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BACKGROUND: The exposome serves as a popular framework in which to study exposures from chemical and nonchemical stressors across the life course and the differing roles that these exposures can play in human health. As a result, data relevant to the exposome have been used as a resource in the quest to untangle complicated health trajectories and help connect the dots from exposures to adverse outcome pathways. OBJECTIVES: The primary aim of this methods seminar is to clarify and review preprocessing techniques critical for accurate and effective external exposomic data analysis. Scalability is emphasized through an application of highly innovative combinatorial techniques coupled with more traditional statistical strategies. The Public Health Exposome is used as an archetypical model. The novelty and innovation of this seminar's focus stem from its methodical, comprehensive treatment of preprocessing and its demonstration of the positive effects preprocessing can have on downstream analytics. DISCUSSION: State-of-the-art technologies are described for data harmonization and to mitigate noise, which can stymie downstream interpretation, and to select key exposomic features, without which analytics may lose focus. A main task is the reduction of multicollinearity, a particularly formidable problem that frequently arises from repeated measurements of similar events taken at various times and from multiple sources. Empirical results highlight the effectiveness of a carefully planned preprocessing workflow as demonstrated in the context of more highly concentrated variable lists, improved correlational distributions, and enhanced downstream analytics for latent relationship discovery. The nascent field of exposome science can be characterized by the need to analyze and interpret a complex confluence of highly inhomogeneous spatial and temporal data, which may present formidable challenges to even the most powerful analytical tools. A systematic approach to preprocessing can therefore provide an essential first step in the application of modern computer and data science methods. https://doi.org/10.1289/EHP12901, Introduction The exposome is generally viewed as a measure of all the environmental exposures an individual has had over a lifetime. The systematic stratagem of capturing these exposures under a [...]

BackgroundVitamin D supplementation may be an inexpensive intervention to reduce heart failure (HF) incidence. However, there are insufficient data to support this hypothesis. This study evaluates whether vitamin D plus calcium (CaD) supplementation is associated with lower rates of HF in postmenopausal women and whether the effects differ between those at high versus low risk for HF.Methods and resultsAnalyses were restricted to 35 983 (of original 36 282) women aged 50 to 79 years old in the Women's Health Initiative randomized trial of CaD supplementation who were randomized 1:1 in a double-blinded fashion to receive 1000 mg/d of calcium plus 400 IU/d of vitamin D3 or placebo. Overall, 744 adjudicated incident HF cases (intervention, 363; control, 381) occurred during a median follow-up of 7.1 (interquartile range, 1.6) years. CaD supplementation, compared with placebo, was not associated with reduced HF risk in the overall population, hazard ratio, 0.95; P=0.46. However, CaD supplementation had differential effects (P interaction=0.005) in subgroups stratified by baseline risk status of HF defined by the presence (high risk=17 449) or absence (low risk=18 534) of pre-existing HF precursors including coronary heart diseases, diabetes mellitus, or hypertension: 37% (hazard ratio, 0.63 [95% confidence interval, 0.46-0.87]) lower risk of HF in the low-risk versus hazard ratio, 1.06; P=0.51, in the high-risk subgroups.ConclusionsCaD supplementation did not significantly reduce HF incidence in the overall cohort, however, it was beneficial among postmenopausal women without major HF precursors while of little value in high-risk subgroups. Additional studies are warranted to confirm these findings and investigate the underlying mechanism.Clinical trial registration urlhttp://www.clinicaltrials.gov. Unique identifier: NCT00000611.

Purpose: To determine the impact of a business intelligence dashboard tool to optimize automated dispensing cabinets (ADCs). Methods: A pre-post implementation design was used to evaluate key performance indicators (KPI) before and after the implementation of a dashboard tool to optimize ADCs. Eleven ADCs were optimized in 2 phases according to dashboard recommendations: (1) removal of unused medications over 90 days, (2) adjusting periodic automatic replenishment (PAR) levels, and (3) addition of commonly dispensed medications. The KPI measures that were assessed included inventory cost, no. of stocked medications, stockout percentage, vend to refill ratio, and missing dose messages from nursing. An interrupted-time-series regression was used to quantify the impact of ADCs on the means of measured KPIs. Results: Differences in mean distribution of all KPIs, except missing dose, between the pre- and post-ADC periods during the Phase 1 period were statistically significant: inventory cost (54.2 vs 56), stockout percentage (1.55 vs 1.12), vend to refill ratio (6.83 vs 6.14), and missing dose messages (221 vs 229). Only the mean ADC utilization (57.3 vs 64) and missing dose (228 vs 179) were statistically different between the pre- and post-ADC periods in Phase 2. The interrupted-time-series analysis showed that Phase 1 optimization significantly reduced the cost of inventory (β = −$1.238.00, P <.01), no. Stocked medications (β = −8.2, P <.01), percent stockout (β = −.49%, P <.01), vend-to-refill ratio (β = −1.29%, P<.01) and ADC utilization (β = −.2, P <.01). Conclusion: Automated dispensing cabinets optimization, through the use of a dashboard tool, had a positive impact on almost all measured KPIs. [ABSTRACT FROM AUTHOR]

Aims: The aim of this study was to describe the 1‐year direct and indirect transition probabilities to premature discontinuation of statin therapy after concurrently initiating statins and CYP3A4‐inhibitor drugs. Methods: A retrospective new‐user cohort study design was used to identify (N = 160 828) patients who concurrently initiated CYP3A4 inhibitors (diltiazem, ketoconazole, clarithromycin, others) and CYP3A4‐metabolized statins (statin DDI exposed, n = 104 774) vs. other statins (unexposed to statin DDI, n = 56 054) from the MarketScan commercial claims database (2012–2017). The statin DDI exposed and unexposed groups were matched (2:1) through propensity score matching techniques. We applied a multistate transition model to compare the 1‐year transition probabilities involving four distinct states (start, adverse drug events [ADEs], discontinuation of CYP3A4‐inhibitor drugs, and discontinuation of statin therapy) between those exposed to statin DDIs vs. those unexposed. Statistically significant differences were assessed by comparing the 95% confidence intervals (CIs) of probabilities. Results: After concurrently starting stains and CYP3A, patients exposed to statin DDIs, vs. unexposed, were significantly less likely to discontinue statin therapy (71.4% [95% CI: 71.1, 71.6] vs. 73.3% [95% CI: 72.9, 73.6]) but more likely to experience an ADE (3.4% [95% CI: 3.3, 3.5] vs. 3.2% [95% CI: 3.1, 3.3]) and discontinue with CYP3A4‐inhibitor therapy (21.0% [95% CI: 20.8, 21.3] vs. 19.5% [95% CI: 19.2, 19.8]). ADEs did not change these associations because those exposed to statin DDIs, vs. unexposed, were still less likely to discontinue statin therapy but more likely to discontinue CYP3A4‐inhibitor therapy after experiencing an ADE. Conclusion: We did not observe any meaningful clinical differences in the probability of premature statin discontinuation between statin users exposed to statin DDIs and those unexposed. [ABSTRACT FROM AUTHOR]

Objective: Older adults typically experience higher rates of severe disease and mortality than the general population after contracting an infectious disease. Vaccination is critical for preventing disease and severe downstream outcomes; however, vaccination rates among older adults are suboptimal. We assessed predictors associated with pneumococcal and seasonal influenza vaccination among older women. Methods: We used data from the Women's Health Initiative, a nationwide cohort of women. We ascertained seasonal influenza and pneumococcal vaccination status through a questionnaire administered in 2013. We limited analyses to women aged ≥65 years at questionnaire administration. We used logistic regression to estimate associations between demographic, lifestyle, and health-related factors and vaccination and explored stratification by race. Results: Of participants who responded to each question, 84.3% (n = 60 578) reported being vaccinated for influenza and 85.5% (n = 59 015) for pneumonia. The odds of reporting influenza vaccination were significantly lower among non-Hispanic Black participants than among non-Hispanic White participants (odds ratio [OR] = 0.53; 95% CI, 0.49-0.58), women with no health insurance versus private health insurance (OR = 0.61; 95% CI, 0.54-0.68), and women living in rural versus urban settings (OR = 0.84; 95% CI, 0.73-0.96). Current smoking, lower education levels, and having comorbid conditions were associated with lower likelihood of being vaccinated for influenza (than not); past pneumonia diagnosis and being currently married were associated with a higher likelihood. We observed similar associations for pneumococcal vaccination coverage. Conclusions: These findings reinforce the need to enact policy and implement programs to improve access to, education and awareness about, and provider recommendations for these critical disease-prevention tools. Results from our study should guide strategies for SARS-CoV-2 vaccination. [ABSTRACT FROM AUTHOR]

Background: Several clinical trials have documented clinical benefits associated with prophylactic corticosteroid administration at the time of coronary artery bypass graft (CABG) surgery, including a reduction in the risk of atrial fibrillation and hospital length of stay. Despite the published data, the extent to which providers have adopted the perioperative use of corticosteroids remains unknown.Objectives: To assess temporal trends, between-hospital variation, and determinants of perioperative intravenous corticosteroid use during CABG surgery.Methods: We identified all patients admitted for CABG surgery in the Premier Healthcare Database (2003-2014), a large US-based inpatient database. We determined the proportion of patients administered prophylactic corticosteroids on the day of CABG surgery. Linear time-series models were used to estimate the rate and trend of corticosteroid use over time. Separate multivariable generalized estimating equation models were used to quantify the variation in and determinants of perioperative corticosteroid use.Results: Of 401 788 eligible patients who underwent a CABG surgery between 2003 and 2014, 20% (n = 80 681) were administered intravenous prophylactic perioperative corticosteroids (methylprednisolone, dexamethasone, or hydrocortisone). Corticosteroid use increased from 17.5% in 2003 to 22.6% in 2014 (annual rate = 0.42%; P < .001). Individual hospitals accounted for >50% of variation in corticosteroid use. High between-hospital variation was also observed, and the probability of utilization was ≥32.4% in the upper versus ≤3.4% in the bottom quartiles of hospitals.Conclusion: Prophylactic corticosteroid administration during CABG has increased gradually since 2003. To further evaluate the risk-benefit trade-off associated with their use, we believe a large-scale outcomes study is warranted to assess this highly variable practice. [ABSTRACT FROM AUTHOR]

There is a well-documented association between ambient fine particulate matter air pollution (PM2.5) and cardiovascular disease (CVD) morbidity and mortality. Exposure to PM2.5 can cause premature death and harmful and chronic health effects such as heart attack, diabetes, and stroke. The Environmental Protection Agency sets annual PM2.5 standards to reduce these negative health effects. Currently above an annual average level of 12.0 µg/m is considered unhealthy. Methods. We examined the association of long-term exposure to PM2.5 and CVD in a cohort of 44,610 individuals who resided in 12 states recruited into the Southern Community Cohort Study (SCCS). The SCCS was designed to recruit Black and White participants who received care from Federally Qualified Health Centers; hence, they represent vulnerable individuals from low-income families across this vast region. This study tests whether SCCS participants who lived in locations exposed to elevated ambient levels of PM2.5 concentrations were more likely to report a history of CVD at enrollment (2002–2009). Remotely sensed satellite data integrated with ground monitoring data provide an assessment of the average annual PM2.5 in urban and rural locations where the SCCS participants resided. We used multilevel logistic regression to estimate the associations between self-reported CVD and exposure to elevated ambient levels of PM2.5. Results. We found a 13.4 percent increase in the odds of reported CVD with exposure to unhealthy levels of PM2.5 exposure at enrollment. The SCCS participants with medical histories of hypertension, hypercholesterolemia, and smoking had, overall, 385 percent higher odds of reported CVD than those without these clinical risk factors. Additionally, Black participants were more likely to live in locations with higher ambient PM2.5 concentrations and report high levels of clinical risk factors, thus, they may be at a greater future risk of CVD. Conclusions: In the SCCS participants, we found a strong relation between exposures to high ambient levels of PM2.5 and self-reported CVD at enrollment. [ABSTRACT FROM AUTHOR]

(1) Background: Cardio-metabolic diseases (CMD), including cardiovascular disease, stroke, and diabetes, have numerous common individual and environmental risk factors. Yet, few studies to date have considered how these multiple risk factors together affect CMD disparities between Blacks and Whites. (2) Methods: We linked daily fine particulate matter (PM 2.5 ) measures with survey responses of participants in the Southern Community Cohort Study (SCCS). Generalized linear mixed modeling (GLMM) was used to estimate the relationship between CMD risk and social-demographic characteristics, behavioral and personal risk factors, and exposure levels of PM 2.5 . (3) Results: The study resulted in four key findings: (1) PM 2.5 concentration level was significantly associated with reported CMD, with risk rising by 2.6% for each µg/m 3 increase in PM 2.5 ; (2) race did not predict CMD risk when clinical, lifestyle, and environmental risk factors were accounted for; (3) a significant variation of CMD risk was found among participants across states; and (4) multiple personal, clinical, and social-demographic and environmental risk factors played a role in predicting CMD occurrence. (4) Conclusions: Disparities in CMD risk among low social status populations reflect the complex interactions of exposures and cumulative risks for CMD contributed by different personal and environmental factors from natural, built, and social environments., Competing Interests: The authors declare no conflict of interest.

Objectives: Providers who do not contract with insurance plans are considered out-of-network (OON) providers. There were 2 objectives in this study: (1) to examine the variations of OON cost sharing, both at the state level and by care settings, and (2) to investigate the pattern of OON care use and cost sharing associated with OON care over time., Study Design: Secondary data analysis using claims data of employer-sponsored insurance enrollees., Methods: The study sample included adults aged 18 to 64 years who were continuously enrolled for at least a full calendar year with medical and prescription drug coverage and for whom OON care payment data were available. We examined levels and distributions of cost sharing for OON care from 2012 to 2017, in both emergency department (ED) and non-ED care settings. Outcome measures included annual use of health plan-covered OON care and total out-of-pocket (OOP) cost sharing for OON care. We also measured the use of and cost-sharing spending for OON care based on urgency and site of service. Logistic regression models were constructed to estimate the probability of OON care. Among those with each type of OON care, a generalized linear regression model was used to estimate the OOP spending on OON care., Results: Slowly decreasing rates of OON care over time occurred in different care settings and at different urgency levels. The cost-sharing amounts for OON care rose rapidly from 2012 through 2016, before slowing slightly in 2017. The growth of cost sharing for OON care during nonemergent hospitalizations especially increased from $671 to $1286 during the study period. The amount enrollees spent on OON care grew in most states, but there were substantial variations., Conclusions: Cost-sharing payments for OON care represent a growing financial burden for some enrollees. Consumers should be held harmless from higher cost sharing for OON care when it occurs without their knowledge or consent. Further, health plan network adequacy may also merit closer scrutiny. Leveraging provider participation in narrow networks must be balanced with broader consumer protections.