There is growing evidence that electronic cigarettes (e-cigarettes) might be associated with youth initiation of combustible cigarette smoking, and yet for adults, e-cigarettes hold potential as a cessation aid for combustible cigarette smoking. There is also growing concern over the health risks of e-cigarettes for individuals of all ages. This dissertation examines the prospective association between e-cigarette use and youth cigarette smoking initiation, adult cigarette smoking abstinence, and cardiopulmonary disease using four waves of the Population Assessment of Tobacco and Health study (2014-2018). This work enhances prior literature by incorporating novel analytic methods to account for previously unaddressed challenges in e-cigarette research, including time-dependent confounders that simultaneously act as causal intermediates, misclassification of self-reported e-cigarette use, and measurement of cumulative e-cigarette exposure. Study 1 examines the association between time-varying e-cigarette initiation and cigarette smoking initiation in a cohort of cigarette and e-cigarette naïve youth at baseline, and employs marginal structural models (MSMs) to account for time-dependent confounding. MSMs allowed for the modeling of e-cigarette use as a time-varying exposure while appropriately adjusting for time-dependent confounders that otherwise produce overestimates of the association between vaping and cigarette smoking. Youth who initiated e-cigarettes over follow-up were three-times more likely than youth who did not initiate e-cigarettes to subsequently initiate combustible cigarette smoking. The association with smoking initiation appeared stronger for more frequent e-cigarette use. Study 2 uses MSMs to examine the independent and joint association between e-cigarette use frequency at two time-points and combustible cigarette smoking abstinence. MSMs allowed for estimation of the simultaneous effect of e-cigarette use at multiple time points, as well as the direct effect of short-term e-cigarette use on smoking abstinence 24-months later. Consistent daily e-cigarette use was associated with four-times the likelihood of sustained 12-month cigarette smoking abstinence compared to no e-cigarette use over follow-up. Participants who reported consistent non-daily e-cigarette use were 70% less likely to achieve cigarette smoking abstinence than non-users. Study 3 develops a novel measure of cumulative e-cigarette exposure (“vape-years”) using a volume-based approach to measuring e-cigarette dose. The study assesses the association between vape-years and incident cardiovascular disease, lung disease, and disease precursors (hypertension, wheezing/whistling in the chest, dry cough). The highest levels of cumulative e-cigarette exposure were associated with increased risk of incident cardiovascular disease and lung disease among participants with lower combustible smoking pack-years of exposure, though residual confounding by combustible smoking is likely. There was little association between cumulative e-cigarette exposure and disease precursors. This dissertation demonstrates analytic techniques that can be used to address methodological challenges when evaluating longitudinal e-cigarette exposures. Findings provide evidence that e-cigarette use predisposes youth to initiate combustible cigarettes, and e-cigarettes can both help and hinder combustible smoking cessation depending on frequency of use. The association between cumulative e-cigarette exposure and cardiopulmonary disease risk remains unclear. Findings can inform e-cigarette regulations aimed at preventing youth vaping, reducing harm for adult tobacco users, and communicating health effects of vaping. / 2022-08-04T00:00:00Z

The gold standard for evaluating questions of drug safety or efficacy is a well-designed randomized trial. However, randomized trials are often infeasible due to ethical or logistical reasons. When a randomized trial is not possible, we rely on observational studies. We can conceptualize the design and analysis of an observational study as an attempt to emulate a randomized trial. Becoming more intentional about this framework (i.e., “trial emulation”) allows investigators to identify and minimize common biases. This dissertation explores the feasibility of applying a trial emulation framework to three questions evaluating the safety of medications used before or during pregnancy. First, we evaluated the comparative effects of preconception use of various contraceptives on miscarriage. Second, we evaluated the effect of preconception vaccination against coronavirus disease 2019, compared with no preconception vaccination, on rate of miscarriage. Third, we evaluated the comparative safety of metformin plus insulin versus insulin alone during pregnancy for pregestational type 2 diabetes, in relation to perinatal outcomes. The findings of these studies advance our knowledge of medication safety in addition to our understanding of how to mitigate bias in pharmacoepidemiologic studies of pregnancy. / 2024-05-11T00:00:00Z

Observational studies of the effects of medication use during pregnancy are threatened by mechanisms of systematic bias which may impact the interpretation of effect estimates. Importantly, these biases may independently or jointly threaten validity, resulting in observed associations that may be incorrect in both direction and magnitude. Methods of quantitatively assessing and addressing these biases are available, and under the correct assumptions, can provide a more accurate understanding and interpretation of effect measures. The goals of this dissertation were to examine previous studies on associations of commonly used medications during pregnancy, adverse pregnancy and fetal outcomes and apply analytic methods to address validity concerns. We used data from the National Birth Defects Prevention Study (NBDPS) for all three studies, which was the largest, population-based case-control study of congenital anomalies from 1997–2011. In the first study, we evaluated whether the previously reported increased risk of orofacial clefts associated with ondansetron in NBDPS may be explained by selection bias arising from differential participation. We used study records available on participants and non-participants to calculate inverse probability of participation weights (IPWs) to adjust for differential participation. The unadjusted odds ratio (OR) for ondansetron use and cleft palate was 1.5 (95% CI 1.0–2.0). After adjusting for age, education, study year and location, and periconceptional folic acid use, the estimate was 1.6 (95% 1.1–2.1) and the participation-weighted OR was 1.4 (95% CI 1.0–2.0). When we adjusted for confounding using the same covariates as the confounding-only model and selection bias, the OR was 1.6 (95% CI 1.3–2.2). Our estimates suggested limited evidence of selection bias from differential participation in the association between ondansetron use in the first trimester and cleft palate reported in NBDPS. In the second study, we assessed and quantified the presence of immortal time bias in a study on the use of decongestants in late pregnancy and preterm delivery, comparing time-fixed to time-varying analyses. We observed that results from a time-fixed approach (aHR = 0.99, 95% CI 0.75, 1.31) for our time-dependent outcome resulted in downward bias compared to results from the time-varying approach (aHR = 1.09, 95% CI 0.82, 1.44). However, we did not observe the same reductions in risk of preterm delivery associated with use of decongestants in the when using a time-fixed approach as previously reported in the literature. Overall, we found that both time-fixed and time-varying approaches suggested that use of decongestants in second and/or third trimester of pregnancy did not confer a protective effect for preterm delivery. In the third study, we conducted probabilistic and multidimensional bias analyses to address differential and nondifferential exposure misclassification for the association between periconceptional use of non-aspirin non-steroidal anti-inflammatory drugs (NSAIDs) and amniotic band syndrome. Under the assumption of differential misclassification, assuming better classification in the cases, the bias-adjusted estimates were compatible with either bias away or towards the null. When we assumed greater specificity in the cases, the bias-adjusted estimates suggested bias away from the null in the unadjusted estimates. If we assumed greater sensitivity in the cases, the adjusted estimates suggested bias away when specificity was high (> 0.9) or towards the null as specificity decreased. Results suggested substantial bias towards the null when we assumed nondifferential exposure misclassification, particularly if sensitivity and specificity were low (0.3 and 0.8 respectively). All three studies highlight the importance of examining and quantifying the effect of proposed mechanisms of systematic bias on associations in observational studies otherwise we may be led astray by intuitions. These analyses also underline the critical importance of explicitly stating assumptions since all results are conditional on assumptions being correct. These methods (and others) can be used to quantitively assess important, potential sources of systematic error to ultimately improve the rigor of observational studies and our ability to draw conclusions.

Infertility, defined as the inability to achieve clinical pregnancy after ≥12 months of regular unprotected intercourse, is a growing problem in North America and the world. Estimates place the percentage of couples experiencing infertility at around 15% in North America. Currently, the U.S. health care costs for infertility treatment exceed $5.5 billion, with these costs expected to increase as more couples use assisted reproductive technologies (ART). Additionally, fertility issues are associated with psychological and financial hardship for affected couples, and ART use has been associated with adverse pregnancy outcomes. One vital area of research that has been drastically understudied is male fertility. Male factors are found to contribute to 30-50% of all infertility diagnoses, but the vast majority of studies focus on women. This dissertation uses data from Pregnancy Study Online (PRESTO), a preconception cohort study of pregnancy planners from North America, to examine the role several male exposures have on fertility. In the first study, we examined the association between a history of diagnosed depression, current depressive symptoms, and psychotropic medication (PM) use with fecundability. We found that a history of diagnosed depression, as well as currentvi depressive symptoms, showed slight evidence of an association with decreased fecundability, though this result was compatible with chance. Current psychotropic medication (PM) and antidepressant use were associated with reduced fecundity, particularly among those with current depressive symptoms. Current PM and selective serotonin reuptake inhibitor (SSRI) use mediated part but not all of the relationship between current depressive symptoms and fecundability. In the second paper, we studied the role of testicular heat exposure in declining fertility. We estimated the extent to which selected male heat exposures, including use of saunas, hot tubs, and hot baths; use of restrictive underwear; time spent sitting; use of car seat heaters; use of a laptop computer on one’s lap; and fever within the last 3 months affected fecundability. Additionally, we attempted to create a composite heat score to measure cumulative heat exposure. We found small inverse associations for sauna use, hot tub/bath use, and seat heater use in the winter with fecundability. Additionally, we found evidence of threshold for overall exposure to multiple heat factors. The third paper focused specifically on occupational stress exposure, an understudied source of exposure to stress. These occupational stressors included employment status (employed or unemployed), number of hours worked, time of day mainly worked, and a measure of job independence. We found that working non-daytime shifts and being unemployed were associated with slightly decreased fecundability in men. However, total hours worked per week and job independence score showed little relation to reduced fecundability

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Background: Rainfall is a major driver of waterborne disease. One mechanism by which rainfall can introduce pathogens into environmental waterways is by causing combined sewer overflows (CSOs). Exposure to contaminated surface water may occur during recreational activities that result in accidental ingestion of enteric waterborne pathogens. These pathogens can cause acute gastrointestinal illness (AGI), which is particularly harmful for certain vulnerable groups. Due to projected increases in precipitation in certain areas of the United States, it is important to better understand these relationships and identify populations that may be impacted. Objectives: This dissertation aims to explore the relationships between rainfall, CSOs, and waterborne disease in Philadelphia and in Pennsylvania and to determine how environmental, social, and climatic factors impact these relationships. To do so, this dissertation will 1) identify demographic and economic characteristics of populations that are more likely to be affected by CSO-impacted waters in Philadelphia, 2) quantify the risk of AGI due to recreational exposure to CSO-impacted and non-impacted waters in Philadelphia, and 3) assess the relationships between precipitation and potentially waterborne reportable diseases in Pennsylvania. Methods: To accomplish the first aim, survey data were collected from adults recreating at or near CSO-impacted sites in Philadelphia. Surveys measured participant demographics, recreation behavior, and travel behaviors. Travel measures reported in surveys were used to develop network buffers around both CSO-impacted and non-impacted sites where recreational exposures may occur in Philadelphia. Modified Poisson regression models compared populations living within the reported travel distances to CSO-impacted sites to those living within the same distances to non-impacted sites. To accomplish aim 2, the concentrations of five pathogens were determined by quantifying the concentration of the HF183 marker for human Bacteroides in water samples collected at three sites in Philadelphia during CSO-impacted and non-impacted conditions. Observational data that measured recreational exposures to these waterbodies were collected along with water samples. These data were used to develop quantitative microbial risk assessment (QMRA) models that measured the risk of illness due to these five pathogens during CSO-impacted and non-impacted conditions. Finally, for aim 3, mixed-effects negative binomial regression models were used to measure associations between precipitation, temperature, and the monthly incidence of campylobacteriosis, salmonellosis, cryptosporidiosis, and giardiasis reported per patient zip code in Pennsylvania from January 2014-December 2018. Additional models assessed the impact of seasonality, explored lagged relationships, and determined whether these relationships differed in areas that did or did not contain a combined sewer outfall. Results: Survey data collected for aim 1 found that participants walk an average of 1.4km to get to recreation sites. Populations that reside near CSO-impacted waterways were more likely to be minority and low-income than those that reside near non-impacted water bodies in Philadelphia, presenting a potential environmental justice issue. Results of QMRA models found that several recreational exposure scenarios resulted in a mean risk of illness above the United States Environmental Protection Agency’s acceptable threshold of 30 illnesses per 1,000 exposed. For several exposure scenarios, the risk was still above this threshold during non-impacted conditions. Finally, a 1cm increase in rainfall per month was associated with a 1% increase in the incidence of campylobacteriosis and salmonellosis (IRR: 1.01, 95% CI: 1.00-1.01, for both) and every additional day with at least 2.54mm of rainfall was associated with 1% increase in the incidence of salmonellosis (IRR: 1.01, 95% CI: 1.00, 1.03) and a 3% increase in cryptosporidiosis (IRR: 1.02, 95% CI: 1.01, 1.05). Associations were also found between the daily maximum temperature per month and the incidence of campylobacteriosis, salmonellosis, and cryptosporidiosis. These relationships were strongest during summer months. No differences were observed when comparing results among areas that did or did not contain a combined sewer outfall. Conclusions: Findings from this dissertation suggest that recreation in CSO-impacted waters in Philadelphia presents a health risk. In addition, minority and low-income communities may be more impacted by this potential health risk as they are more likely to reside near potential recreation sites that are impacted by CSOs in Philadelphia. Finally, relationships between precipitation and waterborne disease incidence in Pennsylvania demonstrate how projected increases in precipitation events due to global climate change may increase waterborne disease incidence in Pennsylvania, although the drivers of this relationship are unclear and likely diverse. / Epidemiology