, cognitive, vision, and independent living disabilities had higher odds of e-cigarette use compared to those who reported no disability. There was no statistically significant difference in the odds of e-cigarette use for those reporting hearing and mobility disabilities compared to those who reported no disability. This study highlights the need for increased public education and cessation programs for this population.

Biomarkers of Toxicant Exposure and Inflammation Among Women of Reproductive Age Who Use Electronic or Conventional Cigarettes.

Background: Electronic cigarettes (e-cigarettes) generally have a more favorable toxicant profile than conventional cigarettes; however, limited information exists for women of reproductive age (WRA). Our aim was to compare biomarkers of toxicant exposure, inflammation, and oxidative stress among WRA who self-report exclusive e-cigarette use, exclusive cigarette smoking, or never tobacco use (controls). Methods: Multivariable linear regression models were used to compare the geometric means of urinary biomarkers of toxicant exposure and their metabolites, serum markers of inflammation [highly sensitive C-reactive protein, soluble intercellular adhesion molecule (sICAM), interleukin 6, fibrinogen], and a measurement of oxidative stress [prostaglandin F2a-8-isoprostane (F2PG2a)] among WRA from the Population Assessment of Tobacco and Health survey. Results: E-cigarette users had higher levels of lead, tobacco-specific nitrosamines, nicotine metabolites, and some volatile organic compounds (VOCs) than controls. Except for cadmium and lead, e-cigarette users had lower levels of the analyzed urinary toxicant biomarkers compared with cigarette smokers. Cigarette smokers had higher levels of all the biomarkers of toxicant exposure than controls. There were no significant differences in the levels of markers of inflammation and oxidative stress between e-cigarette users and controls. E-cigarette users and controls had lower levels of sICAM and F2PG2a than cigarette smokers. Conclusion: WRA who use e-cigarettes had lower levels of some of the evaluated urinary biomarkers of toxicant exposure and serum biomarkers of inflammation and oxidative stress than those who smoke cigarettes, but higher lead, nicotine metabolites, and some VOCs than controls, which can increase health risks.

Electronic Cigarettes Associated With Incident and Polysubstance Use Among Youth.

PURPOSE: Electronic cigarette (e-cigarette) use has increased exponentially among the youth in the United States and may increase the incidence of substance use. METHODS: Youth participants (12-17 years) were surveyed through the Population Assessment of Tobacco and Health study over a three-year time period. Youth with any baseline substance use or diagnosis of an attention deficit disorder were excluded from the analysis. Multivariable logistic regressions were used to assess the association between e-cigarette use at Wave 1 and incident substance use (marijuana, painkillers, sedatives, or tranquilizers and Ritalin/Adderall) and polysubstance use at Wave 2 or 3, and marijuana use in the electronic nicotine device at Wave 3. RESULTS: Baseline ever e-cigarette users who had no history of marijuana, nonprescribed drugs and illicit substance use in Wave 1 had increased odds of reporting incident use of marijuana (odds ratio 2.59, 95% confidence interval: 1.90-3.52), nonprescribed Ritalin/Adderall use (1.89, 1.09-3.28), or polysubstance use (2.09, 1.43-3.05) in Wave 2 or 3 compared to never e-cigarette users. They were also more likely to report use of marijuana in the electronic nicotine product (2.26, 1.56-3.27) in Wave 3 compared to never e-cigarette users. There was no statistically significant association between baseline e-cigarette use and incident use of painkillers, sedatives, or tranquilizers in Wave 2 or 3 (1.21, .79-1.87). CONCLUSIONS: E-cigarette use is associated with incident use of marijuana, marijuana in electronic nicotine devices, Ritalin/Adderall, and polysubstance use but not painkillers, sedatives, or tranquilizers. Results indicate that e-cigarettes are associated with subsequent additional risky health behaviors in youth.

The inflammatory biomarker YKL-40 is elevated in the serum, but not the sputum, of E-cigarette users.

METHODS: We conducted a cross-sectional study of adults between 18 and 55 years old. Inclusion criteria were: exclusive e-cigarette use or cigarette smoking for ≥ 1 year or no history of tobacco use. Participants with a history of pulmonary illness, atopy, medications (except birth control pills), marijuana, and illegal substance use were excluded. Custom Multiplex ELISA was used to measure YKL-40 and other biomarker levels in the serum and induced sputum of the participants. Multivariable linear regression was used to compare the levels of YLK-40 in healthy participants, e-cigarette, and cigarette users after adjusting for age, sex, and BMI. RESULTS: We recruited 20 healthy controls, 23 cigarette smokers, and 22 exclusive e-cigarette users. Serum YKL-40 (ng/ml) was significantly higher in e-cigarette users (Median 21.2 [IQR 12.1-24.0] ng/ml) when compared to controls (12.2 [IQR 8.7-18.1] ng/ml, p = 0.016) but comparable to cigarette smokers (21.6 [IQR 11.62-51.7] ng/ml, p = 0.31). No significant differences were found in the serum or sputum of the other biomarkers tested. CONCLUSION: The inflammatory biomarker, YKL-40 is elevated in the serum but not the sputum of e-cigarette users with no reported pulmonary disease. Further research is necessary to characterize this association.

Factors Associated with E-Cigarette Use in U.S. Young Adult Never Smokers of Conventional Cigarettes: A Machine Learning Approach.

E-cigarette use is increasing among young adult never smokers of conventional cigarettes, but the awareness of the factors associated with e-cigarette use in this population is limited. The goal of this work was to use machine learning (ML) algorithms to determine the factors associated with current e-cigarette use among US young adult never cigarette smokers. Young adult (18-34 years) never cigarette smokers from the 2016 and 2017 Behavioral Risk Factor Surveillance System (BRFSS) who reported current or never e-cigarette use were used for the analysis (n = 79,539). Variables associated with current e-cigarette use were selected by two ML algorithms (Boruta and Least absolute shrinkage and selection operator (LASSO)). Odds ratios were calculated to determine the association between e-cigarette use and the variables selected by the ML algorithms, after adjusting for age, gender and race/ethnicity and incorporating the BRFSS complex design. The prevalence of e-cigarette use varied across states. Factors previously reported in the literature, such as age, race/ethnicity, alcohol use, depression, as well as novel factors associated with e-cigarette use, such as disabilities, obesity, history of diabetes and history of arthritis were identified. These results can be used to generate further hypotheses for research, increase public awareness and help provide targeted e-cigarette education.

E-cigarette use is associated with a self-reported diagnosis of prediabetes in never cigarette smokers: Results from the behavioral risk factor surveillance system survey.

BACKGROUND: The use of e-cigarettes is increasing in the US but there is still a paucity of research on the metabolic effects of e-cigarette use. The goal of this work was to determine the association between e-cigarette use and self-reported prediabetes in adult never cigarette smokers. METHOD: The 2017 cross sectional Behavioral Risk Factor Surveillance System (BRFSS) survey data was used for the analysis. Current e-cigarette users reported daily or someday use of e-cigarettes and former e-cigarette users reported no current use of e-cigarettes. Participants who reported a history of diabetes, gestational prediabetes/ diabetes were excluded. Odds ratios were calculated to determine the association between e-cigarette use and self-reported prediabetes in never cigarette smokers after adjusting for potential confounders. RESULTS: There were a total of 154,404 participants that met the inclusion criteria. Of those participants, there were 143,952 never, 1339 current and 7625 former e-cigarette users. Current e-cigarette users had an increased odds of reporting a diagnosis of prediabetes 1.97 (95% CI 1.25-3.10) compared to never e-cigarette users. After stratifying by gender, men and women had an increased odds ratio of reporting a diagnosis of prediabetes 2.36 (95% CI 1.26-4.40) and 1.88 (95% CI 1.00-3.53) respectively when compared to never e-cigarette users. There was no association between former e-cigarette use and a self-reported diagnosis of prediabetes. CONCLUSION: Our findings show that e-cigarette use may be associated with self-reported prediabetes. Further evaluation is needed in prospective studies.

Adult E-Cigarettes Use Associated with a Self-Reported Diagnosis of COPD.

The use of electronic cigarettes (e-cigarettes) has increased in the US, but little is known about the effects of these products on lung health. The main purpose of this study was to examine the association between e-cigarette use and a participant's report of being diagnosed with chronic obstructive pulmonary disease (COPD) in a nationally representative sample of adults. Methods: The first wave of the Population Assessment of Tobacco and Health (PATH) survey adult data was used (N = 32,320). Potential confounders between e-cigarette users and non-users were balanced using propensity score matching. Odds ratios (OR) were calculated to examine the association between e-cigarette use and COPD in the propensity-matched sample, the entire sample, different age groups, and in nonsmokers. Replicate weights and balanced repeated replication methods were utilized to account for the complex survey design. Results: Of the 3642 participants who met the criteria for e-cigarette use, 2727 were propensity matched with 2727 non e-cigarette users. In the propensity-matched sample, e-cigarette users were more likely to report being diagnosed with COPD (OR 1.43, 95% confidence interval [CI] 1.12-1.85) than non-e-cigarette users after adjusting for confounders. The result was similar in the entire sample and in the different age subgroups. Among nonsmokers, the odds of reporting a COPD diagnosis were even greater among e-cigarette users (OR 2.94, 95% CI 1.73-4.99) compared to non-e-cigarette users. Conclusion: Our findings demonstrate that e-cigarette use was associated with a reported diagnosis of COPD among adults in the US. Further research is necessary to characterize the nature of this association and on the long-term effects of using e-cigarettes.

Association between Regular Electronic Nicotine Product Use and Self-reported Periodontal Disease Status: Population Assessment of Tobacco and Health Survey.

Electronic nicotine product use is increasing in the U.S., but few studies have addressed its effects on oral health. The goal of this work was to determine the association between electronic nicotine product use and periodontal disease. Population Assessment of Tobacco and Health adult survey data from 2013⁻2016 (waves 1, 2 and 3) was used for the analysis. Longitudinal electronic nicotine product users used electronic nicotine products regularly every day or somedays in all three waves. Participants with new cases of gum disease reported no history of gum disease in wave 1 but reported being diagnosed with gum disease in waves 2 or 3. Odds ratios (OR) were calculated to determine the association between electronic nicotine product use and new cases of gum disease after controlling for potential cofounders. Compared to never users, longitudinal electronic nicotine product users had increased odds of being diagnosed with gum disease (OR 1.76, 95% Confidence Interval (CI) 1.12⁻2.76) and bone loss around teeth (OR 1.67, 95% CI 1.06⁻2.63). These odds were higher for participants with a history of marijuana and a history of illicit or non-prescribed drug use. Our findings show that e-cigarettes may be harmful to oral health.

Impact of piperacillin/tazobactam on nephrotoxicity in patients with Gram-negative bacteraemia.

Piperacillin/tazobactam (TZP) has been associated with nephrotoxicity in patients receiving vancomycin. Its impact on nephrotoxicity in patients with Gram-negative bacteraemia (GNB) is unclear. This study evaluated the impact of TZP on nephrotoxicity in patients with GNB. This retrospective cohort included patients aged ≥18 years receiving ≥48 h of therapy for bacteraemia due to Escherichia coli, Pseudomonas aeruginosa, Enterobacter, Klebsiella, Acinetobacter or Stenotrophomonas maltophilia from 1/01/2008-8/31/2011. Patients with baseline serum creatinine (SCr) ≥3.5 mg/dL, polymicrobial infection or recurrent bacteraemia were excluded. Nephrotoxicity was defined as a ≥0.5 mg/dL increase in SCr or ≥50% increase from baseline for ≥2 consecutive days. Any variable demonstrating a 10% change in exposure effect was retained in the final model. All variables biologically reasonable causes of nephrotoxicity were also considered for inclusion. The median age of the cohort (n = 292) was 76 years; 38.0% had a cancer diagnosis and ICU residence was common (21.9%). There was no difference in nephrotoxicity incidence based on days of TZP received (0 days, 13.6%; 1-2 days, 14.7%; 3-4 days, 6.9%; ≥5 days, 16.7%; P = 0.71). In multivariable analysis, baseline SCr, total body weight and vasopressor use were independently associated with nephrotoxicity. Duration of TZP was not associated with nephrotoxicity in multivariable analysis (1-2 days, OR = 0.91, 95% CI 0.39-2.12; 3-4 days, OR = 0.48, 95% CI 0.10-2.46; ≥5 days, OR = 0.57, 95% CI 0.11-3.02). In this cohort of GNB patients, duration of TZP was not associated with nephrotoxicity.

The Association Between Major Depressive Disorder and Outcomes in Older Veterans Hospitalized With Pneumonia.

BACKGROUND: Major depressive disorder ("depression") has been identified as an independent risk factor for mortality for many comorbid conditions, including heart failure, cancer and stroke. Major depressive disorder has also been linked to immune suppression by generating a chronic inflammatory state. However, the association between major depression and pneumonia has not been examined. The aim of this study was to examine the association between depression and outcomes, including mortality and intensive care unit admission, in Veterans hospitalized with pneumonia. MATERIALS AND METHODS: We conducted a retrospective national study using administrative data of patients hospitalized at any Veterans Administration acute care hospital. We included patients ≥65 years old hospitalized with pneumonia from 2002-2012. Depressed patients were further analyzed based on whether they were receiving medications to treat depression. We used generalized linear mixed effect models to examine the association of depression with the outcomes of interest after controlling for potential confounders. RESULTS: Patients with depression had a significantly higher 90-day mortality (odds ratio 1.12, 95% confidence interval 1.07-1.17) compared to patients without depression. Patients with untreated depression had a significantly higher 30-day (1.11, 1.04-1.20) and 90-day (1.20, 1.13-1.28) mortality, as well as significantly higher intensive care unit admission rates (1.12, 1.03-1.21), compared to patients with treated depression. CONCLUSION: For older veterans hospitalized with pneumonia, a concurrent diagnosis of major depressive disorder, and especially untreated depression, was associated with higher mortality. This highlights that untreated major depressive disorder is an independent risk factor for mortality for patients with pneumonia.

Impact of Concurrent Medication Use on Pancreatic Cancer Survival-SEER-Medicare Analysis.

OBJECTIVES: Preclinical studies have suggested that non-antineoplastic medication use may impact pancreatic cancer biology. We examined the association of several medication classes on pancreatic cancer survival in a large medical claims database. MATERIALS AND METHODS: Histologically confirmed pancreatic adenocarcinoma diagnosed between 2006 and 2009 were analyzed from the Surveillance, Epidemiology, and End Results-Medicare database with available part D data. Drug use was defined as having 2 prescriptions filled within 12 months of pancreatic cancer diagnosis. The following medication classes/combinations were analyzed: ß-blocker, statin, insulin, metformin, thiazolidinedione, warfarin, heparin, ß-blocker/statin, metformin/statin, and ß-blocker/metformin. Multivariable Cox proportional hazard models adjusting for age, sex, race, stage at diagnosis, site of cancer, and Charlson comorbidity index were constructed to test the association between medication classes and overall survival. RESULTS: A total of 13,702 patients were included in the study; median age 76 years, 42.5% males, 77.1% white. The most common anatomic site and stage at diagnosis were head of the pancreas (49.9%) and stage 4 (49.6%), respectively. Ninety-four percent of patients died in the follow-up period (median overall survival 5.3 mo). Multivariable Cox regression analysis showed that use of ß-blockers, heparin, insulin, and warfarin were significantly associated with improved survival (P<0.05 for each one), whereas metformin, thiazolidinedione, statin, and combination therapies were not. CONCLUSIONS: In this study, use of ß-blockers, heparin, insulin, and warfarin were associated with improved survival in patients with pancreatic cancer. Additional studies are needed to validate these findings in the clinical setting.

Impact of total body weight on 30-day mortality in patients with gram-negative bacteremia.

BACKGROUND: The impact of total body weight (TBW) on 30-day mortality associated with gram-negative bacteremia has not been previously evaluated. METHODS: The cohort included 323 patients >/ = 18 years old with gram-negative bacteremia (1/1/2008-8/31/2011) who received >/ = 48 hours of antibiotics. We compared 30-day mortality of TBW <70 kg vs. >/ = 70 kg with a multivariable stepwise logistic regression adjusting for age >/ = 70 years, cancer diagnosis, and Pitt bacteremia score of >/ = 4. RESULTS: The cohort was 57% TBW >/ = 70 kg and 43% TBW <70 kg. TBW >/ = 70 kg patients had lower 30-day mortality (11.0% vs. 16.3%), which was significant in the multivariable analysis (OR 0.45, 95% CI 0.21-0.97). Cancer and Pitt bacteremia score >/ = 4 were also independently associated with 30-day mortality. TBW was no longer significant when TBW <50 kg patients were excluded. CONCLUSION: TBW >/ = 70 kg was associated with an improved 30-day mortality; however, the high mortality rates for patients with a TBW < 50 kg is responsible for this association.

Statins and Lower Gastrointestinal Conditions: A Retrospective Cohort Study.

Several studies have reported constipation, abdominal pain, or diarrhea as common adverse events for statins. Statins are among the most commonly prescribed medications, and the impact on the prevalence of these conditions was rarely studied as main outcomes. The aim of this study is to determine if statin therapy is associated with constipation, abdominal pain, diarrhea, or colitis. This was a retrospective cohort study using a regional military health care data from October 1, 2003, to March 1, 2012. A propensity score-matched cohort of statin users and nonusers was created based on 82 variables. The primary analysis evaluated the odds ratios of the following diagnoses: constipation, ≥3 encounters for constipation; abdominal pain, ≥3 encounters for abdominal pain; diarrhea, ≥3 encounters for diarrhea; colitis, ≥3 encounters for colitis; and endoscopy of the lower gastrointestinal tract, ≥3 endoscopies of the lower gastrointestinal tract. After propensity score matching of 6342 statin users and 6342 nonusers, there was no statistically significant difference in constipation (OR, 0.96; 95%CI, 0.87-1.05; P = .33), abdominal pain (OR, 0.95; 95%CI, 0.88-1.02; P = .15), or colitis (OR, 1.02; 95%CI, 0.91-1.14; P = .73). However, there was an association between statin therapy and endoscopy of the lower gastrointestinal tract (OR, 1.14; 95%CI, 1.04-1.26; P = .002) and decreased odds of diarrhea (OR, 0.88; 95%CI, 0.80-0.97; P = .01). In this retrospective cohort study, an association between statin therapy and increased likelihood of being diagnosed with lower gastrointestinal conditions could not be demonstrated, contrary to some statins package inserts.

Statins for primary prevention in physically active individuals: Do the risks outweigh the benefits?

OBJECTIVES: There are little data on the potential benefits and adverse events of statins among physically fit individuals. Our objective was to examine the associations of statin use with beneficial cardiovascular outcomes and adverse events in active duty military (a surrogate for high level of physical fitness). DESIGN: This is a retrospective propensity score-matched cohort study of healthy active duty military (fiscal years [FY] 2002-2011). METHODS: Statin-users received statins during FY 2005 as their only prescription medication. FY 2002-2004 was used to describe baseline characteristics; and FY 2006-2011were used to capture outcomes. Study outcomes included major acute cardiovascular events (MACE), diabetes mellitus and its complications, kidney diseases, musculoskeletal diseases, obesity, and malignancy. RESULTS: We propensity score matched 837 statin-users to 2488 nonusers. During follow-up, 1.6% statin-users and 1.5% nonusers were diagnosed with MACE (odds ratio [OR] 1.05, 95% confidence interval [CI] 0.55-1.98), 12.5% of statin-users and 5.8% of nonusers were diagnosed with diabetes (OR 2.34, 95% CI 1.79-3.04), and 1.7% statin- users and 0.7% nonusers were diagnosed with diabetes with complication (OR 2.47, 95% CI 1.21-5.04). There were no differences in rates of other adverse events. CONCLUSIONS: Among healthy physically active individuals, statin use was associated with doubled the odds of diabetes and diabetic complications without countervailing cardiovascular benefits.

Long-Term Outcomes of Short-Term Statin Use in Healthy Adults: A Retrospective Cohort Study.

INTRODUCTION: Data suggest that the beneficial cardiovascular effects of statins are maximized after the first year of statin use; yet, the timeline of statin-associated adverse events is not well delineated. OBJECTIVE: To examine the associations of short-term statin use (≤1 year) with short- and long-term adverse events and beneficial cardiovascular outcomes in a 'healthy' cohort. PARTICIPANTS AND METHODS: A cohort study of a healthy Tricare population (fiscal year [FY] 2002 through FY 2011) who have no cardiovascular disease, major comorbidities requiring medications, or functional limitations. Statin users used statins for 90-365 days during FY 2005 as their only prescription medication. Nonusers had medical encounters but did not receive prescription medications during FY 2005, and did not receive any statins throughout the study period from FY 2002 to FY 2011. Outcomes were the occurrence of major acute cardiovascular events, diabetes mellitus and its complications, kidney diseases, musculoskeletal diseases, obesity, cataracts, malignancy, and death. RESULTS: We matched 1525 statin users to 1525 nonusers. During the follow-up period (FY 2006 to FY 2011), statin users had significantly higher odds of developing diabetes and diabetic complications that persisted throughout follow-up (odds ratio [OR] 1.93, 95 % confidence interval [CI] 1.55-2.41 and OR 2.15, 95 % CI 1.20-3.86, respectively). Short-term statin use was not associated with decreased odds of major acute cardiovascular events (OR 1.17, 95 % CI 0.72-1.92). There were no differences in risks of kidney diseases, musculoskeletal diseases, or malignancy. CONCLUSIONS: Short-term statin use for primary prevention in this healthy cohort was associated with an increased risk of long-term diabetes and diabetic complications without cardiovascular benefits. Further study using pragmatic studies and prospective observational studies appropriately equipped to eliminate unidentified confounders are urgently needed.