Path-specific causal decomposition analysis with multiple correlated mediator variables.

A causal decomposition analysis allows researchers to determine whether the difference in a health outcome between two groups can be attributed to a difference in each group's distribution of one or more modifiable mediator variables. With this knowledge, researchers and policymakers can focus on designing interventions that target these mediator variables. Existing methods for causal decomposition analysis either focus on one mediator variable or assume that each mediator variable is conditionally independent given the group label and the mediator-outcome confounders. In this article, we propose a flexible causal decomposition analysis method that can accommodate multiple correlated and interacting mediator variables, which are frequently seen in studies of health behaviors and studies of environmental pollutants. We extend a Monte Carlo-based causal decomposition analysis method to this setting by using a multivariate mediator model that can accommodate any combination of binary and continuous mediator variables. Furthermore, we state the causal assumptions needed to identify both joint and path-specific decomposition effects through each mediator variable. To illustrate the reduction in bias and confidence interval width of the decomposition effects under our proposed method, we perform a simulation study. We also apply our approach to examine whether differences in smoking status and dietary inflammation score explain any of the Black-White differences in incident diabetes using data from a national cohort study.

Area-Level Social Vulnerability and Severe COVID-19: A Case-Control Study Using Electronic Health Records from Multiple Health Systems in the Southeastern Pennsylvania Region.

Knowledge about neighborhood characteristics that predict disease burden can be used to guide equity-based public health interventions or targeted social services. We used a case-control design to examine the association between area-level social vulnerability and severe COVID-19 using electronic health records (EHR) from a regional health information hub in the greater Philadelphia region. Severe COVID-19 cases (n = 15,464 unique patients) were defined as those with an inpatient admission and a diagnosis of COVID-19 in 2020. Controls (n = 78,600; 5:1 control-case ratio) were a random sample of individuals who did not have a COVID-19 diagnosis from the same geographic area. Retrospective data on comorbidities and demographic variables were extracted from EHR and linked to area-level social vulnerability index (SVI) data using ZIP codes. Models adjusted for different sets of covariates showed incidence rate ratios (IRR) ranging from 1.15 (95% CI, 1.13-1.17) in the model adjusted for individual-level age, sex, and marital status to 1.09 (95% CI, 1.08-1.11) in the fully adjusted model, which included individual-level comorbidities and race/ethnicity. The fully adjusted model indicates that a 10% higher area-level SVI was associated with a 9% higher risk of severe COVID-19. Individuals in neighborhoods with high social vulnerability were more likely to have severe COVID-19 after accounting for comorbidities and demographic characteristics. Our findings support initiatives incorporating neighborhood-level social determinants of health when planning interventions and allocating resources to mitigate epidemic respiratory diseases, including other coronavirus or influenza viruses.

Serum zinc concentration and dietary zinc intake in relation to cognitive function: an analysis of the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort.

PURPOSE: There are several pathways by which zinc may be a modifiable factor to slow age-related cognitive decline. We investigated the associations between serum and dietary zinc and cognitive impairment in a longitudinal cohort. METHODS: We used data from the REasons for Geographic and Racial Differences in Stroke (REGARDS) Cohort (n = 30,239) and the REGARDS Trace Element Study (n = 2666). Baseline serum zinc concentrations (2003-2007) were measured using inductively coupled plasma mass spectrometry. Baseline dietary zinc intake was measured via the Block food frequency questionnaire. Serum zinc concentrations and dietary zinc intake were categorized into quartiles. The outcome of interest was impairment on the Six-Item Screener (SIS), a measure of global cognitive functioning administered annually. The Enhanced Cognitive Battery (ECB), a more comprehensive series of tests assessing memory and fluency, was administered every two years and considered a secondary outcome. Associations between zinc and incident impairment were assessed using multivariable logistic regression. RESULTS: Among 2065 participants with serum zinc data, 184 individuals developed impairment over 10 years of follow-up. In adjusted models, there was no significant association between serum zinc and impairment as assessed by the SIS or the ECB. Among 18,103 participants who had dietary data, 1424 experienced incident impairment on the SIS. Dietary zinc intake was not significantly associated with impairment as assessed by the SIS or the ECB in adjusted models. CONCLUSION: Findings from this U.S. cohort did not support the hypothesis that serum zinc concentration or dietary zinc intake is associated with the risk of cognitive impairment.

Teaching children pedestrian safety in virtual reality via smartphone: a noninferiority randomized clinical trial.

OBJECTIVE: To evaluate whether child pedestrian safety training in a smartphone-based virtual reality (VR) environment is not inferior to training in a large, semi-immersive VR environment with demonstrated effectiveness. METHODS: Five hundred 7- and 8-year-old children participated; 479 were randomized to one of two conditions: Learning to cross streets in a smartphone-based VR or learning in a semi-immersive kiosk VR. The systems used identical virtual environments and scenarios. At baseline, children's pedestrian skills were assessed in both VR systems and through a vehicle approach estimation task (judging speed/distance of oncoming traffic on monitor). Training in both conditions comprised at least six 30-min sessions in the randomly assigned VR platform and continued for up to 25 visits until adult-level proficiency was obtained. Following training and again 6 months later, children completed pedestrian safety assessments identical to baseline. Three outcomes were considered from assessments in each VR platform: Unsafe crossings (collisions plus close calls), time to contact (shortest time between child and oncoming simulated traffic), and missed opportunities (unselected safe opportunities to cross). RESULTS: Participants achieved adult-level street-crossing skill through VR training. Training in a smartphone-based VR system was generally not inferior to training in a large semi-immersive VR system. There were no adverse effects. CONCLUSIONS: Seven- and 8-year-old children can learn pedestrian safety through VR-based training, including training in a smartphone-based VR system. Combined with recent meta-analytic results, the present findings support broad implementation and dissemination of child pedestrian safety training through VR, including smartphone-based VR systems.

Children's ability to estimate approaching vehicle time-to-arrival following training in a virtual pedestrian environment.

OBJECTIVES: Child pedestrian injuries represent a significant public health challenge. Understanding the most complex cognitive skills required to cross streets helps us understand, improve, and protect children in traffic, as underdeveloped cognitive skill likely impacts children's pedestrian safety. One complex component of street-crossing is the cognitive-perceptual task of judging time-to-arrival of oncoming traffic. We examined capacity of 7- and 8-year-olds to judge time-to-arrival for vehicles approaching from varying distances and speeds, as well as improvement in those judgments following intensive street-crossing training in a virtual reality (VR) pedestrian simulator. METHODS: 500 seven- and eight-year-olds participated in a randomized trial evaluating use of a large kiosk VR versus smartphone-based VR headset to teach street-crossing skills. Prior to randomization into VR training condition and also prior to initiation of any training, children engaged in a video-based vehicle approach estimation task to assess ability to judge traffic time-to-arrival. They then engaged in multiple VR-based pedestrian safety training sessions in their randomly assigned condition until achieving adult functioning. Soon after training and again 6 months later, children repeated the vehicle estimation task. RESULTS: Prior to randomization or training, children were more accurate judging time to arrival for closer versus farther traffic, and rapidly-moving versus slower-moving traffic, but those results were subsumed by a speed x distance interaction. The interaction suggested distance cues were used more prominently than speed cues, and speed had varying effects at different distances. Training group had minimal effect on learning and all children became significantly better at judging vehicle arrival times following training. CONCLUSIONS: Children tend to underestimate vehicle arrival times. Distance cues are more impactful on time-to-arrival judgments than speed cues, but children's estimations based both on manipulations of vehicle speed and manipulations of vehicle distance improved post-training. Improvements were retained six months later. This finding is consistent with psychophysics research suggesting vehicle approach judgments rely on optical size and looming, which are impacted both by vehicle speeds and distances. Implementation of VR-based training for child pedestrian safety is recommended, as it may improve children's judgment of vehicle time-to-arrival, but it must be conducted cautiously to avoid iatrogenic effects.

Child pedestrian safety training in virtual reality: How quickly do children achieve adult functioning and what individual differences impact learning efficiency?

INTRODUCTION: Pedestrian injuries represent a leading cause of child death globally. One prevention strategy is teaching children street-crossing skills. Virtual reality (VR) has emerged as a strategy to offer repeated street-crossing practice and overcome ethical barriers of training children in live traffic. This study addressed two questions pertinent to implementation of child pedestrian safety training within VR: (a) how much training do children require to achieve adult street-crossing competency, and (b) what individual differences might facilitate children to acquire that competency more efficiently? METHODS: Five hundred 7- and 8-year-olds were recruited. Children completed pedestrian safety training within VR for up to 25 thirty-minute training sessions until they achieved adult levels of mastery. At baseline, four cognitive-perceptual skills (visual memory, visual perception, processing speed, working memory) and parent-reported externalizing symptomatology were assessed. RESULTS: On average, children achieved adult pedestrian safety competency after 10.0 training sessions (SD = 4.8). Just one child (<1%) failed to achieve adult pedestrian functioning after 25 training sessions. In univariate analyses, boys took slightly longer than girls to achieve adult functioning, and visual memory, visual perception, processing speed, working memory, and fewer externalizing symptoms were all positively associated with shorter time to mastery. In a multivariable model, only child age was a statistically significant predictor. CONCLUSION: Almost all participants achieved adult street-crossing skills competency through VR training, although they required about 10 sessions on average. Analysis of predictor variables confirmed that nearly all 7- and 8-year-olds are trainable. PRACTICAL APPLICATION: Implementation of VR pedestrian safety training is recommended, but must be conducted cautiously to ensure children are not permitted to engage independently in traffic until they are assessed and demonstrate sufficient skills.

A two-stage bayesian model for assessing the geography of racialized economic segregation and premature mortality across US counties.

Racialized economic segregation, a key metric that simultaneously accounts for spatial, social and income polarization in communities, has been linked to adverse health outcomes, including morbidity and mortality. Due to the spatial nature of this metric, the association between health outcomes and racialized economic segregation could also change with space. Most studies assessing the relationship between racialized economic segregation and health outcomes have always treated racialized economic segregation as a fixed effect and ignored the spatial nature of it. This paper proposes a two-stage Bayesian statistical framework that provides a broad, flexible approach to studying the spatially varying association between premature mortality and racialized economic segregation while accounting for neighborhood-level latent health factors across US counties. The two-stage framework reduces the dimensionality of spatially correlated data and highlights the importance of accounting for spatial autocorrelation in racialized economic segregation measures, in health equity focused settings.

N-Terminal Pro-B-Type Natriuretic Peptide and Risk for Diabetes Mellitus and Metabolic Syndrome.

CONTEXT: Natriuretic peptide concentrations are inversely associated with risk of diabetes mellitus and may be protective from metabolic dysfunction. OBJECTIVE: We studied associations of N-terminal pro-B-type natriuretic peptide (NT-proBNP) with incident diabetes, metabolic syndrome (MetS), and MetS components. DESIGN/SETTING/PARTICIPANTS: 2,899 participants with baseline (2003-2007) and follow-up (2013-2016) examinations and baseline NT-proBNP measurement in the REasons for Geographic And Racial Differences in Stroke study. Logistic regression models were fitted to incident MetS, MetS components, and diabetes; covariates included demographics, risk and laboratory factors. MAIN OUTCOME MEASURES: Incident diabetes, defined as fasting glucose ≥126 mg/dL, random glucose ≥200 mg/dL, or use of insulin or hypoglycemic drugs at follow-up but not baseline. Incident MetS, in participants with ≥3 harmonized criteria at follow-up and <3 at baseline. RESULTS: 310 participants (2,364 at risk) developed diabetes and 361 (2,059 at risk) developed MetS over mean 9.4 years follow-up. NT-proBNP was inversely associated with odds of incident diabetes (fully-adjusted OR per-SD higher log NT-proBNP 0.80, 95% CI 0.69-0.93) and MetS in the highest vs. lowest quartile only (fully-adjusted OR 0.59, 95% CI 0.37-0.92); the linear association with incident MetS was not statistically significant. NT-proBNP was inversely associated with incident dysglycemia in all models (fully-adjusted OR per-SD log NT-proBNP 0.65, 95% CI 0.53-0.79), but not with other MetS components. Effect modification by sex, race, age, or BMI was not observed. CONCLUSIONS: NT-proBNP was inversely associated with odds of diabetes, MetS, and the MetS dysglycemia component. The metabolic implications of B-type natriuretic peptides appear important for glycemic homeostasis.

Changes in Adiposity and Cognitive Function in Older Adults: The REGARDS Study.

OBJECTIVES: Adiposity may have a role in the risk of dementia. Fewer studies have focused on the relationship between change in adiposity and cognitive decline. Our study aimed to explore the association between the change in adiposity and cognitive function in Black and White older adults. METHODS: The participants were 12,204 older adults without cognitive impairment (62.8 ±â€…8.0 years) in the United States. The percent body mass index change (%BMI change) and percent waist circumference change (%WC change) were measured at 2 in-home visits (first: 2003-2007, second: 2013-2016). Cognitive status was assessed by the Six-Item Screener annually. Memory and executive function were measured by word list learning, MOCA recall and orientation, and letter and animal fluency every 2 years. Logistic regression or linear regression models were used to estimate the relationship between percent change in adiposity and cognitive function. RESULTS: After 12.7 ±â€…1.7 years, a greater decrease in %BMI change or %WC change was significantly associated with a higher risk of cognitive impairment. Compared to older adults with -5% ≤ change ≤ 5% from baseline, a significantly higher risk of cognitive impairment and greater loss in memory and executive function were found among those who experienced more than a 10% decline in %BMI change or %WC change. Older adults who experienced a 5%-10% decrease in %BMI change had a higher risk of cognitive impairment and greater loss of memory compared to those with -5% ≤ change ≤ 5%. DISCUSSION: A greater decrease in %BMI (>5%) and %WC (>10%) change was associated with greater cognitive loss observed over time.