Person:

VanderWeele, Tyler

Background: To investigate the attitudes of premarital couples towards the premarital screening program after the abolition of compulsory screening in China and to study the factors influencing participation. Methods: Between July 1st 2010 to August 31st 2010, 650 people who registered for marriage at the civil affairs bureau of Wuhan, Suizhou, Zaoyang in Hubei province were studied using questionnaires. Logistic regression was used to examine the factors influencing participation in the premarital screening program. Results: The premarital screening rate was 34.8% (95% Confidence Interval: 31.0% to 38.5%). Several demographic factors (age, residence, profession), awareness, knowledge, and attitudes towards premarital screening all had significant influence on participation in the premarital screening program. Conclusions: Promotion activities and health education to improve knowledge and attitudes to premarital screening will help increase the rate of voluntary premarital screening.

Background: 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. Objectives: 1) Review robust epidemiologic evidence comparing mortality and medical event risk between FGAs and SGAs in older adults; 2) Quantify how much these medical events explain the observed mortality difference between FGAs and SGAs. Data sources Pubmed and Science Citation Index. Study eligibility criteria, participants, and interventions Studies of antipsychotic users that: 1) evaluated mortality or medical events specified above; 2) restricted to populations with a mean age of 65 years or older 3) compared FGAs to SGAs, or both to a non-user group; (4) employed a “new user” design; (5) adjusted for confounders assessed prior to antipsychotic initiation; (6) and did not require survival after antipsychotic initiation. A separate search was performed for mortality estimates associated with the specified medical events. Study appraisal and synthesis methods For each medical event, we used a non-parametric model to estimate lower and upper bounds for the proportion of the mortality difference—comparing FGAs to SGAs—mediated by their difference in risk for the medical event. Results: We provide a brief, updated summary of the included studies and the biological plausibility of these mechanisms. Of the 1122 unique citations retrieved, we reviewed 20 observational cohort studies that reported 28 associations. We identified hip fracture, stroke, myocardial infarction, and ventricular arrhythmias as potential intermediaries on the causal pathway from antipsychotic type to death. However, these events did not appear to explain the entire mortality difference. Conclusions: The current literature suggests that hip fracture, stroke, myocardial infarction, and ventricular arrhythmias partially explain the mortality difference between SGAs and FGAs.

Objectives To prospectively assess the joint association of birth weight and established lifestyle risk factors in adulthood with incident type 2 diabetes and to quantitatively decompose the attributing effects to birth weight only, to adulthood lifestyle only, and to their interaction. Design: Prospective cohort study. Setting: Health Professionals Follow-up Study (1986-2010), Nurses’ Health Study (1980-2010), and Nurses’ Health Study II (1991-2011). Participants: 149 794 men and women without diabetes, cardiovascular disease, or cancer at baseline. Main outcome measure Incident cases of type 2 diabetes, identified through self report and validated by a supplementary questionnaire. Unhealthy lifestyle was defined on the basis of body mass index, smoking, physical activity, alcohol consumption, and the alternate healthy eating index. Results: During 20-30 years of follow-up, 11 709 new cases of type 2 diabetes were documented. The multivariate adjusted relative risk of type 2 diabetes was 1.45 (95% confidence interval 1.32 to 1.59) per kg lower birth weight and 2.10 (1.71 to 2.58) per unhealthy lifestyle factor. The relative risk of type 2 diabetes associated with a combination of per kg lower birth weight and per unhealthy lifestyle factor was 2.86 (2.26 to 3.63), which was more than the addition of the risk associated with each individual factor, indicating a significant interaction on an additive scale (P for interaction<0.001). The attributable proportions of joint effect were 22% (95% confidence interval 18.3% to 26.4%) to lower birth weight alone, 59% (57.1% to 61.5%) to unhealthy lifestyle alone, and 18% (13.9% to 21.3%) to their interaction. Conclusion: Most cases of type 2 diabetes could be prevented by the adoption of a healthier lifestyle, but simultaneous improvement of both prenatal and postnatal factors could further prevent additional cases.

Background: Relatively little is known about the peer influence in health behaviors within university dormitory rooms. Moreover, in China, the problem of unhealthy behaviors among university students has not yet been sufficiently recognized. We thus investigated health behavior peer influence in Peking University dormitories utilizing a randomized cluster-assignment design. Methods: Study design: Cross-sectional in-dormitory survey. Study population: Current students from Peking University Health Science Center from April to June, 2009. Measurement: Self-reported questionnaire on health behaviors: physical activity (including bicycling), dietary intake and tobacco use. Results: Use of bicycle, moderate-intensity exercise, frequency of sweet food and soybean milk intake, frequency of roasted/baked/toasted food intake were behaviors significantly or marginally significantly affected by peer influence. Conclusion: Health behavior peer effects exist within dormitory rooms among university students. This could provide guidance on room assignment, or inform intervention programs. Examining these may demand attention from university administrators and policy makers.

Mammographic breast density has been found to be associated with breast cancer risk. Many of the traditional risk factors for breast cancer are themselves associated with mammographic breast density. A natural question that arises in this setting is the extent to which the effects of breast cancer risk factors are mediated by breast density and the extent to which such effects are through other pathways. We discuss analytic approaches to address these questions of mediation and also discuss how such approaches can accommodate potential interaction between risk factors and mammographic density and can accommodate case-control study designs.

Background: Mediation analysis is useful for understanding mechanisms and has been used minimally in the study of the environment and disease. Objective: We examined mediation of the association between phthalate exposure during pregnancy and preterm birth by oxidative stress. Methods: This nested case–control study of preterm birth (n = 130 cases, 352 controls) included women who delivered in Boston, Massachusestts, from 2006 through 2008. Phthalate metabolites and 8-isoprostane, an oxidative stress biomarker, were measured in urine from three visits in pregnancy. We applied four counterfactual mediation methods: method 1, utilizing exposure and mediator averages; method 2, using averages but allowing for an exposure–mediator interaction; method 3, incorporating longitudinal measurements of the exposure and mediator; and method 4, using longitudinal measurements and allowing for an exposure–mediator interaction. Results: We observed mediation of the associations between phthalate metabolites and all preterm birth by 8-isoprostane, with the greatest estimated proportion mediated observed for spontaneous preterm births specifically. Fully utilizing repeated measures of the exposure and mediator improved precision of indirect (i.e., mediated) effect estimates, and including an exposure–mediator interaction increased the estimated proportion mediated. For example, for mono(2-ethyl-carboxy-propyl) phthalate (MECPP), a metabolite of di(2-ethylhexyl) phthalate (DEHP), the percent of the total effect mediated by 8-isoprostane increased from 47% to 60% with inclusion of an exposure–mediator interaction term, in reference to a total adjusted odds ratio of 1.67 or 1.48, respectively. Conclusions: This demonstrates mediation of the phthalate–preterm birth relationship by oxidative stress, and the utility of complex regression models in capturing mediated associations when repeated measures of exposure and mediator are available and an exposure–mediator interaction may exist. Citation: Ferguson KK, Chen YH, VanderWeele TJ, McElrath TF, Meeker JD, Mukherjee B. 2017. Mediation of the relationship between maternal phthalate exposure and preterm birth by oxidative stress with repeated measurements across pregnancy. Environ Health Perspect 125:488–494; http://dx.doi.org/10.1289/EHP282

Purpose To measure the frequency of prescription medication changes following direct-to-consumer personal genomic testing (DTC-PGT) and their association with the pharmacogenomic results received. Methods: New DTC-PGT customers were enrolled in 2012 and completed surveys prior to return of results and 6 months post-results; DTC-PGT results were linked to survey data. ‘Atypical response’ pharmacogenomic results were defined as those indicating an increase or decrease in risk of an adverse drug event or likelihood of therapeutic benefit. At follow-up, participants reported prescription medication changes and health care provider consultation. Results: Follow-up data were available from 961 participants, of which 54 (5.6%) reported changing a medication they were taking, or starting a new medication, due to their DTC-PGT results. Of these, 45 (83.3%) reported consulting with a health care provider regarding the change. Pharmacogenomic results were available for 961 participants, of which 875 (91.2%) received ≥1 atypical response result. For each such result received, the odds of reporting a prescription medication change increased 1.57 times (95% confidence interval = 1.17, 2.11). Conclusion: Receipt of pharmacogenomic results indicating atypical drug response is common with DTC-PGT, and associated with prescription medication changes; however, fewer than 1% of consumers report unsupervised changes at 6 months post-testing.

Sensitivity analysis can be useful in assessing how robust associations are to potential unmeasured or uncontrolled confounding. In this paper we introduce a new measure that we call the “E-value,” a measure related to the evidence for causality in observational studies, when they are potentially subject to confounding. The E-value is defined as the minimum strength of association on the risk ratio scale that an unmeasured confounder would need to have with both the treatment and the outcome to fully explain away a specific treatment-outcome association, conditional on the measured covariates. A large E-value implies considerable unmeasured confounding would be needed to explain away an effect estimate. A small E-value implies little unmeasured confounding would be needed to explain away an effect estimate. We propose that in all observational studies intended to produce evidence for causality, the E-value be reported, or some other sensitivity analysis be used. We suggest calculating the E-value for both the observed association estimate (after adjustments for measured confounders) and for the limit of the confidence interval closest to the null. If this were to become standard practice, the ability of the scientific community to assess evidence from observational studies would be improved considerably, and ultimately, science would be strengthened.

Unmeasured confounding may undermine the validity of causal inference with observational studies. Sensitivity analysis provides an attractive way to partially circumvent this issue by assessing the potential influence of unmeasured confounding on causal conclusions. However, previous sensitivity analysis approaches often make strong and untestable assumptions such as having an unmeasured confounder that is binary, or having no interaction between the effects of the exposure and the confounder on the outcome, or having only one unmeasured confounder. Without imposing any assumptions on the unmeasured confounder or confounders, we derive a bounding factor and a sharp inequality such that the sensitivity analysis parameters must satisfy the inequality if an unmeasured confounder is to explain away the observed effect estimate or reduce it to a particular level. Our approach is easy to implement and involves only two sensitivity parameters. Surprisingly, our bounding factor, which makes no simplifying assumptions, is no more conservative than a number of previous sensitivity analysis techniques that do make assumptions. Our new bounding factor implies not only the traditional Cornfield conditions that both the relative risk of the exposure on the confounder and that of the confounder on the outcome must satisfy but also a high threshold that the maximum of these relative risks must satisfy. Furthermore, this new bounding factor can be viewed as a measure of the strength of confounding between the exposure and the outcome induced by a confounder.

Background: Direct access to genomic information has the potential to transform cancer risk counseling. We measured the impact of direct-to-consumer genomic risk information on changes to perceived risk (ΔPR) of breast, prostate, colorectal and lung cancer among personal genomic testing (PGT) customers. We hypothesized that ΔPR would reflect directionality of risk estimates, attenuate with time, and be modified by participant characteristics. Methods: Pathway Genomics and 23andMe customers were surveyed prior to receiving PGT results, and 2 weeks and 6 months post-results. For each cancer, PR was measured on a 5-point ordinal scale from “much lower than average” to “much higher than average.” PGT results, based on genotyping of common genetic variants, were dichotomized as elevated or average risk. The relationship between risk estimate and ΔPR was evaluated with linear regression; generalized estimating equations modeled this relationship over time. Results: With the exception of lung cancer (for which ΔPR was positive regardless of result), elevated risk results were significantly associated with positive ΔPR, and average risk results with negative ΔPR (e.g., prostate cancer, 2 weeks: least squares-adjusted ΔPR = 0.77 for elevated risk versus −0.21 for average risk; p-valuedifference < 0.0001) among 1154 participants. Large changes were rare: for each cancer, <4 % of participants overall reported a ΔPR of ±3 or more units. Effect modification by age, cancer family history, and baseline interest was observed for breast, colorectal, and lung cancer, respectively. A pattern of decreasing impact on ΔPR over time was consistently observed, but this trend was significant only in the case of colorectal cancer. Conclusions: We have quantified the effect on consumer risk perception of returning genetic-based cancer risk information directly to consumers without clinician mediation. Provided via PGT, this information has a measurable but modest effect on perceived cancer risk, and one that is in some cases modified by consumers’ non-genetic risk context. Our observations of modest marginal effect sizes, infrequent extreme changes in perceived risk, and a pattern of diminishing impact with time, suggest that the ability of PGT to effect changes to cancer screening and prevention behaviors may be limited by relatively small changes to perceived risk. Electronic supplementary material The online version of this article (doi:10.1186/s12920-015-0140-y) contains supplementary material, which is available to authorized users.