Eyal Shahar

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• Lutsey, P. L., Misialek, J. R., Mosley, T. H., Gottesman, R. F., Punjabi, N. M., Shahar, E., MacLehose, R., Ogilvie, R. P., Knopman, D., & Alonso, A. (2017). Sleep characteristics and risk of dementia and Alzheimer's disease: The Atherosclerosis Risk in Communities Study. Alzheimer's & dementia : the journal of the Alzheimer's Association, 14(2), 157-166.
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  This study tested the hypotheses that late-midlife obstructive sleep apnea (OSA) and short and long sleep duration are associated with dementia over 15 years of follow-up.
• Agarwala, A., Pokharel, Y., Saeed, A., Sun, W., Virani, S. S., Nambi, V., Ndumele, C., Shahar, E., Heiss, G., Boerwinkle, E., Konety, S., Hoogeveen, R. C., & Ballantyne, C. M. (2017). The association of lipoprotein(a) with incident heart failure hospitalization: Atherosclerosis Risk in Communities study. Atherosclerosis, 262, 131-137.
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  Lipoprotein(a) [Lp(a)] is a proatherogenic lipoprotein associated with coronary heart disease, ischemic stroke, and more recently aortic stenosis and heart failure (HF). We examined the association of Lp(a) levels with incident HF hospitalization in the Atherosclerosis Risk in Communities (ARIC) study. We also assessed the relationship between Lp(a) levels and arterial stiffness as a potential mechanism for development of HF.
• Shahar, D. J., & Shahar, E. (2017). A Theorem at the Core of Colliding Bias. The international journal of biostatistics, 13(1).
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  Conditioning on a shared outcome of two variables can alter the association between these variables, possibly adding a bias component when estimating effects. In particular, if two causes are marginally independent, they might be dependent in strata of their common effect. Explanations of the phenomenon, however, do not explicitly state when dependence will be created and have been largely informal. We prove that two, marginally independent, causes will be dependent in a particular stratum of their shared outcome if and only if they modify each other's effects, on a probability ratio scale, on that value of the outcome variable. Using our result, we also qualify the claim that such causes will "almost certainly" be dependent in at least one stratum of the outcome: dependence must be created in one stratum of a binary outcome, and independence can be maintained in every stratum of a trinary outcome.
• Folsom, A. R., Gottesman, R. F., Appiah, D., Shahar, E., & Mosley, T. H. (2016). Plasma d-Dimer and Incident Ischemic Stroke and Coronary Heart Disease: The Atherosclerosis Risk in Communities Study. Stroke, 47(1), 18-23.
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  Epidemiological studies have documented that plasma d-dimer, a fibrin degradation product, is a risk marker for coronary heart disease, but there is limited prospective evidence for stroke. Given that thrombosis is a key mechanism for many strokes, we studied whether d-dimer is a risk marker for ischemic stroke incidence in the Atherosclerosis Risk in Communities (ARIC) Study.
• Lutsey, P. L., Norby, F. L., Gottesman, R. F., Mosley, T., MacLehose, R. F., Punjabi, N. M., Shahar, E., Jack, C. R., & Alonso, A. (2016). Sleep Apnea, Sleep Duration and Brain MRI Markers of Cerebral Vascular Disease and Alzheimer's Disease: The Atherosclerosis Risk in Communities Study (ARIC). PloS one, 11(7), e0158758.
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  A growing body of literature has suggested that obstructive sleep apnea (OSA) and habitual short sleep duration are linked to poor cognitive function. Neuroimaging studies may provide insight into this relation.
• Nagayoshi, M., Lutsey, P. L., Benkeser, D., Wassel, C. L., Folsom, A. R., Shahar, E., Iso, H., Allison, M. A., Criqui, M. H., & Redline, S. (2016). Association of sleep apnea and sleep duration with peripheral artery disease: The Multi-Ethnic Study of Atherosclerosis (MESA). Atherosclerosis, 251, 467-75.
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  Numerous biological pathways linking sleep disturbances to atherosclerosis have been identified, such as insulin resistance, inflammation, hypertension, and endothelial dysfunction. Yet, the association of sleep apnea and sleep duration with peripheral artery disease (PAD) is not well characterized.
• Nagayoshi, M., Punjabi, N. M., Selvin, E., Pankow, J. S., Shahar, E., Iso, H., Folsom, A. R., & Lutsey, P. L. (2016). Obstructive sleep apnea and incident type 2 diabetes. Sleep medicine, 25, 156-161.
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  To determine whether severity of obstructive sleep apnea is associated with incident diabetes in middle-aged and older adults.
• Wang, W., Shen, G., Shahar, E., Bidulescu, A., Kimberly, W. T., Sheth, K. N., Campbell, B. W., Horbal, S., Correa, A., & Griswold, M. E. (2016). Forced Expiratory Volume in the First Second and Aldosterone as Mediators of Smoking Effect on Stroke in African Americans: The Jackson Heart Study. Journal of the American Heart Association, 5(1).
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  Cigarette smoking is a risk factor for stroke, but the mechanisms by which smoking contributes to stroke are not well understood. This study aimed to evaluate the roles of lung function (represented by forced expiratory volume in the first second (FEV1)) and aldosterone as potential mediators of the association of smoking with stroke.
• Carty, C. L., Keene, K. L., Cheng, Y., Meschia, J. F., Chen, W., Nalls, M., Bis, J. C., Kittner, S. J., Rich, S. S., Tajuddin, S., Zonderman, A. B., Evans, M. K., Langefeld, C. D., Gottesman, R., Mosley, T. H., Shahar, E., Woo, D., Yaffe, K., Liu, Y., , Sale, M. M., et al. (2015). Meta-Analysis of Genome-Wide Association Studies Identifies Genetic Risk Factors for Stroke in African Americans. Stroke; a journal of cerebral circulation, 46(8), 2063-8.
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  The majority of genome-wide association studies (GWAS) of stroke have focused on European-ancestry populations; however, none has been conducted in African Americans, despite the disproportionately high burden of stroke in this population. The Consortium of Minority Population Genome-Wide Association Studies of Stroke (COMPASS) was established to identify stroke susceptibility loci in minority populations.
• Jones, S. B., Loehr, L., Avery, C. L., Gottesman, R. F., Wruck, L., Shahar, E., & Rosamond, W. D. (2015). Midlife Alcohol Consumption and the Risk of Stroke in the Atherosclerosis Risk in Communities Study. Stroke; a journal of cerebral circulation, 46(11), 3124-30.
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  Alcohol consumption is common in the United States and may confer beneficial cardiovascular effects at light-to-moderate doses. The alcohol-stroke relationship remains debated. We estimated the relationship between midlife, self-reported alcohol consumption and ischemic stroke and intracerebral hemorrhage (ICH) in a biracial cohort.
• Lutsey, P. L., Bengtson, L. G., Punjabi, N. M., Shahar, E., Mosley, T. H., Gottesman, R. F., Wruck, L. M., MacLehose, R. F., & Alonso, A. (2015). Obstructive Sleep Apnea and 15-Year Cognitive Decline: The Atherosclerosis Risk in Communities (ARIC) Study. Sleep.
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  Prospective data evaluating abnormal sleep quality and quantity with cognitive decline are limited because most studies used subjective data and/or had short follow-up. We hypothesized that, over 15 y of follow-up, participants with objectively measured obstructive sleep apnea (OSA) and other indices of poor sleep quantity and quality would experience greater decline in cognitive functioning than participants with normal sleep patterns.
• Lutsey, P. L., McClelland, R. L., Duprez, D., Shea, S., Shahar, E., Nagayoshi, M., Budoff, M., Kaufman, J. D., & Redline, S. (2015). Objectively measured sleep characteristics and prevalence of coronary artery calcification: the Multi-Ethnic Study of Atherosclerosis Sleep study. Thorax, 70(9), 880-7.
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  We tested whether objectively measured indices of obstructive sleep apnoea (OSA) and sleep quality are associated with coronary artery calcification (CAC) prevalence independent of obesity, a classic confounder.
• O'Brien, E. C., Greiner, M. A., Sims, M., Hardy, N. C., Wang, W., Shahar, E., Hernandez, A. F., & Curtis, L. H. (2015). Depressive Symptoms and Risk of Cardiovascular Events in Blacks: Findings From the Jackson Heart Study. Circulation. Cardiovascular quality and outcomes, 8(6), 552-9.
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  Most studies of depression and cardiovascular risk have been conducted in white populations. We investigated this association in a community-based cohort of blacks.
• Shahar, E., & Shahar, D. J. (2015). On which variable(s) should we condition to remove confounding bias?. British Journal of Medicine and Medical Research.
• Bis, J. C., DeStefano, A., Liu, X., Brody, J. A., Choi, S. H., Verhaaren, B. F., Debette, S., Ikram, M. A., Shahar, E., Butler, K. R., Gottesman, R. F., Muzny, D., Kovar, C. L., Psaty, B. M., Hofman, A., Lumley, T., Gupta, M., Wolf, P. A., van Duijn, C., , Gibbs, R. A., et al. (2014). Associations of NINJ2 sequence variants with incident ischemic stroke in the Cohorts for Heart and Aging in Genomic Epidemiology (CHARGE) consortium. PloS one, 9(6), e99798.
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  Stroke, the leading neurologic cause of death and disability, has a substantial genetic component. We previously conducted a genome-wide association study (GWAS) in four prospective studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and demonstrated that sequence variants near the NINJ2 gene are associated with incident ischemic stroke. Here, we sought to fine-map functional variants in the region and evaluate the contribution of rare variants to ischemic stroke risk.
• Ibrahim-Verbaas, C. A., Fornage, M., Bis, J. C., Choi, S. H., Psaty, B. M., Meigs, J. B., Rao, M., Nalls, M., Fontes, J. D., O'Donnell, C. J., Kathiresan, S., Ehret, G. B., Fox, C. S., Malik, R., Dichgans, M., Schmidt, H., Lahti, J., Heckbert, S. R., Lumley, T., , Rice, K., et al. (2014). Predicting stroke through genetic risk functions: the CHARGE Risk Score Project. Stroke; a journal of cerebral circulation, 45(2), 403-12.
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  Beyond the Framingham Stroke Risk Score, prediction of future stroke may improve with a genetic risk score (GRS) based on single-nucleotide polymorphisms associated with stroke and its risk factors.
• Jones, S. A., Gottesman, R. F., Shahar, E., Wruck, L., & Rosamond, W. D. (2014). Validity of hospital discharge diagnosis codes for stroke: the Atherosclerosis Risk in Communities Study. Stroke; a journal of cerebral circulation, 45(11), 3219-25.
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  Characterizing International Classification of Disease 9th Revision, Clinical Modification (ICD-9-CM) code validity is essential given widespread use of hospital discharge databases in research. Using the Atherosclerosis Risk in Communities (ARIC) Study, we estimated the accuracy of ICD-9-CM stroke codes.
• Koton, S., Schneider, A. L., Rosamond, W. D., Shahar, E., Sang, Y., Gottesman, R. F., & Coresh, J. (2014). Stroke incidence and mortality trends in US communities, 1987 to 2011. JAMA, 312(3), 259-68.
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  Prior studies have shown decreases in stroke mortality over time, but data on validated stroke incidence and long-term trends by race are limited.
• Kwon, Y., Duprez, D. A., Jacobs, D. R., Nagayoshi, M., McClelland, R. L., Shahar, E., Budoff, M., Redline, S., Shea, S., Carr, J. J., & Lutsey, P. L. (2014). Obstructive sleep apnea and progression of coronary artery calcium: the multi-ethnic study of atherosclerosis study. Journal of the American Heart Association, 3(5), e001241.
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  Obstructive sleep apnea (OSA) is a common condition associated with cardiovascular disease. Its potential effect on progression of subclinical atherosclerosis is not well understood. We tested the hypothesis that self-reported OSA is associated with progression of coronary artery calcium (CAC). We also evaluated whether traditional cardiovascular risk factors accounted for the association.
• Shahar, E. (2014). Apnea-hypopnea index: time to wake up. Nature and science of sleep, 6, 51-6.
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  Despite the widespread use of the apnea-hypopnea index in research, its scientific and statistical properties have not been examined thoroughly. The index may be viewed either as a rate (number of events per hour of sleep) or as a ratio of two variables (number of events/number of hours of sleep). When considered as a rate, the apnea-hypopnea index may be modeled as the dependent variable, provided that researchers explicitly state which physical property they assume to be measuring. On the other hand, the index is rarely, if ever, the preferred model of exposure to sleep-disordered breathing (an independent variable), regardless of whether it is considered a rate or a ratio variable. Continued indiscriminate use of the apnea-hypopnea index in sleep research should be discouraged.
• Snyder, M. L., Love, S., Sorlie, P. D., Rosamond, W. D., Antini, C., Metcalf, P. A., Hardy, S., Suchindran, C. M., Shahar, E., & Heiss, G. (2014). Redistribution of heart failure as the cause of death: the Atherosclerosis Risk in Communities Study. Population health metrics, 12(1), 10.
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  Heart failure is sometimes incorrectly listed as the underlying cause of death (UCD) on death certificates, thus compromising the accuracy and comparability of mortality statistics. Statistical redistribution of the UCD has been used to examine the effect of misclassification of the UCD attributed to heart failure, but sex- and race-specific redistribution of deaths on coronary heart disease (CHD) mortality in the United States has not been examined.
• Chang, P. P., Chambless, L. E., Shahar, E., Bertoni, A. G., Russell, S. D., Ni, H., He, M., Mosley, T. H., Wagenknecht, L. E., Samdarshi, T. E., Wruck, L. M., & Rosamond, W. D. (2013). Incidence and Survival of Hospitalized Acute Decompensated Heart Failure in Four US Communities (from the Atherosclerosis Risk in Communities Study). The American journal of cardiology.
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  Most population-based estimates of incident hospitalized heart failure (HF) have not differentiated acute decompensated heart failure (ADHF) from chronic stable HF nor included racially diverse populations. The Atherosclerosis Risk in Communities Study conducted surveillance of hospitalized HF events (age ≥55 years) in 4 US communities. We estimated hospitalized ADHF incidence and survival by race and gender. Potential 2005 to 2009 HF hospitalizations were identified by International Classification of Diseases, Ninth Revision, Clinical Modification, codes; 6,168 records were reviewed to validate ADHF cases. Population estimates were derived from US Census data; 50% of eligible hospitalizations were classified as ADHF, of which 63.6% were incident ADHF and 36.4% were recurrent ADHF. The average incidence of hospitalized ADHF was 11.6 per 1,000 persons, aged ≥55 years, per year, and recurrent hospitalized ADHF was 6.6 per 1,000 persons/yr. Age-adjusted annual ADHF incidence was highest for black men (15.7 per 1,000), followed by black women (13.3 per 1,000), white men (12.3 per 1,000), and white women (9.9 per 1,000). Of incident ADHF events with heart function assessment (89%), 53% had reduced the ejection fraction (heart failure with reduced ejection fraction [HFrEF]) and 47% had preserved ejection fraction (heart failure with preserved ejection fraction [HFpEF]). Black men had the highest proportion of acute HFrEF events (70%); white women had the highest proportion of acute HFpEF (59%). Age-adjusted 28-day and 1-year case fatality after an incident ADHF was 10.4% and 29.5%, respectively. Survival did not differ by race or gender. In conclusion, ADHF hospitalization and HF type varied by both race and gender, but case fatality rates did not. Further studies are needed to explain why black men are at higher risk of hospitalized ADHF and HFrEF.
• Huxley, R. R., Bell, E. J., Lutsey, P. L., Bushnell, C., Shahar, E., Rosamond, W., Gottesman, R., & Folsom, A. (2013). A comparative analysis of risk factors for stroke in blacks and whites: the Atherosclerosis Risk in Communities study. Ethnicity & health.
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  Objective Previous studies have speculated that the higher stroke incidence rate (IR) in blacks compared with whites may be due, in part, to stroke risk factors exerting a more adverse effect among blacks than whites. To determine whether such racial differences exist we compared the prospective associations between novel, traditional, and emerging stroke risk factors in blacks and whites. Design Baseline characteristics on risk factor levels were obtained on 15,407 participants from the Atherosclerosis Risk in Communities Study. Stroke incidence was ascertained from 1987 to 2008. Adjusted Cox proportional hazard models were used to compute hazard ratios (HRs) and their 95% confidence intervals (CIs) for stroke in relation to stroke risk factor levels stratified by race. Results During follow-up, 988 stroke events occurred: blacks had higher stroke incident rates compared with whites with the greatest difference in those aged
• Loehr, L. R., Agarwal, S. K., Baggett, C., Wruck, L. M., Chang, P. P., Solomon, S. D., Shahar, E., Ni, H., Rosamond, W. D., & Heiss, G. (2013). Classification of acute decompensated heart failure (ADHF): an automated algorithm compared to a physician reviewer panel: the ARIC study. Circulation Heart Failure.
• Shahar, E., & Shahar, D. J. (2013). Causal diagrams and the cross-sectional study. Clinical epidemiology, 5.
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  The cross-sectional study design is sometimes avoided by researchers or considered an undesired methodology. Possible reasons include incomplete understanding of the research design, fear of bias, and uncertainty about the measure of association. Using causal diagrams and certain premises, we compared a hypothetical cross-sectional study of the effect of a fertility drug on pregnancy with a hypothetical cohort study. A side-by-side analysis showed that both designs call for a tradeoff between information bias and variance and that neither offers immunity to sampling colliding bias (selection bias). Confounding bias does not discriminate between the two designs either. Uncertainty about the order of causation (ambiguous temporality) depends on the nature of the postulated cause and the measurement method. We conclude that a cross-sectional study is not inherently inferior to a cohort study. Rather than devaluing the cross-sectional design, threats of bias should be evaluated in the context of a concrete study, the causal question at hand, and a theoretical causal structure.
• Shahar, E., & Shahar, E. -. (2013). A new criterion for confounder selection? Neither a confounder nor science. Journal of evaluation in clinical practice, 19(5).
• Shahar, E., & Shahar, E. -. (2013). Causal diagrams, gastroesophageal reflux and erosive oesophagitis. Journal of evaluation in clinical practice, 19(5).
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  Gastroesophageal reflux and its consequences have inspired numerous research questions in recent years: are non-erosive reflux disease (NERD) and erosive oesophagitis phenotypic expressions of gastroesophageal reflux disease? Why do patients with NERD not respond to treatment as well as patients with erosive oesophagitis? What is the natural history of NERD? Causal diagrams, coupled with conditional probabilities, offer clear and surprising answers.
• Shahar, E., Shahar, E. -., & Shahar, D. J. (2013). Causal diagrams, the placebo effect, and the expectation effect. International journal of general medicine, 6.
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  Using causal diagrams, a formal research methodology, we analyzed several definitions of placebo and the placebo effect. We conclude that placebo is an ambiguous, redundant term and that the so-called placebo effect conceals far more interesting effects that are attributed to the patient's expectation. Biomedical research will benefit from abandoning the term placebo effect and focusing instead on a deeper understanding of the expectation variable, including its causes, effects, and effect modifiers. This avenue of research should be pursued by observational cohorts that are nested within clinical trials.
• Shahar, E., Shahar, E. -., & Shahar, D. J. (2013). Marginal structural models: much ado about (almost) nothing. Journal of evaluation in clinical practice, 19(1).
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  Marginal structural models were developed to account for a so-called time-dependent confounder and to estimate the presumed effect of 'treatment regime' (treatment over time). We present a set of causal axioms, according to which the problem of time-dependent confounding does not exist, and 'treatment regime' affects nothing. Per our axiomatization, marginal structural models do not introduce a new idea of deconfounding, but simply estimate a weighted average of effects. Whenever a weighted average and the weighting scheme can both be rationalized, the models are acceptable. Whenever a weighted average does not estimate an effect (e.g. important effect modification is ignored), or the weights are senseless - the models should not be fit.
• Shahar, E., & Shahar, E. -. (2012). A method to detect an unknown confounder: something from nothing?. Journal of evaluation in clinical practice, 18(3).
• Shahar, E., Shahar, E. -., & Shahar, D. J. (2012). Causal diagrams and change variables. Journal of evaluation in clinical practice, 18(1).
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  The true change in the value of a variable between two time points is often assumed to be a cause or an effect of interest. To our knowledge, this assumption is based on intuition, rather than on any formal theoretical justification.
• Shahar, E., Shahar, E. -., & Shahar, D. J. (2012). Causal diagrams and the logic of matched case-control studies. Clinical epidemiology, 4.
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  It is tempting to assume that confounding bias is eliminated by choosing controls that are identical to the cases on the matched confounder(s). We used causal diagrams to explain why such matching not only fails to remove confounding bias, but also adds colliding bias, and why both types of bias are removed by conditioning on the matched confounder(s). As in some publications, we trace the logic of matching to a possible tradeoff between effort and variance, not between effort and bias. Lastly, we explain why the analysis of a matched case-control study - regardless of the method of matching - is not conceptually different from that of an unmatched study.
• Shahar, E., & Shahar, E. -. (2010). Metabolic syndrome? A critical look from the viewpoints of causal diagrams and statistics. Journal of cardiovascular medicine (Hagerstown, Md.), 11(10).
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  The debate on the metabolic syndrome has attracted great interest among physicians and researchers. This article sheds new light on the term by using a tool called causal diagrams (also known as causal directed acyclic graphs). Formal analysis according to causal and statistical principles reveals little substance behind the new syndrome, as well as numerous false claims. From a research viewpoint, continued use of a variable called 'metabolic syndrome status' should be discouraged.
• Shahar, E., & Shahar, E. -. (2009). Causal diagrams for encoding and evaluation of information bias. Journal of evaluation in clinical practice, 15(3).
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  Epidemiologists and clinical researchers usually classify bias into three main categories: confounding, selection bias and information bias. Previous authors have described the first two categories in the logic and notation of causal diagrams, formally known as directed acyclic graphs (DAG).
• Shahar, E., & Shahar, E. -. (2009). Evaluating the effect of change on change: a different viewpoint. Journal of evaluation in clinical practice, 15(1).
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  When a causal variable and its presumed effect are measured at two time points in a cohort study, most researchers prefer to fit some type of a change model. Many of them believe that such an analysis is superior to a cross-sectional analysis 'because change models estimate the effect of change on change', which sounds epistemologically stronger than 'estimating a cross-sectional association'.
• Shahar, E., & Shahar, E. -. (2009). Making sense of health statistics?. Journal of evaluation in clinical practice, 15(6).
• Shahar, E., & Shahar, E. -. (2009). The association of body mass index with health outcomes: causal, inconsistent, or confounded?. American journal of epidemiology, 170(8).
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  According to the definition of confounding in a causal diagram, the association of body mass index (weight (kg)/height (m)(2)) with health-related outcomes is almost always noncausal, attributable to confounding by weight and perhaps height. The same conclusion holds for any other deterministic derivation from weight and height. No causal knowledge is gained by estimating a nonexistent effect of body mass index.
• Shahar, E., Shahar, E. -., & Shahar, D. J. (2009). On the causal structure of information bias and confounding bias in randomized trials. Journal of evaluation in clinical practice, 15(6).
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  Randomized trials are undoubtedly different from observational studies, but authors sometimes propose differences between these designs that do not exist. In this article we examine two claims about randomized trials: first, a recent claim that the causal structure of exposure measurement (information) bias in a randomized trial differs from the causal structure of that bias in an observational study. Second, a long-standing claim that confounding bias cannot operate in a randomized trial - if randomization was perfectly implemented. Using causal diagrams (causal directed acyclic graphs), we show that both claims are false in the context of an intention-to-treat analysis. We also describe a previously unrecognized mechanism of information bias, and suggest that the term 'information bias' should replace the terms 'measurement bias' and 'observation bias'.
• Shahar, E., & Shahar, E. -. (2007). Commentary: interpreting the interpretation. Journal of evaluation in clinical practice, 13(4).
• Shahar, E., & Shahar, E. -. (2007). Estimating causal parameters without target populations. Journal of evaluation in clinical practice, 13(5).
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  In recent years, numerous research methodologists have argued forcefully that any estimated effect from an observational study or a randomized trial should apply to a 'target population'- to a finite group of people. Some methods to adjust for confounders heavily draw upon this idea.
• Shahar, E., & Shahar, E. -. (2007). On editorial practice and peer review. Journal of evaluation in clinical practice, 13(4).

Others

• Shahar, E. (2014, Dec). Reflux, Barrett's esophagus and esophageal adenocarcinoma. Scandinavian journal of gastroenterology.