Testing a brief web-based intervention to increase recognition of tobacco constituents

Objective: We examined website formats to increase smokers\u27 recognition of harmful and potentially harmful constituents (HPHCs) in cigarettes. Methods: Adult, daily smokers (N = 279) were randomized to view a brief, single-page study website showing HPHC names and uses. The intervention site was tailored + interactive, labeled by cigarette brand/subbrand showing color imagery and pop-up boxes; the generic + static website (control) was unbranded in greyscale. Eye tracking equipment measured attention (dwell time) to precise website features. Linear regression analyses compared attention to HPHC descriptions and the correct recognition of 15 HPHC chemicals. A randomly selected sub-sample (N = 30) of participants qualitatively rated website usability. Results: Despite spending less dwell time on the HPHC text and entire website, adult smokers who viewed the generic + static website had greater improvement in HPHC recognition compared to the tailored + interactive website (4.6 vs 3.6; p = .02); this finding contrasts with current literature on tailoring and interactivity. Both websites were rated highly on ease-of-use and readability. Conclusions: Basic formats and narrative HPHC Web-based content attracted less visual attention, yet increased recognition of these chemicals in cigarettes, compared to brand-tailored, interactive web-based content

Distribution of cardiovascular health by individual- and neighborhood-level socioeconomic status: Findings from the Jackson Heart Study

BACKGROUND: Data demonstrate a positive relationship between socioeconomic status (SES) and cardiovascular health (CVH). OBJECTIVE: To assess the association between individual- and neighborhood-level SES and CVH among participants of the JHS (Jackson Heart Study), a community-based cohort of African Americans in Jackson, Mississippi. METHODS: We included all JHS participants with complete SES and CVH information at the baseline study visit (n = 3,667). We characterized individual- and neighborhood-level SES according to income (primary analysis) and education (secondary analysis), respectively. The outcome of interest for these analyses was a CVH score, based on 7 modifiable behaviors and factors, summed to a total of 0 (worst) to 14 (best) points. We utilized generalized estimating equations to account for the clustering of participants within the same residential areas to estimate the linear association between SES and CVH. RESULTS: The median age of the participants was 55 years, and 64% were women. Nearly one-third of eligible participants had individual incomes \u3c$20,000 and close to 40$25,480). Adjusted for age, sex, and neighborhood SES, there was an average increase in CVH score of 0.31 points associated with each 1-category increase in individual income. Similarly, each 1-category increase in neighborhood SES was associated with a 0.19-point increase in CVH score. These patterns held for our secondary analyses, which used educational attainment in place of income. These data did not suggest a synergistic effect of individual- and neighborhood-level SES on CVH. CONCLUSIONS: Our findings suggest a potential causal pathway for disparities in CVH among vulnerable populations. These data can be useful to the JHS community to empower public health and clinical interventions and policies for the improvement of CVH

A Comparison of Benefit Limits in Mental Health

This study provides insight to policy makers and stakeholders on how three types of benefits limits on Medicaid-covered mental health services might affect access for consumers diagnosed with severe mental illness. The study used a retrospective cohort design with data for Medicaid-covered, community-based mental health services provided in Ohio during fiscal year 2010. Log-binomial regression was used for the analysis. Results indicate that limits compared have significant, varying consequences based on Medicaid coverage and diagnoses. When constraining Medicaid costs, policy makers should consider how limits will disrupt care and include clinicians in discussions prior to implementatio

More data, less information? Potential for nonmonotonic information growth using GEE

<p>Statistical intuition suggests that increasing the total number of observations available for analysis should increase the precision with which parameters can be estimated. Such monotonic growth of statistical information is of particular importance when data are analyzed sequentially, such as in confirmatory clinical trials. However, monotonic information growth is not always guaranteed, even when using a valid, but inefficient estimator. In this article, we demonstrate the theoretical possibility of nonmonotonic information growth when using generalized estimating equations (GEE) to estimate a slope and provide intuition for why this possibility exists. We use theoretical and simulation-based results to characterize situations that may result in nonmonotonic information growth. Nonmonotonic information growth is most likely to occur when (1) accrual is fast relative to follow-up on each individual, (2) correlation among measurements from the same individual is high, and (3) measurements are becoming more variable further from randomization. In situations that may lead to nonmonotonic information growth, study designers should plan interim analyses to avoid situations most likely to result in nonmonotonic information growth.</p

Association of Oral Calcitriol with Improved Survival in Nondialyzed CKD

Parenteral vitamin D is associated with improved survival among long-term hemodialysis patients. Among nondialyzed patients with chronic kidney disease (CKD), oral activated vitamin D reduces parathyroid hormone levels, but the impact on clinical outcomes is unknown. We evaluated associations of oral calcitriol use with mortality and dialysis dependence in 1418 nondialysis patients with CKD and hyperparathyroidism in the Veterans’ Affairs Consumer Health Information and Performance Sets database. Incident calcitriol users and nonusers were selected on the basis of stages 3 to 4 CKD, hyperparathyroidism, and the absence of hypercalcemia before calcitriol use and then were matched by age and estimated kidney function. During a median follow-up of 1.9 yr, 408 (29%) patients died and 217 (16%) initiated long-term dialysis. After adjustment for demographics; comorbidities; estimated kidney function; medications; and baseline levels of parathyroid hormone, calcium, and phosphorous, oral calcitriol use was associated with a 26% lower risk for death (95% confidence interval 5 to 42% lower; P = 0.016) and a 20% lower risk for death or dialysis (95% confidence interval 1 to 35% lower; P = 0.038). The association of calcitriol with improved survival was not statistically different across baseline parathyroid hormone levels. Calcitriol use was associated with a greater risk for hypercalcemia. In conclusion, oral calcitriol use is associated with lower mortality in nondialysis patients with CKD

Marginal modeling in community randomized trials with rare events: Utilization of the negative binomial regression model

This work is motivated by the HEALing Communities Study, which is a post-test only cluster randomized trial in which communities are randomized to two different trial arms. The primary interest is in reducing opioid overdose fatalities, which will be collected as a count outcome at the community level. Communities range in size from thousands to over one million residents, and fatalities are expected to be rare. Traditional marginal modeling approaches in the cluster randomized trial literature include the use of generalized estimating equations with an exchangeable correlation structure when utilizing subject-level data, or analogously quasi-likelihood based on an over-dispersed binomial variance when utilizing community-level data. These approaches account for and estimate the intra-cluster correlation coefficient, which should be provided in the results from a cluster randomized trial. Alternatively, the coefficient of variation or R coefficient could be reported. In this article, we show that negative binomial regression can also be utilized when communities are large and events are rare. The objectives of this article are (1) to show that the negative binomial regression approach targets the same marginal regression parameter(s) as an over-dispersed binomial model and to explain why the estimates may differ; (2) to derive formulas relating the negative binomial overdispersion parameter k with the intra-cluster correlation coefficient, coefficient of variation, and R coefficient; and (3) analyze pre-intervention data from the HEALing Communities Study to demonstrate and contrast models and to show how to report the intra-cluster correlation coefficient, coefficient of variation, and R coefficient when utilizing negative binomial regression. Negative binomial and over-dispersed binomial regression modeling are contrasted in terms of model setup, regression parameter estimation, and formulation of the overdispersion parameter. Three specific models are used to illustrate concepts and address the third objective. The negative binomial regression approach targets the same marginal regression parameter(s) as an over-dispersed binomial model, although estimates may differ. Practical differences arise in regard to how overdispersion, and hence the intra-cluster correlation coefficient is modeled. The negative binomial overdispersion parameter is approximately equal to the ratio of the intra-cluster correlation coefficient and marginal probability, the square of the coefficient of variation, and the R coefficient minus 1. As a result, estimates corresponding to all four of these different types of overdispersion parameterizations can be reported when utilizing negative binomial regression. Negative binomial regression provides a valid, practical, alternative approach to the analysis of count data, and corresponding reporting of overdispersion parameters, from community randomized trials in which communities are large and events are rare

Electronic health record-based assessment of cardiovascular health: The stroke prevention in healthcare delivery environments (SPHERE) study

<3% of Americans have ideal cardiovascular health (CVH). The primary care encounter provides a setting in which to conduct patient-provider discussions of CVH. We implemented a CVH risk assessment, visualization, and decision-making tool that automatically populates with electronic health record (EHR) data during the encounter in order to encourage patient-centered CVH discussions among at-risk, yet under-treated, populations. We quantified five of the seven CVH behaviors and factors that were available in The Ohio State University Wexner Medical Center's EHR at baseline (May–July 2013) and compared values to those ascertained at one-year (May–July 2014) among intervention (n = 109) and control (n = 42) patients. The CVH of women in the intervention clinic improved relative to the metrics of body mass index (16% to 21% ideal) and diabetes (62% to 68% ideal), but not for smoking, total cholesterol, or blood pressure. Meanwhile, the CVH of women in the control clinic either held constant or worsened slightly as measured using those same metrics. Providers need easy-to-use tools at the point-of-care to help patients improve CVH. We demonstrated that the EHR could deliver such a tool using an existing American Heart Association framework, and we noted small improvements in CVH in our patient population. Future work is needed to assess how to best harness the potential of such tools in order to have the greatest impact on the CVH of a larger patient population. Keywords: Prevention, Primary care, Medical informatics, Health outcomes, Disease managemen

25-Hydroxyvitamin D Levels Inversely Associate with Risk for Developing Coronary Artery Calcification

Vitamin D deficiency associates with increased risk for cardiovascular events and mortality, but the mechanism driving this association is unknown. Here, we tested whether circulating 25-hydroxyvitamin D concentration associates with coronary artery calcification (CAC), a measure of coronary atherosclerosis, in the Multi-Ethnic Study of Atherosclerosis. We included 1370 participants: 394 with and 976 without chronic kidney disease (estimated GFR <60 ml/min per 1.73 m2). At baseline, CAC was prevalent among 723 (53%) participants. Among participants free of CAC at baseline, 135 (21%) developed incident CAC during 3 yr of follow-up. Lower 25-hydroxyvitamin D concentration did not associate with prevalent CAC but did associate with increased risk for developing incident CAC, adjusting for age, gender, race/ethnicity, site, season, physical activity, smoking, body mass index, and kidney function. Further adjustment for BP, diabetes, C-reactive protein, and lipids did not alter this finding. The association of 25-hydroxyvitamin D with incident CAC seemed to be stronger among participants with lower estimated GFR. Circulating 1,25-dihydroxyvitamin D concentrations among participants with chronic kidney disease did not significantly associate with prevalent or incident CAC in adjusted models. In conclusion, lower 25-hydroxyvitamin D concentrations associate with increased risk for incident CAC. Accelerated development of atherosclerosis may underlie, in part, the increased cardiovascular risk associated with vitamin D deficiency