Study of effect modifiers of genetically predicted CETP reduction.

Genetic variants in drug targets can be used to predict the long-term, on-target effect of drugs. Here, we extend this principle to assess how sex and body mass index may modify the effect of genetically predicted lower CETP levels on biomarkers and cardiovascular outcomes. We found sex and body mass index (BMI) to be modifiers of the association between genetically predicted lower CETP and lipid biomarkers in UK Biobank participants. Female sex and lower BMI were associated with higher high-density lipoprotein cholesterol and lower low-density lipoprotein cholesterol for the same genetically predicted reduction in CETP concentration. We found that sex also modulated the effect of genetically lower CETP on cholesterol efflux capacity in samples from the Montreal Heart Institute Biobank. However, these modifying effects did not extend to sex differences in cardiovascular outcomes in our data. Our results provide insight into the clinical effects of CETP inhibitors in the presence of effect modification based on genetic data. The approach can support precision medicine applications and help assess the external validity of clinical trials.

Role of Physical Activity and Sedentary Behaviors on Vascular and Myocardial Structure and Function in Type 1 Diabetes.

OBJECTIVE: To estimate associations between physical activity and sedentary behaviors and early markers of cardiovascular diseases in adolescents with and without type 1 diabetes. STUDY DESIGN: Cross-sectional data stem from the CARdiovascular Disease risk in pEdiatric type 1 diAbetes (CARDEA) study, a study investigating early cardiovascular disease development in 100 adolescents with type 1 diabetes recruited at Sainte-Justine University Hospital Diabetes Clinic and 97 healthy adolescents without diabetes (14-18 years), in Montreal, Canada. Outcomes included arterial stiffness by pulse-wave velocity, endothelial function (velocity time integral) by flow-mediated dilation test, and cardiac magnetic resonance imaging markers. Moderate-to-vigorous physical activity (MVPA) and sedentary time were estimated by accelerometry and leisure screen time by questionnaire. We estimated multivariable linear regression models stratified by group. RESULTS: In adolescents with type 1 diabetes, 10-minutes daily increase in MVPA was associated with 3.69 g/m (95% CI: -1.16; 8.54) higher left ventricular (LV) mass/height and 1-hour increase in device-measured sedentary time with 0.68 mm (0.20; 1.16) higher wall thickness but only in those with glycated hemoglobin ≤7.5%. In healthy adolescents, a 10-minute increase in MVPA was associated with 1.32 g/m (-0.03; 2.66) higher LV mass/height. Every 1-hour increase in sedentary time was associated with -1.82 cm (-3.25; -0.39) lower velocity time integral, -2.99 g/m (-5.03; -0.95) lower LV mass/height, and -0.47 mm (-0.82; -0.12) lower wall thickness. CONCLUSIONS: Being active and limiting sedentary time appears beneficial for cardiac structure and endothelial function in healthy adolescents; however, adequate glycemic control combined with higher levels of MVPA may be required for adolescents with type 1 diabetes to overcome the impact of diabetes.

Trajectories of opioid consumption as predictors of patient-reported outcomes among individuals attending multidisciplinary pain treatment clinics.

PURPOSE: This study aimed to identify opioid consumption trajectories among persons living with chronic pain (CP) and put them in relation to patient-reported outcomes 6 months after initiating multidisciplinary pain treatment. METHODS: This study used data from the Quebec Pain Registry (2008-2014) linked to longitudinal Quebec health insurance databases. We included adults diagnosed with CP and covered by the Quebec public prescription drug insurance plan. The daily cumulative opioid doses in the first 6 months after initiating multidisciplinary pain treatment were transformed into morphine milligram equivalents. An individual-centered approach involving principal factor and cluster analyses applied to longitudinal statistical indicators of opioid use was conducted to classify trajectories. Multivariate regression models were applied to evaluate the associations between trajectory group membership and outcomes at 6-month follow-up (pain intensity, pain interference, depression, and physical and mental health-related quality of life). RESULTS: We identified three trajectories of opioid consumption: "no or very low and stable" opioid consumption (n = 2067, 96.3%), "increasing" opioid consumption (n = 40, 1.9%), and "decreasing" opioid consumption (n = 39, 1.8%). Patients in the "no or very low and stable" trajectory were less likely to be current smokers, experience polypharmacy, use opioids or benzodiazepine preceding their first visit, or experience pain interference at treatment initiation. Patients in the "increasing" opioid consumption group had significantly greater depression scores at 6-month compared to patients in the "no or very low and stable" trajectory group. CONCLUSION: Opioid consumption trajectories do not seem to be important determinants of most PROs 6 months after initiating multidisciplinary pain treatment.

A qualitative study of experiences among young adults who increased their cannabis use during the COVID-19 pandemic.

BACKGROUND: Young adults face unique vulnerabilities during major life disruptions like the COVID-19 pandemic. The pandemic contributed to increases in mental health challenges and substance use among young adults. This study explores the experiences of young adults who increased their cannabis use during the pandemic. METHODS: Participants were recruited from the Nicotine Dependence in Teens (NDIT) study, and qualitative data were collected through semi-structured interviews conducted via Zoom. A total of 25 participants (ages 33-34) reporting increased cannabis use during the pandemic were included. Thematic analysis and gender-based analysis was employed to extract key themes. RESULTS: Five themes emerged: (1) No disruption in cannabis use; (2) Cannabis use to manage declines in mental health; (3) Cannabis use to break up pandemic boredom; (4) Cannabis use as an expression of freedom; (5) Cannabis use as "another way to chill out." CONCLUSIONS: This research provides valuable perspectives on how major life disruptions, like the COVID-19 pandemic, influence cannabis use among young adults. The findings offer guidance for public health initiatives and highlight avenues for further investigation.

Comparison of three frailty measures for predicting hospitalization and mortality in the Canadian Longitudinal Study on Aging.

BACKGROUND: Few studies have compared different measures of frailty for predicting adverse outcomes. It remains unknown which frailty measurement approach best predicts healthcare utilization such as hospitalization and mortality. AIMS: This study aims to compare three approaches to measuring frailty-grip strength, frailty phenotype, and frailty index-in predicting hospitalization and mortality among middle-aged and older Canadians. METHODS: We analyzed baseline and the first 3-year follow-up data for 30,097 participants aged 45 to 85 years from the comprehensive cohort of the Canadian Longitudinal Study on Aging (CLSA). Using separate logistic regression models adjusted for multimorbidity, age and biological sex, we predicted participants' risks for overnight hospitalization in the past 12 months and mortality, at the first 3-year follow-up, using each of the three frailty measurements at baseline. Model discrimination was assessed using Harrell's c-statistic and calibration assessed using calibration plots. RESULTS: The predictive performance of all three measures of frailty were roughly similar when predicting overnight hospitalization and mortality risk among CLSA participants. Model discrimination measured using c-statistics ranged from 0.67 to 0.69 for hospitalization and 0.79 to 0.80 for mortality. All measures of frailty yielded strong model calibration. DISCUSSION AND CONCLUSION: All three measures of frailty had similar predictive performance. Discrimination was modest for predicting hospitalization and superior in predicting mortality. This likely reflects the objective nature of mortality as an outcome and the challenges in reducing the complex concept of healthcare utilization to a single variable such as any overnight hospitalization.

The application of target trials with longitudinal targeted maximum likelihood estimation to assess the effect of alcohol consumption in adolescence on depressive symptoms in adulthood.

Time-varying confounding is a common challenge for causal inference in observational studies with time-varying treatments, long follow-up periods, and participant dropout. Confounder adjustment using traditional approaches can be limited by data sparsity, weight instability and computational issues. The Nicotine Dependence in Teens (NDIT) study is a prospective cohort study involving 24 data collection cycles from 1999 to date, among 1,294 students recruited from 10 high schools in Montreal, Canada, including follow-up into adulthood. Our aim is to estimate associations between the timing of alcohol initiation and the cumulative duration of alcohol use on depression symptoms in adulthood. Based on the target trials framework, we define intention-to-treat and as-treated parameters in a marginal structural model with sex as a potential effect-modifier. We then use the observational data to emulate the trials. For estimation, we use pooled longitudinal target maximum likelihood estimation (LTMLE), a plug-in estimator with double robust and local efficiency properties. We describe strategies for dealing with high-dimensional potential drinking patterns and practical positivity violations due to a long follow-up time, including modifying the effect of interest by removing sparsely observed drinking patterns from the loss function and applying longitudinal modified treatment policies to represent the effect of discouraging drinking.

The Pathways study: a cohort study of new food-aid users in rural, semi urban, and urban areas of Quebec, Canada.

BACKGROUND: While considerable research has been conducted on household food insecurity (HFI), little research has examined the effects of food donation programs on users' living conditions. The Pathways study was established to investigate the long-term effects of food donation programs on food insecurity as well as other critical outcomes, such as diet, health, and social support. Herein, we describe the design of the Pathways Study and the participants' characteristics at baseline. METHODS: The Pathways study is a prospective cohort study of 1001 food-aid users in Quebec (Canada). We recruited newly registered users of food donation programs from 106 community-based food-aid organizations that partnered with the study. Baseline data were collected through face-to-face interviews from September 2018 to January 2020, with planned follow-up interviews at 12 and 24 months after enrollment. Household food insecurity, diet, food competencies, food shopping behaviors, perceived food environment, health status, social support and isolation, sociodemographic characteristics, housing conditions, negative life events, and the impacts of COVID-19 were assessed with validated questionnaires. RESULTS: The cohort included 1001 participants living in rural (n = 181), semi-urban (n = 250), and urban areas (n = 570). Overall, household food insecurity was reported as severe among 46.2% and moderate in 36.9% of participants. Severe household food insecurity was more prevalent in rural (51.4%) and urban (47.8%) areas compared to semi-urban (39%) areas. Overall, 76.1% of participants reported an annual income below C$20,000. Half (52%) had low education levels (high school or lower), 22.0% lived in single-parent households, and 52.1% lived alone. Most (62.9%) experienced at least one major financial crisis in the preceding year. CONCLUSIONS: Results show that newly registered users of food donation programs often have low-income and severe food insecurity, with major differences across geographical locations. The Pathways study is the first study designed to follow, over a 2-year period, a cohort of newly registered users of food donation programs and to quantify their trajectories of service use. Findings from the Pathways study might help adapt the community response to the strategies used by food-insecure households to feed themselves.

Does group-based trajectory modeling estimate spurious trajectories?

BACKGROUND: Group-based trajectory modelling (GBTM) is increasingly used to identify subgroups of individuals with similar patterns. In this paper, we use simulated and real-life data to illustrate that GBTM is susceptible to generating spurious findings in some circumstances. METHODS: Six plausible scenarios, two of which mimicked published analyses, were simulated. Models with 1 to 10 trajectory subgroups were estimated and the model that minimized the Bayes criterion was selected. For each scenario, we assessed whether the method identified the correct number of trajectories, the correct shapes of the trajectories, and the mean number of participants of each trajectory subgroup. The performance of the average posterior probabilities, relative entropy and mismatch criteria to assess classification adequacy were compared. RESULTS: Among the six scenarios, the correct number of trajectories was identified in two, the correct shapes in four and the mean number of participants of each trajectory subgroup in only one. Relative entropy and mismatch outperformed the average posterior probability in detecting spurious trajectories. CONCLUSION: Researchers should be aware that GBTM can generate spurious findings, especially when the average posterior probability is used as the sole criterion to evaluate model fit. Several model adequacy criteria should be used to assess classification adequacy.

Natural history and determinants of dysglycemia in Canadian children with parental obesity from ages 8-10 to 15-17 years: The QUALITY cohort.

In children, the mechanisms implicated in deterioration of glucose homeostasis versus reversion to normal glucose tolerance (NGT) remain uncertain. We aimed to describe the natural history of dysglycemia from childhood to late adolescence and to identify its early determinants. We used baseline (8-10 years, n = 630), 1st follow-up (10-12 years, n = 564) and 2nd follow-up (15-17 years, n = 377) data from the QUALITY cohort of White Canadian children with parental obesity. Children underwent a 2-h oral glucose tolerance test at each cycle with plasma glucose and insulin measured at 0/30/60/90/120 min. American Diabetes Association criteria defined dysglycemia (impaired fasting glucose, impaired glucose tolerance or type 2 diabetes). Longitudinal patterns of insulin sensitivity and beta-cell function were estimated using generalized additive mixed models. Model averaging identified biological, sociodemographic and lifestyle-related determinants of dysglycemia. Of the children NGT at baseline, 66 (21%) developed dysglycemia without reverting to NGT. Among children with dysglycemia at baseline, 24 (73%) reverted to NGT. In children with dysglycemia at 1st follow-up, 18 (53%) later reverted to NGT. Among biological, sociodemographic and lifestyle determinants at 8-10 years, only fasting and 2-h glucose were associated with developing dysglycemia (odds ratio [95% CI] per 1 mmol/L increase: 4.50 [1.06; 19.02] and 1.74 [1.11; 2.73], respectively). Beta-cell function decreased by 40% in children with overweight or obesity. In conclusion, up to 75% of children with dysglycemia reverted to NGT during puberty. Children with higher fasting and 2-h glucose were at higher risk for progression to dysglycemia, while no demographic/lifestyle determinants were identified.

Cigarette Smoking Trajectories in Adolescent Smokers: Does the Time Axis Metric Matter?

INTRODUCTION: Most studies modeling adolescent cigarette smoking trajectories use age as the time axis, possibly obscuring depiction of the natural course of cigarette smoking. We used a simulated example and real data to contrast smoking trajectories obtained from models that used time since smoking onset or calendar time (age) as the time axis. METHODS: Data were drawn from a longitudinal investigation of 1293 grade 7 students (mean age 12.8 years) recruited from 10 high schools in Montreal, Canada in 1999-2000, who were followed into young adulthood. Cigarette consumption was measured every 3 months during high school, and again at mean ages 20.4 and 24.0. Analyses using time since onset of smoking as the time metric was restricted to 307 incident smokers; analysis using calendar time included 645 prevalent and incident smokers. Smoking status and nicotine dependence (ND) were assessed at mean ages 20.4 and 24.0. Simulated data mimicked the real study during high school. RESULTS: Use of different time metrics resulted in different numbers and shapes of trajectories in the simulated and real datasets. Participants in the calendar time analyses reported more ND in young adulthood, reflecting inclusion of 388 prevalent smokers who had smoked for longer durations. CONCLUSIONS: Choosing the right time metric for trajectory analysis should be balanced against research intent. Trajectory analyses using the time since onset metric depict the natural course of smoking in incident smokers. Those using calendar time offer a snapshot of smoking across ages during a given time period. IMPLICATIONS: This study uses simulated and real data to show that trajectory analyses of cigarette smoking that use calendar time (e.g., age) versus time since onset as the time axis metric tell a different story. Trajectory analyses using the time since onset metric depict the natural course of smoking in incident smokers. Those using calendar time offer a snapshot of smoking across ages during a given time period. Choosing the right time metric should be balanced against research intent.