Many epidemiological studies assess the effects of time-dependent exposures, where both the exposure status and its intensity vary over time. The analysis of such studies poses the challenge of modelling the association between complex time-dependent drug exposure and the risk, especially given the uncertainty about the etiological relevance of doses taken in different time periods. / To address this challenge, I developed a flexible method for modelling cumulative effects of time-varying exposures, weighted by recency, represented by time-dependent covariates in the Cox proportional hazards model. The function that assigns weights to doses taken in the past is estimated using cubic regression splines. Models with different number of knots and constraints are estimated. Bootstrap techniques are used to obtain pointwise confidence bands around the weight functions, accounting for both the sampling variation of the regression coefficients, and the uncertainty at the model selection stage, i.e. the additional variance due to a posteriori selection of the number of knots. / To assess the method in simulations, I had to develop and validate a novel algorithm to generate event times conditional on time-dependent covariates and compared it with the algorithms available in the literature. The proposed algorithm extends a previously proposed permutational algorithm to include a rejection sampler. While all the algorithms generated data sets that, once analyzed, provided virtually unbiased estimates with comparable variances, the algorithm that I proposed reduced the computational time by more than 50 per cent relative to alternative methods. I used simulations to systematically investigate the properties of the weighted cumulative dose method. Six different weight functions were considered. Simulations showed that in most situations, the proposed method was able to capture the shape of the true weight functions and to produce estimates of the magnitude of the exposure effect on the risk that were close to those used to generate the data. I finally illustrated the use of the weighted cumulative dose modelling by reassessing the association between the use of selected benzodiazepines and fall-related injuries, using administrative data on a cohort of elderly who initiated their use of benzodiazepines between 1990 and 2004.

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BACKGROUND AND OBJECTIVES: Sexual minority individuals demonstrate disparate rates of substance use. Research suggests that bisexual women are vulnerable to substance use disorders when compared to other sexual minority groups. This study explored differences in prevalence of past-year alcohol use disorder (AUD) with and without concurrent past-year opioid and/or benzodiazepine misuse. METHODS: The present study utilized responses from the National Survey on Drug Use and Health (NSDUH) public dataset between the years 2015-2019 (N = 16,002) to examine the association between sexual orientation and concurrent misuse of opioids and/or benzodiazepines among individuals with past-year AUD, stratified by sex. RESULTS: Bisexual females demonstrated higher rates of concurrent opioid and benzodiazepine use compared to all other groups. Although there was no association between sexual orientation and concurrent substance use patterns among males, female respondents with past-year AUD endorsing past-year misuse of opioids and benzodiazepines, both alone and in combination, were more likely to be bisexual compared to heterosexual. Lesbians were less likely to endorse concurrent misuse of opioids and benzodiazepines compared to bisexual females. DISCUSSION AND CONCLUSIONS: In a national sample, bisexual females demonstrated higher odds of risky concurrent substance use patterns. Identifying sexual minority individuals who exhibit elevated risk of co-occurring alcohol, opioid, and/or benzodiazepine misuse is an important step to targeted prevention efforts and allocation of resources to combat rising overdose deaths. SCIENTIFIC SIGNIFICANCE: For the first time, this study explored risky concurrent alcohol, opioid, and benzodiazepine misuse patterns among individuals of different sexual orientations.