Tyler J VanderWeele

Harvard University, Cambridge, Massachusetts, United States

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Publications (193)812.7 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Observational studies of older adults showed higher mortality for first-generation antipsychotics than their second--generation counterparts, which led to US Food and Drug Administration warnings, but the actual mechanisms involved remain unclear. A cohort of 9,060 initiators of first-generation antipsychotics and 17,137 of second-generation antipsychotics enrolled in New Jersey and Pennsylvania Medicare were followed for 180 days. Medical events were assessed using diagnostic and procedure codes on inpatient billing claims. For the individual and joint set of medical events (mediators), we estimated the total, direct, and indirect effects of antipsychotic type (first versus second generation) on mortality on the risk ratio scale and the proportion mediated on the risk difference scale, obtaining 95% confidence intervals through bootstrapping. We performed bias analyses for false-negative mediator misclassification in claims data, with sensitivity ranging from 0.25 to 0.75. There were 3,199 deaths (outcomes), 862 cardiovascular events, 675 infectious events, and 491 hip fractures (potential mediators). Mortality was higher for first- than second-generation antipsychotic initiators (adjusted risk ratio: 1.14; 95% confidence interval: 1.06, 1.22). In naïve analyses, that ignored potential misclassification, less than 4% of this difference was explained by any particular medical event. In bias analyses, the proportion mediated ranged from 6% to 16% for stroke, 3% to 9% for ventricular arrhythmia, 3% to 11% for myocardial infarction, 0% venous thromboembolism, 3% to 9% for pneumonia, 0% to 1% for other bacterial infection, and 1% to 3% for hip fracture. Acute cardiovascular events and pneumonia may explain part of the mortality difference between first- and second-generation antipsychotic initiators in this analysis.
    Epidemiology (Cambridge, Mass.) 05/2015; DOI:10.1097/EDE.0000000000000321 · 6.18 Impact Factor
  • Zhichao Jiang, Tyler J VanderWeele
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    ABSTRACT: Assessment of indirect effects is useful for epidemiologists interested in understanding the mechanisms of exposure-outcome relationships. A traditional way of estimating indirect effects is to use the "difference method," which is based on regression analysis in which one adds a possible mediator to the regression model and examines whether the coefficient for the exposure changes. The difference method has been criticized for lacking a causal interpretation when it is used with logistic regression. In this article, we use the counterfactual framework to define the natural indirect effect (NIE) and assess the relationship between the NIE and the difference method. We show that under appropriate assumptions, the difference method consistently estimates the NIE for continuous outcomes and is always conservative for binary outcomes. Thus, the difference method can be used to provide evidence for the presence of mediation but not for the absence of mediation. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
    American journal of epidemiology 05/2015; DOI:10.1093/aje/kwv059 · 4.98 Impact Factor
  • Zhichao Jiang, Tyler J VanderWeele
    American journal of epidemiology 05/2015; DOI:10.1093/aje/kwv058 · 4.98 Impact Factor
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    ABSTRACT: Health care providers' lack of education on spiritual care is a significant barrier to the integration of spiritual care into health care services. The study objective was to describe the training program, Clinical Pastoral Education for Healthcare Providers (CPE-HP) and evaluate its impact on providers' spiritual care skills. Fifty CPE-HP participants completed self-report surveys at baseline and posttraining measuring frequency of and confidence in providing religious/spiritual (R/S) care. Four domains were assessed: (1) ability and (2) frequency of R/S care provision; (3) comfort using religious language; and (4) confidence in providing R/S care. At baseline, participants rated their ability to provide R/S care and comfort with religious language as "fair." In the previous two weeks, they reported approximately two R/S patient conversations, initiated R/S conversations less than twice, and prayed with patients less than once. Posttraining participants' reported ability to provide spiritual care increased by 33% (p<0.001). Their comfort using religious language improved by 29% (p<0.001), and frequency of R/S care increased 75% (p<0.001). Participants reported having 61% more (p<0.001) R/S conversations and more frequent prayer with patients (95% increase; p<0.001). Confidence in providing spiritual care improved by 36% overall, by 20% (p<0.001) with religiously concordant patients, and by 43% (p<0.001) with religiously discordant patients. This study suggests that CPE-HP is an effective approach for training health care providers in spiritual care. Dissemination of this training may improve integration of spiritual care into health care, thereby strengthening comprehensive patient-centered care.
    Journal of palliative medicine 04/2015; 18(5). DOI:10.1089/jpm.2014.0306 · 2.06 Impact Factor
  • Tyler J VanderWeele, Eric J Tchetgen Tchetgen
    Epidemiology (Cambridge, Mass.) 02/2015; 26(3). DOI:10.1097/EDE.0000000000000263 · 6.18 Impact Factor
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    ABSTRACT: The purpose of this study is to determine how oncology nurses and physicians view their role in providing spiritual care (SC), factors influencing this perception, and how this belief affects SC provision. This is a survey-based, multisite study conducted from October 2008 to January 2009. All oncology physicians and nurses caring for advanced cancer patients at four Boston, MA cancer centers were invited to participate; 339 participated (response rate = 63 %). Nurses were more likely than physicians to report that it is the role of medical practitioners to provide SC, including for doctors (69 vs. 49 %, p < 0.001), nurses (73 vs. 49 %, p < 0.001), and social workers (81 vs. 63 %, p = 0.001). Among nurses, older age was the only variable that was predictive of this belief [adjusted odds ratio (AOR) 1.08; 1.01-1.16, p = 0.02]. For nurses, role perception was not related to actual SC provision to patients. In contrast, physicians' role perceptions were influenced by their intrinsic religiosity (AOR, 1.44; 95 % CI, 1.09-1.89; p = 0.01) and spirituality (AOR, 6.41; 95 % CI, 2.31-17.73, p < 0.001). Furthermore, physicians who perceive themselves as having a role in SC provision reported greater SC provision to their last advanced cancer patients seen in clinic, 69 % compared to 31 %, p < 0.001. Nurses are more likely than physicians to perceive medical practitioners as having a role in SC provision. Physicians' perceptions of their role in SC provision are influenced by their religious/spiritual characteristics and are predictive of actual SC provision to patients. Spiritual care training that includes improved understanding of clinicians' appropriate role in SC provision to severely ill patients may lead to increased SC provision.
    Journal of Pain and Symptom Management 01/2015; 49(2). DOI:10.1007/s00520-015-2611-2 · 2.74 Impact Factor
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    ABSTRACT: Epidemiologic data on genetic susceptibility to cardiovascular effects of arsenic exposure from drinking water are limited. We investigated whether the association between well-water arsenic and cardiovascular disease (CVD) differed by 170 single nucleotide polymorphisms (SNPs) in 17 genes related to arsenic metabolism, oxidative stress, inflammation, and endothelial dysfunction. We conducted a prospective case-cohort study nested in the Health Effects of Arsenic Longitudinal Study, with a random subcohort of 1,375 subjects and 447 incident fatal and nonfatal cases of CVD. Well-water arsenic was measured in 2000 at baseline. The CVD cases, 56 of which occurred in the subcohort, included 238 coronary heart disease cases, 165 stroke cases, and 44 deaths due to other CVD identified during follow-up from 2000 to 2012. Of the 170 SNPs tested, multiplicative interactions between well-water arsenic and two SNPs, rs281432 in ICAM1 (Padj = 0.0002) and rs3176867 in VCAM1 (Padj = 0.035), were significant for CVD after adjustment for multiple testing. Compared with those with GC or CC genotype in rs281432 and lower well-water arsenic, the adjusted hazard ratio (aHR) for CVD was 1.82 (95% CI: 1.31, 2.54) for a 1-SD increase in well-water arsenic combined with the GG genotype, which was greater than expected given aHRs of 1.08 and 0.96 for separate effects of arsenic and the genotype alone, respectively. Similarly, the joint aHR for arsenic and the rs3176867 CC genotype was 1.34 (95% CI: 0.95, 1.87), greater than expected given aHRs for their separate effects of 1.02 and 0.84, respectively. Associations between CVD and arsenic exposure may be modified by genetic variants related to endothelial dysfunction.
    Environmental Health Perspectives 01/2015; DOI:10.1289/ehp.1307883 · 7.03 Impact Factor
  • Etsuji Suzuki, Tyler J VanderWeele
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    ABSTRACT: Under Bateson's original conception, the term "epistasis" is used to describe the situation in which the effect of a genetic factor at one locus is masked by a variant at another locus. Epistasis in the sense of masking has been termed "compositional epistasis." In general, statistical tests for interaction are of limited use in detecting compositional epistasis. Using recently developed epidemiological methods, however, it has been shown that there are relations between empirical data patterns and compositional epistasis. These relations can sometimes be exploited to empirically test for certain forms of compositional epistasis, by using alternative nonstandard tests for interaction.Using the counterfactual framework, we show conditions that can be empirically tested to determine whether there are individuals whose phenotype response patterns manifest epistasis in the sense of masking. Only under some very strong assumptions would tests for standard statistical interactions correspond to compositional epistasis. Even without such strong assumptions, however, one can still test whether there are individuals of phenotype response type representing compositional epistasis. The empirical conditions are quite strong, but the conclusions which tests of these conditions allow may be of interest in a wide range of studies. This chapter highlights that epidemiologic perspectives can be used to shed light on underlying mechanisms at the genetic, molecular, and cellular levels.
    Methods in molecular biology (Clifton, N.J.) 01/2015; 1253:197-216. DOI:10.1007/978-1-4939-2155-3_11 · 1.29 Impact Factor
  • Zhichao Jiang, Tyler J VanderWeele
    Epidemiology (Cambridge, Mass.) 01/2015; 26(1):e8-9. DOI:10.1097/EDE.0000000000000204 · 6.18 Impact Factor
  • Zhichao Jiang, Tyler J VanderWeele
    American Journal of Epidemiology 12/2014; DOI:10.1093/aje/kwu351 · 4.98 Impact Factor
  • Linda Valeri, Xihong Lin, Tyler J VanderWeele
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    ABSTRACT: Mediation analysis is a popular approach to examine the extent to which the effect of an exposure on an outcome is through an intermediate variable (mediator) and the extent to which the effect is direct. When the mediator is mis-measured, the validity of mediation analysis can be severely undermined. In this paper, we first study the bias of classical, non-differential measurement error on a continuous mediator in the estimation of direct and indirect causal effects in generalized linear models when the outcome is either continuous or discrete and exposure-mediator interaction may be present. Our theoretical results as well as a numerical study demonstrate that in the presence of non-linearities, the bias of naive estimators for direct and indirect effects that ignore measurement error can take unintuitive directions. We then develop methods to correct for measurement error. Three correction approaches using method of moments, regression calibration, and SIMEX are compared. We apply the proposed method to the Massachusetts General Hospital lung cancer study to evaluate the effect of genetic variants mediated through smoking on lung cancer risk. Copyright © 2014 John Wiley & Sons, Ltd.
    Statistics in Medicine 12/2014; 33(28). DOI:10.1002/sim.6295 · 2.04 Impact Factor
  • Tyler VanderWeele
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    ABSTRACT: The talk will survey some of the methodological challenges in assessing causality in religion and health research. While the field has seen increasing use of better longitudinal designs in assessing the relationship between religion and health, for certain questions considerable methodological challenges remain. For example, while it is the case that religious participation is longitudinally associated with less depression, it is also the case that those who become depressed are more likely to cease attending religious services. Such feedback, with causality in both directions, renders cross-section data useless, and requires causal modeling techniques, such as marginal structural models, to adequately assess the extent of the effects in both directions. Analyses using marginal structural models with the Nurses' Health Study data will be presented in studying this feedback between religious service attendance and depression. Another set of methodological challenges arises when interest lies in studying mechanisms governing the relationship between religious participation and health outcomes. The relevance of the literature on causal mediation analysis to religion and health research will be discussed generally, and analyses will be presented examining the mechanisms for the religion-mortality relationship in the Nurses' Health Study data.
    142nd APHA Annual Meeting and Exposition 2014; 11/2014
  • Tyler VanderWeele
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    ABSTRACT: This talk with present the work of the Spiegleman award winner Dr. Tyler VanderWeele. His methodologic research concerns how we distinguish between association and causation in the biomedical and social sciences and the study of the mechanisms by which causal effects arise. The current focus of my work includes the analysis of pathways, assessments of interaction, and the evaluation of network and spillover effects in which one person’s exposure will affect the outcomes of another. Dr. VanderWeele's research employs counterfactual theory and ideas from causal inference to clarify and formalize concepts used by epidemiologists, biomedical researchers and social scientists. His empirical work has been in the areas of perinatal, psychiatric and genetic epidemiology; various fields within the social sciences; and the study of religion and health. In perinatal epidemiology, he has worked on evaluating prenatal care indices, on the analysis of trends in birth outcomes, and on assessing the role of preterm birth in mediating the effects of prenatal exposures on mortality outcomes. In genetic epidemiology, he has been studying gene-environment interaction and the pathways by which genetic variants operate. In psychiatric epidemiology, he sudies the feedback and inter-relationships between depression, loneliness and subjective well-being. His work in the social sciences has included the study of educational interventions, micro-finance programs, social network effects, and judicial decisions. His work in religion and health is oriented towards assessing the mechanisms by which religion and spirituality affect health outcomes.
    142nd APHA Annual Meeting and Exposition 2014; 11/2014
  • Tyler J VanderWeele, Whitney R Robinson
    Epidemiology (Cambridge, Mass.) 11/2014; 25(6):937-938. DOI:10.1097/EDE.0000000000000186 · 6.18 Impact Factor
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    ABSTRACT: Causal inference with interference is a rapidly growing area. The literature has begun to relax the "no-interference" assumption that the treatment received by one individual does not affect the outcomes of other individuals. In this paper we briefly review the literature on causal inference in the presence of interference when treatments have been randomized. We then consider settings in which causal effects in the presence of interference are not identified, either because randomization alone does not suffice for identification, or because treatment is not randomized and there may be unmeasured confounders of the treatment-outcome relationship. We develop sensitivity analysis techniques for these settings. We describe several sensitivity analysis techniques for the infectiousness effect which, in a vaccine trial, captures the effect of the vaccine of one person on protecting a second person from infection even if the first is infected. We also develop two sensitivity analysis techniques for causal effects in the presence of unmeasured confounding which generalize analogous techniques when interference is absent. These two techniques for unmeasured confounding are compared and contrasted.
    Statistical Science 11/2014; 29(4):687-706. DOI:10.1214/14-STS479 · 1.69 Impact Factor
  • Tyler J VanderWeele
    International Journal of Epidemiology 10/2014; 43(5):1368-73. DOI:10.1093/ije/dyu162 · 9.20 Impact Factor
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    ABSTRACT: Additive interactions can have public health and etiological implications but are infrequently reported. We assessed departures from additivity on the absolute risk scale between 9 established breast cancer risk factors and 23 susceptibility single-nucleotide polymorphisms (SNPs) identified from genome-wide association studies among 10,146 non-Hispanic white breast cancer cases and 12,760 controls within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium. We estimated the relative excess risk due to interaction and its 95% confidence interval for each pairwise combination of SNPs and nongenetic risk factors using age- and cohort-adjusted logistic regression models. After correction for multiple comparisons, we identified a statistically significant relative excess risk due to interaction (uncorrected P = 4.51 × 10(-5)) between a SNP in the DNA repair protein RAD51 homolog 2 gene (RAD51L1; rs10483813) and body mass index (weight (kg)/height (m)(2)). We also compared additive and multiplicative polygenic risk prediction models using per-allele odds ratio estimates from previous studies for breast-cancer susceptibility SNPs and observed that the multiplicative model had a substantially better goodness of fit than the additive model.
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    ABSTRACT: Antipsychotic drugs are used to treat dementia-related symptoms in older adults, and observational studies show higher risks of death and stroke associated with the use of first-generation antipsychotic drugs (FGAs) compared with second-generation antipsychotic drugs (SGAs). However, the extent to which stroke explains the differential mortality risk between FGA use and SGA use in older adults is unclear. We followed those who initiated use of antipsychotic drugs (9,777 FGA users and 21,164 SGA users) aged 65 years or older, and who were enrolled in Medicare and either the New Jersey or Pennsylvania pharmacy assistance program during 1994 to 2005, over 180 days for the outcomes of stroke and death. We estimated direct and indirect effects by comparing 180-day mortality risks associated with the use of FGAs versus SGAs as mediated by stroke on the risk ratio scale, as well as the proportion mediated on the risk difference scale. FGA use was associated with marginally higher risks of stroke (risk ratio =1.24, 95% confidence interval (CI): 1.01, 1.53) and death (risk ratio = 1.15, 95% CI: 1.08, 1.22) compared with SGA use, but stroke explained little (2.7%) of the observed difference in mortality risk. The indirect effect was null (risk ratio = 1.004, 95% CI: 1.000, 1.008), and the direct effect was equal to the total effect of antipsychotic drug type (FGA vs. SGA) on mortality risk (risk ratio = 1.15, 95% CI: 1.08, 1.22). These results suggest that the difference in mortality risk between users of FGAs and SGAs may develop mostly through pathways that do not involve stroke.
    American Journal of Epidemiology 09/2014; 180(8). DOI:10.1093/aje/kwu210 · 4.98 Impact Factor
  • Tyler J VanderWeele, Eric J. Tchetgen Tchetgen
    Epidemiology (Cambridge, Mass.) 09/2014; 25(5):727-8. DOI:10.1097/EDE.0000000000000098 · 6.18 Impact Factor
  • Source
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    ABSTRACT: Observational studies have reported higher mortality among older adults treated with first-generation antipsychotics (FGAs) versus second-generation antipsychotics (SGAs). A few studies examined risk for medical events, including stroke, ventricular arrhythmia, venous thromboembolism, myocardial infarction, pneumonia, and hip fracture.
    PLoS ONE 08/2014; 9(8):e105376. DOI:10.1371/journal.pone.0105376 · 3.53 Impact Factor

Publication Stats

3k Citations
812.70 Total Impact Points


  • 2009–2014
    • Harvard University
      Cambridge, Massachusetts, United States
    • Northwestern University
      • Department of Preventive Medicine
      Evanston, IL, United States
    • University of Illinois at Chicago
      Chicago, Illinois, United States
  • 2006–2014
    • Harvard Medical School
      • Department of Medicine
      Boston, Massachusetts, United States
  • 2010–2013
    • Massachusetts Department of Public Health
      Boston, Massachusetts, United States
  • 2011
    • Princeton University
      Princeton, New Jersey, United States
    • Kinki University
      Ōsaka, Ōsaka, Japan
    • Eunice Kennedy Shriver National Institute of Child Health and Human Development
      Maryland, United States
  • 2006–2010
    • University of Chicago
      • Department of Health Studies
      Chicago, Illinois, United States
  • 2008
    • McLean Hospital
      • Biological Psychiatry Laboratory
      Cambridge, MA, United States