Impact of Educational Activity Formats, Online or In-Person, on the Intention of Medical Specialists to Adopt a Clinical Behaviour: A Comparative Study.

COVID-19 accelerated continuing professional development (CPD) delivered online. We aimed to compare the impact of in-person versus online CPD courses on medical specialists' behavioural intentions and subsequent behaviour. In this comparative before-and-after study, medical specialists attended in-person courses on nine clinical topics. A second group attended an adapted online version of these courses. Behavioural intention and its psychosocial determinants were measured before and immediately after the courses. Behaviour change was measured six months later. Generalised estimating equation (GEE) models were used to compare the impact of course formats. A total of 82/206 in-person registrants (mean age: 52±10 years; 50% men) and 318/506 on-line registrants (mean age: 49±12 years; men: 63%) participated. Mean intention before in-person courses was 5.99±1.31 and 6.43±0.80 afterwards (average intention gain 0.44, CI: 0.16-0.74; p=0.003); mean intention before online courses was 5.53±1.62 and 5.98±1.40 afterwards (average intention gain of 0.45, CI: 0.30-0.58; p<0.0001). Difference in intention gain between groups was not statistically significant. Behaviour reported six months later was not significantly associated with post-course intention in either group. However, the intention difference increased significantly among those who said they had adopted the targeted behaviour (paired wilcoxon test: n = 40 and p-value=0.002) while it did not increase significantly in the group of those who had not adopted a targeted behaviour (paired wilcoxon test: n = 16 and p-value=0.223). In conclusion, the increase in intention of specialists after CPD courses was similar whether the course was in-person or online. Also, an increase in intention in both groups signalled more likelihood of adoption.

10-Year Multimorbidity Trajectories in Older People Have Limited Benefit in Predicting Short-Term Health Outcomes in Comparison to Standard Multimorbidity Thresholds: A Population-Based Study.

Purpose: To identify multimorbidity trajectories among older adults and to compare their health outcome predictive performance with that of cross-sectional multimorbidity thresholds (eg, ≥2 chronic conditions (CCs)). Patients and Methods: We performed a population-based longitudinal study with a random sample of 99,411 individuals aged >65 years on April 1, 2019. Using health administrative data, we calculated for each individual the yearly CCs number from 2010 to 2019 and constructed the trajectories with latent class growth analysis. We used logistic regression to determine the increase in predictive capacity (c-statistic) of multimorbidity trajectories and traditional cross-sectional indicators (≥2, ≥3, or ≥4 CCs, assessed in April 2019) over that of a baseline model (including age, sex, and deprivation). We predicted 1-year mortality, hospitalization, polypharmacy, and frequent general practitioner, specialist, or emergency department visits. Results: We identified eight multimorbidity trajectories, each representing between 3% and 25% of the population. These trajectories exhibited trends of increasing, stable, or decreasing number of CCs. When predicting mortality, the 95% CI for the increase in the c-statistic for multimorbidity trajectories [0.032-0.044] overlapped with that of the ≥3 indicator [0.037-0.050]. Similar results were observed when predicting other health outcomes and with other cross-sectional indicators. Conclusion: Multimorbidity trajectories displayed comparable health outcome predictive capacity to those of traditional cross-sectional multimorbidity indicators. Given its ease of calculation, continued use of traditional multimorbidity thresholds remains relevant for population-based multimorbidity surveillance and clinical practice.

Strategies aiming to improve statin therapy adherence in older adults: a systematic review.

BACKGROUND: Randomized clinical trials have shown that, under optimal conditions, statins reduce the risk of cardiovascular events in older adults. Given the prevalence and consequences of suboptimal adherence to statin among older adults, it is essential to document strategies designed to increase statin adherence in this population. The objective of this systematic review is to describe and summarize the effectiveness of interventions to improve statin adherence in older adults (≥ 65 years old). METHODS: This review followed PRISMA guidelines. Studies were identified from PubMed, PsycINFO, Embase, CINAHL and Web of Science. Study selection was conducted independently by four reviewers working in pairs. Included studies reported data on interventions designed to increase adherence to statin therapy in older adults and were original trials or observational studies. Interventions were pragmatically regrouped into 8 different categories going from patient to administrative level. Two reviewers extracted study data and assessed study quality independently. Given the heterogeneity between the included studies, a narrative critique and summary was conducted. RESULTS: Twelve out of the 2889 identified articles were included in the review. Our review showed that simplifying patients' drug regimen, administrative improvements and large-scale pharmacy-led automated telephone interventions show positive effects on patient adherence to statin therapy, with odds ratios between > 1.0 and 3.0, while education-based strategies and intensified patient care showed mixed results. CONCLUSIONS: Current evidence suggests that some interventions can increase statin adherence in older adults, which could help in the reduction of the risk of a cardiovascular event in this population.

Multimorbidity prevalence and health outcome prediction: assessing the impact of lookback periods, disease count, and definition criteria in health administrative data at the population-based level.

BACKGROUND: Health administrative databases play a crucial role in population-level multimorbidity surveillance. Determining the appropriate retrospective or lookback period (LP) for observing prevalent and newly diagnosed diseases in administrative data presents challenge in estimating multimorbidity prevalence and predicting health outcome. The aim of this population-based study was to assess the impact of LP on multimorbidity prevalence and health outcomes prediction across three multimorbidity definitions, three lists of diseases used for multimorbidity assessment, and six health outcomes. METHODS: We conducted a population-based study including all individuals ages > 65 years on April 1st, 2019, in Québec, Canada. We considered three lists of diseases labeled according to the number of chronic conditions it considered: (1) L60 included 60 chronic conditions from the International Classification of Diseases (ICD); (2) L20 included a core of 20 chronic conditions; and (3) L31 included 31 chronic conditions from the Charlson and Elixhauser indices. For each list, we: (1) measured multimorbidity prevalence for three multimorbidity definitions (at least two [MM2+], three [MM3+] or four (MM4+) chronic conditions); and (2) evaluated capacity (c-statistic) to predict 1-year outcomes (mortality, hospitalisation, polypharmacy, and general practitioner, specialist, or emergency department visits) using LPs ranging from 1 to 20 years. RESULTS: Increase in multimorbidity prevalence decelerated after 5-10 years (e.g., MM2+, L31: LP = 1y: 14%, LP = 10y: 58%, LP = 20y: 69%). Within the 5-10 years LP range, predictive performance was better for L20 than L60 (e.g., LP = 7y, mortality, MM3+: L20 [0.798;95%CI:0.797-0.800] vs. L60 [0.779; 95%CI:0.777-0.781]) and typically better for MM3 + and MM4 + definitions (e.g., LP = 7y, mortality, L60: MM4+ [0.788;95%CI:0.786-0.790] vs. MM2+ [0.768;95%CI:0.766-0.770]). CONCLUSIONS: In our databases, ten years of data was required for stable estimation of multimorbidity prevalence. Within that range, the L20 and multimorbidity definitions MM3 + or MM4 + reached maximal predictive performance.

Value-based comparison of ambulatory children with respiratory diseases in an emergency department and a walk-in clinic: a retrospective cohort study in Québec, Canada.

OBJECTIVE: To compare health outcomes and costs given in the emergency department (ED) and walk-in clinics for ambulatory children presenting with acute respiratory diseases. DESIGN: A retrospective cohort study. SETTING: This study was conducted from April 2016 to March 2017 in one ED and one walk-in clinic. The ED is a paediatric tertiary care centre, and the clinic has access to lab tests and X-rays. PARTICIPANTS: Inclusion criteria were children: (1) aged from 2 to 17 years old and (2) discharged home with a diagnosis of upper respiratory tract infection (URTI), pneumonia or acute asthma. MAIN OUTCOME MEASURES: The primary outcome measure was the proportion of patients returning to any ED or clinic within 3 and 7 days of the index visit. The secondary outcome measures were the mean cost of care estimated using time-driven activity-based costing and the incidence of antibiotic prescription for URTI patients. RESULTS: We included 532 children seen in the ED and 201 seen in the walk-in clinic. The incidence of return visits at 3 and 7 days was 20.7% and 27.3% in the ED vs 6.5% and 11.4% in the clinic (adjusted relative risk at 3 days (aRR) (95% CI) 3.17 (1.77 to 5.66) and aRR at 7 days 2.24 (1.46 to 3.44)). The mean cost (95% CI) of care (CAD) at the index visit was $C96.68 (92.62 to 100.74) in the ED vs $C48.82 (45.47 to 52.16) in the clinic (mean difference (95% CI): 46.15 (41.29 to 51.02)). Antibiotic prescription for URTI was less common in the ED than in the clinic (1.5% vs 16.4%; aRR 0.10 (95% CI 0.03 to 0.32)). CONCLUSIONS: The incidence of return visits and cost of care were significantly higher in the ED, while antibiotic use for URTI was more frequent in the walk-in clinic. These data may help determine which setting offers the highest value to ambulatory children with acute respiratory conditions.

[Effects of extended aromatase inhibitors in women with hormone-dependent breast cancer who have already received five years of adjuvant hormone therapy: A systematic review and meta-analysis]. / Analyse des effets des inhibiteurs de l'aromatase en traitement prolongé chez les femmes ménopausées atteintes d'un cancer du sein non métastatique hormonodépendant ayant déjà reçu cinq ans d'hormonothérapie adjuvante : revue systématique et méta-analyse.

INTRODUCTION: Evaluating the benefits and risks of prolonged hormonal treatment with aromatase inhibitors (AIs) for treating hormone-dependent breast cancer. METHODS: A systematic review and meta-analysis was conducted. Studies reporting on randomized clinical trials concerning prolongating hormonal therapy with AIs as compared to a placebo or no prolongation, after an initial five years of hormonal therapy, were eligible. RESULTS: Seven clinical trials were included. Prolonged AI therapy was associated with a statistically significant improvement in disease-free survival (RR=0.70, 95% CI 0.60 to 0.80). A statistically significant increase was observed for osteoporosis (RR=1.17, 95% CI 1.03 to 1.33), hot flushes/flashes (RR=1.27, 95% CI 1.08 to 1.49), myalgia (RR=1.23, 95% CI 1.09 to 1.39), fractures (RR=1.26, 95% CI 1.09 to 1.45) and arthralgia (RR=1.17, 95% CI 1.10 to 1.25). However, no statistically significant association was observed between prolonged AI therapy and overall survival, cardiovascular events, and bone pain. DISCUSSION: Prolonged AI therapy has significant benefits in terms of disease-free survival in women with hormone-dependent breast cancer. However, adverse effects and a lack of evidence for a benefit on overall survival must be considered in the decision-making process regarding adjuvant hormone therapy extension.

Polypharmacy and risk of fractures in older adults: A systematic review.

BACKGROUND: Fractures have serious health consequences in older adults. While some medications are individually associated with increased risk of falls and fractures, it is not clear if this holds true for the use of many medications (polypharmacy). We aimed to identify what is known about the association between polypharmacy and the risk of fractures in adults aged ≥65 and to examine the methods used to study this association. METHODS: We conducted a systematic review with narrative synthesis of studies published up to October 2023 in PubMed, Embase, CINAHL, PsychINFO, Cochrane Library, Web of Science, and the grey literature. Two independent reviewers screened titles, abstracts, and full texts, then performed data extraction and quality assessment. RESULTS: Among the 31 studies included, 11 different definitions of polypharmacy were used and were based on three medication counting methods (concurrent use 15/31, cumulative use over a period 6/31, daily average 3/31, and indeterminate 7/31). Overall, polypharmacy was frequent and associated with higher fracture risk. A dose-response relationship between increasing number of medications and increased risk of fractures was observed. However, only seven studies adjusted for major confounders (age, sex, and chronic disease). The quality of the studies ranged from poor to high. CONCLUSIONS: Polypharmacy appears to be a relevant modifiable risk factor for fractures in older individuals that can easily be used to identify those at risk. The diversity of medication calculation methods and definitions of polypharmacy highlights the importance of a detailed methodology to understand and compare results.

Effect of statin use for the primary prevention of cardiovascular disease among older adults: a cautionary tale concerning target trials emulation.

OBJECTIVES: Evidence concerning the effect of statins in primary prevention of cardiovascular disease (CVD) among older adults is lacking. Using Quebec population-wide administrative data, we emulated a hypothetical randomized trial including older adults >65 years on April 1, 2013, with no CVD history and no statin use in the previous year. STUDY DESIGN AND SETTING: We included individuals who initiated statins and classified them as exposed if they were using statin at least 3 months after initiation and nonexposed otherwise. We followed them until March 31, 2018. The primary outcome was the composite endpoint of coronary events (myocardial infarction, coronary bypass, and percutaneous coronary intervention), stroke, and all-cause mortality. The intention-to-treat (ITT) effect was estimated with adjusted Cox models and per-protocol effect with inverse probability of censoring weighting. RESULTS: A total of 65,096 individuals were included (mean age = 71.0 ± 5.5, female = 55.0%) and 93.7% were exposed. Whereas we observed a reduction in the composite outcome (ITT-hazard ratio (HR) = 0.75; 95% CI: 0.68-0.83) and mortality (ITT-HR = 0.69; 95% CI: 0.61-0.77) among exposed, coronary events increased (ITT-HR = 1.46; 95% CI: 1.09-1.94). All multibias E-values were low indicating that the results were not robust to unmeasured confounding, selection, and misclassification biases simultaneously. CONCLUSION: We cannot conclude on the effectiveness of statins in primary prevention of CVD among older adults. We caution that an in-depth reflection on sources of biases and careful interpretation of results are always required in observational studies.

Assessing the performance of group-based trajectory modeling method to discover different patterns of medication adherence.

It is well known that medication adherence is critical to patient outcomes and can decrease patient mortality. The Pharmacy Quality Alliance (PQA) has recognized and identified medication adherence as an important indicator of medication-use quality. Hence, there is a need to use the right methods to assess medication adherence. The PQA has endorsed the proportion of days covered (PDC) as the primary method of measuring adherence. Although easy to calculate, the PDC has however several drawbacks as a method of measuring adherence. PDC is a deterministic approach that cannot capture the complexity of a dynamic phenomenon. Group-based trajectory modeling (GBTM) is increasingly proposed as an alternative to capture heterogeneity in medication adherence. The main goal of this paper is to demonstrate, through a simulation study, the ability of GBTM to capture treatment adherence when compared to its deterministic PDC analogue and to the nonparametric longitudinal K-means. A time-varying treatment was generated as a quadratic function of time, baseline, and time-varying covariates. Three trajectory models are considered combining a cat's cradle effect, and a rainbow effect. The performance of GBTM was compared to the PDC and longitudinal K-means using the absolute bias, the variance, the c-statistics, the relative bias, and the relative variance. For all explored scenarios, we find that GBTM performed better in capturing different patterns of medication adherence with lower relative bias and variance even under model misspecification than PDC and longitudinal K-means.

How does deprescribing (not) reduce mortality? A review of a meta-analysis in community-dwelling older adults casts uncertainty over claimed benefits.

Some meta-analyses suggest that deprescribing may reduce mortality. Our aim was to determine the underlying factors contributing to this observed reduction. We analysed data from 12 randomized controlled trials included in the latest meta-analysis on deprescribing in community-dwelling older adults. Our analysis focused on deprescribed medications and potential methodological concerns. Only a third (4/12) of the trials aimed to study mortality, and that too as a secondary outcome. Five trials reported a reduction in total medications, potentially inappropriate medications or drug-related problems. Information on specific classes of deprescribed medications was limited, although a wide array was concerned (e.g., antihypertensive, sedative, gastro-intestinal medications and vitamins). Follow-up periods were ≤1 year in 11 trials, and five trials included ≤150 participants. Small sample sizes often resulted in imbalanced groups (e.g., comorbidities, number of potentially inappropriate medications), yet no trials presented multivariable analyses. In the two trials with the most weight in the meta-analysis, several deaths occurred before the intervention, making it difficult to draw conclusions about the impact of the deprescribing intervention on mortality. These methodological issues cast significant uncertainty on the benefits of deprescribing on mortality outcomes. Large-scale, well-designed trials are needed to address this issue effectively.

Test negative design for vaccine effectiveness estimation in the context of the COVID-19 pandemic: A systematic methodology review.

BACKGROUND: During the height of the global COVID-19 pandemic, the test-negative design (TND) was extensively used in many countries to evaluate COVID-19 vaccine effectiveness (VE). Typically, the TND involves the recruitment of care-seeking individuals who meet a common clinical case definition. All participants are then tested for an infection of interest. OBJECTIVES: To review and describe the variation in TND methodology, and disclosure of potential biases, as applied to the evaluation of COVID-19 VE during the early vaccination phase of the pandemic. METHODS: We conducted a systematic review by searching four biomedical databases using defined keywords to identify peer-reviewed articles published between January 1, 2020, and January 25, 2022. We included only original articles that employed a TND to estimate VE of COVID-19 vaccines in which cases and controls were evaluated based on SARS-CoV-2 laboratory test results. RESULTS: We identified 96 studies, 35 of which met the defined criteria. Most studies were from North America (16 studies) and targeted the general population (28 studies). Outcome case definitions were based primarily on COVID-19-like symptoms; however, several papers did not consider or specify symptoms. Cases and controls had the same inclusion criteria in only half of the studies. Most studies relied upon administrative or hospital databases assembled for a different (non-evaluation) clinical purpose. Potential unmeasured confounding (20 studies), misclassification of current SARS-CoV-2 infection (16 studies) and selection bias (10 studies) were disclosed as limitations by some studies. CONCLUSION: We observed potentially meaningful deviations from the validated design in the application of the TND during the COVID-19 pandemic.

Single-dose Effectiveness of Mpox Vaccine in Quebec, Canada: Test-negative Design With and Without Adjustment for Self-reported Exposure Risk.

INTRODUCTION: During the 2022 mpox outbreak, the province of Quebec, Canada, prioritized first doses for pre-exposure vaccination of people at high mpox risk, delaying second doses due to limited supply. We estimated single-dose mpox vaccine effectiveness (VE) adjusting for virus exposure risk based only on surrogate indicators available within administrative databases (eg, clinical record of sexually transmitted infections) or supplemented by self-reported risk factor information (eg, sexual contacts). METHODS: We conducted a test-negative case-control study between 19 June and 24 September 2022. Information from administrative databases was supplemented by questionnaire collection of self-reported risk factors specific to the 3-week period before testing. Two study populations were assessed: all within the administrative databases (All-Admin) and the subset completing the questionnaire (Sub-Quest). Logistic regression models adjusted for age, calendar-time and exposure-risk, the latter based on administrative indicators only (All-Admin and Sub-Quest) or with questionnaire supplementation (Sub-Quest). RESULTS: There were 532 All-Admin participants, of which 199 (37%) belonged to Sub-Quest. With exposure-risk adjustment based only on administrative indicators, single-dose VE estimates were similar among All-Admin and Sub-Quest populations at 35% (95% confidence interval [CI]:-2 to 59) and 30% (95% CI:-38 to 64), respectively. With adjustment supplemented by questionnaire information, the Sub-Quest VE estimate increased to 65% (95% CI:1-87), with overlapping confidence intervals. CONCLUSIONS: Using only administrative data, we estimate one vaccine dose reduced the mpox risk by about one-third; whereas, additionally adjusting for self-reported risk factor information revealed greater vaccine benefit, with one dose instead estimated to reduce the mpox risk by about two-thirds. Inadequate exposure-risk adjustment may substantially under-estimate mpox VE.

SARS-CoV-2 infection among healthcare workers: the role of occupational and household exposures during the first three pandemic waves in Quebec, Canada.

Objective: We described the evolution of SARS-CoV-2 source of infection in a cohort of healthcare workers (HCWs) of Quebec, Canada, during the first three pandemic waves. We also estimated their household secondary attack rate (SAR) and its risk factors. Design: Cross-sectional surveys. Participants: HCWs with a SARS-CoV-2 infection confirmed by polymerasa chain reaction and diagnosed between March 2020 and May 2021. Methods: We collected demographic, clinical, vaccination, and employment information, self-reported perceived source of infection, and transmission to household members during the first three pandemic waves. SAR was calculated for households with ≥2 members where the HCW was the index case. A Poisson regression model estimated the association between risk factors and SAR. Results: Among the 11,670 HCWs completing the survey, 91%, perceived their workplace as the source of infection during the first wave (March-July 2020), 71% during the second wave (July 2020-March 2021), and 40% during the third wave (March-May 2021). Conversely, HCWs reported an increasing proportion of household-acquired infections with each wave from 4% to 14% and 33%, respectively. The overall household SAR of 7,990 HCWs living with ≥1 person was 30% (95%CI: 29-30). SAR increased with the presence of symptoms, older age, and during Alpha-variant predominant period. Conclusions: HCWs and their household members were largely affected during the first pandemic waves of COVID-19, but the relative importance of occupational exposure changed overtime. Pandemic preparedness in healthcare settings is essential to protect HCWs from emerging biological hazard exposures.

Socioeconomic inequalities, psychosocial stressors at work and physician-diagnosed depression: Time-to-event mediation analysis in the presence of time-varying confounders.

OBJECTIVES: There is evidence that both low socioeconomic status (SES) and psychosocial stressors at work (PSW) increase risk of depression, but prospective studies on the contribution of PSW to the socioeconomic gradient of depression are still limited. METHODS: Using a prospective cohort of Quebec white-collar workers (n = 9188 participants, 50% women), we estimated randomized interventional analogues of the natural direct effect of SES indicators at baseline (education level, household income, occupation type and a combined measure) and of their natural indirect effects mediated through PSW (job strain and effort-reward imbalance (ERI) measured at the follow-up in 1999-2001) on incident physician-diagnosed depression. RESULTS: During 3 years of follow-up, we identified 469 new cases (women: 33.1 per 1000 person-years; men: 16.8). Mainly in men, low SES was a risk factor for depression [education: hazard ratio 1.72 (1.08-2.73); family income: 1.67 (1.04-2.67); occupational type: 2.13 (1.08-4.19)]. In the entire population, exposure to psychosocial stressors at work was associated with increased risk of depression [job strain: 1.42 (1.14-1.78); effort-reward imbalance (ERI) 1.73 (1.41-2.12)]. The estimated indirect effects of socioeconomic indicators on depression mediated through job strain ranged from 1.01 (0.99-1.03) to 1.04 (0.98-1.10), 4-15% of total effects, and for low reward from 1.02 (1.00-1.03) to 1.06 (1.01-1.11), 10-15% of total effects. DISCUSSION: Our study suggests that PSW only slightly mediate the socioeconomic gradient of depression, but that socioeconomic inequalities, especially among men, and PSW both increase the incidence of depression.

On "Reflections on the concept of optimality of single decision point treatment regimes".

This is a discussion of "Reflections on the concept of optimality of single decision point treatment regimes" by Trung Dung Tran, Ariel Alonso Abad, Geert Verbeke, Geert Molenberghs, and Iven Van Mechelen. The authors propose a thoughtful consideration of optimization targets and the implications of such targets for the resulting optimal treatment rule. However, we contest the assertation that targets of optimization have been overlooked and suggest additional considerations that researchers must contemplate as part of a complete framework for learning about optimal treatment regimes.

Longitudinal plasmode algorithms to evaluate statistical methods in realistic scenarios: an illustration applied to occupational epidemiology.

INTRODUCTION: Plasmode simulations are a type of simulations that use real data to determine the synthetic data-generating equations. Such simulations thus allow evaluating statistical methods under realistic conditions. As far as we know, no plasmode algorithm has been proposed for simulating longitudinal data. In this paper, we propose a longitudinal plasmode framework to generate realistic data with both a time-varying exposure and time-varying covariates. This work was motivated by the objective of comparing different methods for estimating the causal effect of a cumulative exposure to psychosocial stressors at work over time. METHODS: We developed two longitudinal plasmode algorithms: a parametric and a nonparametric algorithms. Data from the PROspective Québec (PROQ) Study on Work and Health were used as an input to generate data with the proposed plasmode algorithms. We evaluated the performance of multiple estimators of the parameters of marginal structural models (MSMs): inverse probability of treatment weighting, g-computation and targeted maximum likelihood estimation. These estimators were also compared to standard regression approaches with either adjustment for baseline covariates only or with adjustment for both baseline and time-varying covariates. RESULTS: Standard regression methods were susceptible to yield biased estimates with confidence intervals having coverage probability lower than their nominal level. The bias was much lower and coverage of confidence intervals was much closer to the nominal level when considering MSMs. Among MSM estimators, g-computation overall produced the best results relative to bias, root mean squared error and coverage of confidence intervals. No method produced unbiased estimates with adequate coverage for all parameters in the more realistic nonparametric plasmode simulation. CONCLUSION: The proposed longitudinal plasmode algorithms can be important methodological tools for evaluating and comparing analytical methods in realistic simulation scenarios. To facilitate the use of these algorithms, we provide R functions on GitHub. We also recommend using MSMs when estimating the effect of cumulative exposure to psychosocial stressors at work.

Psychosocial Stressors at Work and Coronary Heart Disease Risk in Men and Women: 18-Year Prospective Cohort Study of Combined Exposures.

BACKGROUND: Psychosocial stressors at work, like job strain and effort-reward imbalance (ERI), can increase coronary heart disease (CHD) risk. ERI indicates an imbalance between the effort and received rewards. Evidence about the adverse effect of combined exposure to these work stressors on CHD risk is scarce. This study examines the separate and combined effect of job strain and ERI exposure on CHD incidence in a prospective cohort of white-collar workers in Quebec, Canada. METHODS: Six thousand four hundred sixty-five white-collar workers without cardiovascular disease (mean age, 45.3±6.7) were followed for 18 years (from 2000 to 2018). Job strain and ERI were measured with validated questionnaires. CHD events were retrieved from medico-administrative databases using validated algorithms. Marginal Cox models were used to calculate hazard ratios (HR) stratified by sex. Multiple imputation and inverse probability weights were applied to minimize potential threats to internal validity. RESULTS: Among 3118 men, 571 had a first CHD event. Exposure to either job strain or ERI was associated with an adjusted 49% CHD risk increase (HR, 1.49 [95% CI, 1.07-2.09]). Combined exposure to job strain and ERI was associated with an adjusted 103% CHD risk increase (HR, 2.03 [95% CI, 1.38-2.97]). Exclusion of early CHD cases and censoring at retirement did not alter these associations. Among 3347 women, 265 had a first CHD event. Findings were inconclusive (passive job HR, 1.24 [95% CI, 0.80-1.91]; active job HR, 1.16 [95% CI, 0.70-1.94]; job strain HR, 1.08 [95% CI, 0.66-1.77]; ERI HR, 1.02 [95% CI, 0.72-1.45]). CONCLUSIONS: In this prospective cohort study, men exposed to job strain or ERI, separately and in combination, were at increased risk of CHD. Early interventions on these psychosocial stressors at work in men may be effective prevention strategies to reduce CHD burden. Among women, further investigation is required.

Association between psychosocial work-related factors at midlife and arterial stiffness at older age in a prospective cohort of 1736 white-collar workers.

OBJECTIVE: Arterial stiffness and exposure to psychosocial work-related factors increase the risk of developing cardiovascular disease. However, little is known about the relationship between psychosocial work-related factors and arterial stiffness. We aimed to examine this relationship. DESIGN: Prospective cohort study. SETTING: Public organisations in Quebec City, Canada. PARTICIPANTS: The study included 1736 white-collar workers (women 52%) from 19 public organisations. PRIMARY AND SECONDARY OUTCOME MEASURES: Association between psychosocial work-related factors from the job strain and effort-reward imbalance (ERI) models assessed at study baseline (1999-2001) with validated instruments and arterial stiffness assessed using carotid-femoral pulse wave velocity at follow-up, on average 16 years later (2015-2018). Generalised estimating equations were used to estimate differences in arterial stiffness between exposed and unexposed participants. Subgroup analyses according to sex, age, blood pressure (BP), cardiovascular risk score and employment status were conducted. RESULTS: Among participants with high diastolic BP (≥90 mm Hg) at baseline, aged 47 on average, those exposed to high job strain had higher arterial stiffness (1.38 m/s (95% CI: 0.57 to 2.19)) at follow-up, 16 years later, following adjustment for a large set of potential confounders. The trend was similar in participants with high systolic BP (≥140 mm Hg) exposed to high job strain (0.84 m/s (95% CI: -0.35 to 2.03)). No association was observed for ERI in the total sample and counterintuitive associations were observed in subgroup analyses. CONCLUSIONS: Job strain may have a long-term deleterious effect on arterial stiffness in people with high BP. Interventions at midlife to reduce job strain may mitigate arterial stiffness progression.

Marginal structural models with latent class growth analysis of treatment trajectories: Statins for primary prevention among older adults.

Latent class growth analysis is increasingly proposed as a solution to summarize the observed longitudinal treatment into a few distinct groups. When latent class growth analysis is combined with standard approaches like Cox proportional hazards models, confounding bias is not properly addressed because of time-varying covariates that have a double role of confounders and mediators. We propose to use latent class growth analysis to classify individuals into a few latent classes based on their medication adherence pattern, then choose a working marginal structural model that relates the outcome to these groups. The parameter of interest is defined as a projection of the true marginal structural model onto the chosen working model. Simulation studies are used to illustrate our approach and compare it with unadjusted, baseline covariates adjusted, time-varying covariates adjusted, and inverse probability of trajectory groups weighted adjusted models. Our proposed approach yielded estimators with little or no bias and appropriate coverage of confidence intervals in these simulations. We applied our latent class growth analysis and marginal structural model approach to a database comprising information on 52,790 individuals from the province of Quebec, Canada, aged more than 65 and who were statin initiators to estimate the effect of statin-usage trajectories on a first cardiovascular event.