The Carrot and the Stick? Strategies to Improve Compliance with College Campus Tobacco Policies

Objective: Tobacco-free policies are being rapidly adopted nationwide, yet compliance with these policies remains a challenge. This study explored college campus key informants\u27 experiences with tobacco policies, and their perceived benefits, drawbacks, and outcomes. Participants: The sample for this study was 68 key informants representing 16 different California universities with varying tobacco policies (no smoking indoors and within 20 feet of entrances, designated smoking areas, 100% smoke-free, and 100% tobacco-free). Methods: Qualitative, descriptive study. Semistructured interviews were transcribed verbatim and analyzed using content analysis. Results: Strategies to improve compliance ranged from a social approach to a heavy focus on punitive enforcement. Key informants from campuses using a social approach alone reported barriers to improving compliance, including a perceived lack of efficacy of the approach. However, these campuses found it challenging to incorporate enforcement through campus police or security. Conclusions: College campus decision makers should explore using a combined approach (social approach as well as formal enforcement), with enforcement primarily the responsibility of nonpolice university channels (eg, Student Affairs, employee supervisors)

Use of susceptibility scoring in conjunction with the genotypic transmission disequilibrium test

We explored the utility of selecting a genetically predisposed subgroup to increase the finding of a genetic signal in the Genetic Analysis Workshop 14 Collaborative Study on the Genetics of Alcoholism dataset. A subgroup of affected probands with low environmental risk exposures was defined using a susceptibility score calculated from an environmental risk model. Thirty-nine probands with highly positive scores were selected, along with their parents, for use in a genotypic transmission disequilibrium test (TDT) test. We compared the results of the genotypic TDT in this subgroup to the TDT results using all probands and their parents. For some markers, the susceptibility scoring approach resulted in smaller p-values, while for other markers, evidence for a genetic signal weakened. Further explorations into genetic and environmental population characteristics that benefit from this approach are warranted

TRIO LOGIC REGRESSION - DETECTION OF SNP - SNP INTERACTIONS IN CASE-PARENT TRIOS

Statistical approaches to evaluate higher order SNP-SNP and SNP-environment interactions are critical in genetic association studies, as susceptibility to complex disease is likely to be related to the interaction of multiple SNPs and environmental factors. Logic regression (Kooperberg et al., 2001; Ruczinski et al., 2003) is one such approach, where interactions between SNPs and environmental variables are assessed in a regression framework, and interactions become part of the model search space. In this manuscript we extend the logic regression methodology, originally developed for cohort and case-control studies, for studies of trios with affected probands. Trio logic regression accounts for the linkage disequilibrium (LD) structure in the genotype data, and accommodates missing genotypes via haplotype-based imputation. We also derive an efficient algorithm to simulate case-parent trios where genetic risk is determined via epistatic interactions

ASSOCIATON TESTS THAT ACCOMMODATE GENOTYPING ERRORS

High-throughput SNP arrays provide estimates of genotypes for up to one million loci, often used in genome-wide association studies. While these estimates are typically very accurate, genotyping errors do occur, which can influence in particular the most extreme test statistics and p-values. Estimates for the genotype uncertainties are also available, although typically ignored. In this manuscript, we develop a framework to incorporate these genotype uncertainties in case-control studies for any genetic model. We verify that using the assumption of a “local alternative” in the score test is very reasonable for effect sizes typically seen in SNP association studies, and show that the power of the score test is simply a function of the correlation of the genotype probabilities with the true genotypes. We demonstrate that the power to detect a true association can be substantially increased for difficult to call genotypes, resulting in improved inference in association studies

Comparison of type I error for multiple test corrections in large single-nucleotide polymorphism studies using principal components versus haplotype blocking algorithms

Although permutation testing has been the gold standard for assessing significance levels in studies using multiple markers, it is time-consuming. A Bonferroni correction to the nominal p-value that uses the underlying pair-wise linkage disequilibrium (LD) structure among the markers to determine the number of effectively independent tests has recently been proposed. We propose using the number of independent LD blocks plus the number of independent single-nucleotide polymorphisms for correction. Using the Collaborative Study on the Genetics of Alcoholism LD data for chromosome 21, we simulated 1,000 replicates of parent-child trio data under the null hypothesis with two levels of LD: moderate and high. Assuming haplotype blocks were independent, we calculated the number of independent statistical tests using 3 haplotype blocking algorithms. We then compared the type I error rates using a principal components-based method, the three blocking methods, a traditional Bonferroni correction, and the unadjusted p-values obtained from FBAT. Under high LD conditions, the PC method and one of the blocking methods were slightly conservative, whereas the 2 other blocking methods exceeded the target type I error rate. Under conditions of moderate LD, we show that the blocking algorithm corrections are closest to the desired type I error, although still slightly conservative, with the principal components-based method being almost as conservative as the traditional Bonferroni correction

Associations of First Trimester Co-Use of Tobacco and Cannabis with Prenatal Immune Response and Psychosocial Well-Being

PURPOSE: This study aims to describe the association of first trimester co-use of tobacco and cannabis with maternal immune response and psychosocial well-being, relative to tobacco use only. METHODS: A preliminary midpoint analysis included 138 pregnant women with biologically verified tobacco use, 38 of whom (28%) also tested positive for recent cannabis use. Maternal perceived stress (Perceived Stress Scale), depressive symptoms (Edinburgh Postnatal Depression Scale), and serum immune markers (IL-1β, IL-2, IL-6, IL-8, IL-10, TNFα, CRP, MMP8), were collected, although cytokine data were only available for 122 women. RESULTS: Participant average age was 29.1 years, approximately half had a high school education or less, and half were unemployed. Compared to tobacco only users, co-users were more likely to be non-White, younger and more economically disadvantaged. In the adjusted linear regression models, TNF-α levels were significantly lower among co-users relative to tobacco only users, after adjusting for age, race/ethnicity, body mass index and tobacco use group (tobacco cigarettes, electronic nicotine delivery devices [ENDS] or both). TNF-α was the only immune marker found to be significant in this analysis. Measured stress levels (M = 5.9, SD = 3.3; potential range 0-16) and depression scores (M = 7.8, SD = 5.8; potential range 0-30) were low across all participants and did not differ as a function of co-use. CONCLUSION: Preliminary results suggest women co-using during the first trimester exhibit decreased pro-inflammatory immune responsivity on one out of eight markers. Further research is needed to determine the impact of this immune modulation on fetal health outcomes and the unique contribution of cannabis

Maternal Exposure to Occupational Asthmagens During Pregnancy and Autism Spectrum Disorder in the Study to Explore Early Development

Abstract Maternal immune activity has been linked to children with autism spectrum disorder (ASD). We examined maternal occupational exposure to asthma-causing agents during pregnancy in relation to ASD risk. Our sample included 463 ASD cases and 710 general population controls from the Study to Explore Early Development whose mothers reported at least one job during pregnancy. Asthmagen exposure was estimated from a published job-exposure matrix. The adjusted odds ratio for ASD comparing asthmagen-exposed to unexposed was 1.39 (95 % CI 0.96–2.02). Maternal workplace asthmagen exposure was not associated with ASD risk in this study, but this result does not exclude some involvement of maternal exposure to asthma-causing agents in ASD