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Introduction: Reproducible research is increasingly gaining interest in the research community. Automating the production of research manuscript tables from statistical software can help increase the reproducibility of findings. Logistic regression is used in studying disease prevalence and associated factors in epidemiological studies and can be easily performed using widely available software including SAS, SUDAAN, Stata or R. However, output from these software must be processed further to make it readily presentable. There exists a number of procedures developed to organize regression output, though many of them suffer limitations of flexibility, complexity, lack of validation checks for input parameters, as well as inability to incorporate survey design. Methods: We developed a SAS macro, %svy_logistic_regression, for fitting simple and multiple logistic regression models. The macro also creates quality publication-ready tables using survey or non-survey data which aims to increase transparency of data analyses. It further significantly reduces turn-around time for conducting analysis and preparing output tables while also addressing the limitations of existing procedures. In addition, the macro allows for user-specific actions to handle missing data as well as use of replication-based variance estimation methods. Results: We demonstrate the use of the macro in the analysis of the 2013–2014 National Health and Nutrition Examination Survey (NHANES), a complex survey designed to assess the health and nutritional status of adults and children in the United States. The output presented here is directly from the macro and is consistent with how regression results are often presented in the epidemiological and biomedical literature, with unadjusted and adjusted model results presented side by side. Conclusions: The SAS code presented in this macro is comprehensive, easy to follow, manipulate and to extend to other areas of interest. It can also be incorporated quickly by the statistician for immediate use. It is an especially valuable tool for generating quality, easy to review tables which can be incorporated directly in a publication. [ABSTRACT FROM AUTHOR]

A causal association of air pollution with mental diseases is an intriguing possibility raised in a Short Report just published in PLOS Biology. Despite analyses involving large data sets, the available evidence has substantial shortcomings, and a long series of potential biases may invalidate the observed associations. Only bipolar disorder shows consistent results, with similar effects across United States and Denmark data sets, but the effect has modest magnitude, appropriate temporality is not fully secured, and biological gradient, plausibility, coherence, and analogy offer weak support. The signal seems to persist in some robustness analyses, but more analyses by multiple investigators, including contrarians, are necessary. Broader public sharing of data sets would also enhance transparency. [ABSTRACT FROM AUTHOR]

Estimation of influenza-like illness (ILI) using search trends activity was intended to supplement traditional surveillance systems, and was a motivation behind the development of Google Flu Trends (GFT). However, several studies have previously reported large errors in GFT estimates of ILI in the US. Following recent release of time-stamped surveillance data, which better reflects real-time operational scenarios, we reanalyzed GFT errors. Using three data sources—GFT: an archive of weekly ILI estimates from Google Flu Trends; ILIf: fully-observed ILI rates from ILINet; and, ILIp: ILI rates available in real-time based on partial reporting—five influenza seasons were analyzed and mean square errors (MSE) of GFT and ILIp as estimates of ILIf were computed. To correct GFT errors, a random forest regression model was built with ILI and GFT rates from the previous three weeks as predictors. An overall reduction in error of 44% was observed and the errors of the corrected GFT are lower than those of ILIp. An 80% reduction in error during 2012/13, when GFT had large errors, shows that extreme failures of GFT could have been avoided. Using autoregressive integrated moving average (ARIMA) models, one- to four-week ahead forecasts were generated with two separate data streams: ILIp alone, and with both ILIp and corrected GFT. At all forecast targets and seasons, and for all but two regions, inclusion of GFT lowered MSE. Results from two alternative error measures, mean absolute error and mean absolute proportional error, were largely consistent with results from MSE. Taken together these findings provide an error profile of GFT in the US, establish strong evidence for the adoption of search trends based 'nowcasts' in influenza forecast systems, and encourage reevaluation of the utility of this data source in diverse domains. [ABSTRACT FROM AUTHOR]

The Medical Monitoring Project (MMP) is an HIV surveillance system that provides national estimates of HIV-related behaviors and clinical outcomes. When first implemented, MMP excluded persons living with HIV not receiving HIV care. This analysis will describe new case-surveillance-based methods to identify and recruit persons living with HIV who are out of care and at elevated risk for mortality and ongoing HIV transmission. Stratified random samples of all persons living with HIV were selected from the National HIV Surveillance System in five public health jurisdictions from 2012–2014. Sampled persons were located and contacted through seven different data sources and five methods of contact to collect interviews and medical record abstractions. Data were weighted for non-response and case reporting delay. The modified sampling methodology yielded 1159 interviews (adjusted response rate, 44.5%) and matching medical record abstractions for 1087 (93.8%). Of persons with both interview and medical record data, 264 (24.3%) would not have been included using prior MMP methods. Significant predictors were identified for successful contact (e.g., retention in care, adjusted Odds Ratio [aOR] 5.02; 95% Confidence Interval [CI] 1.98–12.73), interview (e.g. moving out of jurisdiction, aOR 0.24; 95% CI: 0.12–0.46) and case reporting delay (e.g. rural residence, aOR 3.18; 95% CI: 2.09–4.85). Case-surveillance-based sampling resulted in a comparable response rate to existing MMP methods while providing information on an important new population. These methods have since been adopted by the nationally representative MMP surveillance system, offering a model for public health program, research and surveillance endeavors seeking inclusion of all persons living with HIV. [ABSTRACT FROM AUTHOR]

Conotruncal heart defects (CTDs) are among the most common and severe groups of congenital heart defects. Despite evidence of an inherited genetic contribution to CTDs, little is known about the specific genes that contribute to the development of CTDs. We performed gene-based genome-wide analyses using microarray-genotyped and imputed common and rare variants data from two large studies of CTDs in the United States. We performed two case-parent trio analyses (N = 640 and 317 trios), using an extension of the family-based multi-marker association test, and two case-control analyses (N = 482 and 406 patients and comparable numbers of controls), using a sequence kernel association test. We also undertook two meta-analyses to combine the results from the analyses that used the same approach (i.e. family-based or case-control). To our knowledge, these analyses are the first reported gene-based, genome-wide association studies of CTDs. Based on our findings, we propose eight CTD candidate genes (ARF5, EIF4E, KPNA1, MAP4K3, MBNL1, NCAPG, NDFUS1 and PSMG3). Four of these genes (ARF5, KPNA1, NDUFS1 and PSMG3) have not been previously associated with normal or abnormal heart development. In addition, our analyses provide additional evidence that genes involved in chromatin-modification and in ribonucleic acid splicing are associated with congenital heart defects. [ABSTRACT FROM AUTHOR]

Objective: To investigate the accuracy and precision of ultrasound shear wave elasticity measurements as a function of target elasticity and acquisition depth. Materials and methods: Using five ultrasound systems (VTQ, VTIQ, EPIQ 5, Aixplorer, and Aplio 500), two operators independently measured shear wave elasticities in two phantoms containing five different target elasticities (8±3, 14±4, 25±6, 45±8, and 80±12 kPa) at depths of 15, 30, 35, and 60 mm. Accuracy was assessed by evaluating measurement errors and the proportions of outliers, while factors affecting accuracy were assessed using logistic regression analysis. Measurement errors were defined as differences between the measured values and 1) the margins of the target elasticity, and 2) the median values of the target elasticity. Outliers were defined as measured values outside the margins of the target elasticity. Precision was assessed by calculating the reproducibility of measurements using the within-subject coefficient of variation (wCV). Results: Mean measurement errors and the proportions of outliers were higher for high than for low target elasticities (p<0.001), but did not differ in relation to acquisition depth, either within an elastography system or across the different systems. Logistic regression analysis showed that target elasticity (p<0.001) significantly affected accuracy, whereas acquisition depth (p>0.05) did not. The wCV for the 80±12 kPa target (31.33%) was significantly higher than that for lower elasticity targets (6.96–10.43 kPa; p<0.001). The wCV did not differ across acquisition depths. The individual elastography systems showed consistent results. Conclusions: Targets with high elasticity showed lower accuracy and lower precision than targets with low elasticity, while acquisition depth did not show consistent patterns in either accuracy or precision. [ABSTRACT FROM AUTHOR]

Background: Persons with dementia have twice the acute hospital use as older persons without dementia. In addition to straining overburdened healthcare systems, acute hospital use impacts patient and caregiver quality of life and is associated with increased risk of adverse outcomes including death. Reducing avoidable acute hospital use in persons with dementia is thus a global healthcare priority. However, evidence regarding the impact of health service interventions as defined by the Effective Practice and Organization of Care Cochrane Group on acute hospital use is scant and inconclusive. The aim of this systematic review and meta-analysis was to synthesize available evidence on the impact of health service interventions on acute hospital use in community-dwelling persons with dementia compared to usual care. Methods: Data Sources: MEDLINE, EMBASE, CINAHL and Cochrane CENTRAL (from 01/1995 to 08/2017). Study eligibility criteria: Randomised controlled trials measuring the impact of health service interventions on acute hospital use (proportion and mean number of emergency department visits and hospitalisations, mean number of hospital days, measured at 12 months, and at longest follow-up) in community-dwelling persons with dementia, compared to usual care. Study selection, appraisal and synthesis methods: Reviewers independently identified studies, extracted data, and assessed the risk of bias, with the Cochrane risk of bias tool. Authors of relevant trials were queried about unpublished data. Random effects model was used for meta-analyses. Effect heterogeneity was assessed through prediction intervals, and explored using sub-group analyses. Findings: Seventeen trials provided data on 4,549 persons. Unpublished data were obtained for 13 trials, representing 65% of synthesized data. Most interventions included a case management or a self-management component. None of the outcome comparisons provided conclusive evidence supporting the hypothesis that these interventions would lead to a decrease in acute hospital use. Furthermore, prediction intervals indicated possible and important increased service use associated with these interventions, such as emergency department visits, hospital admissions, and hospital days. Subgroup analyses did not favour any type of intervention. A limitation of this study is the inclusion of any type of health service intervention, which may have increased the observed heterogeneity. Conclusion: Despite a comprehensive systematic review and meta-analysis, including predominantly unpublished data, no health service intervention beyond usual care was found to reduce acute hospital use in community-dwelling persons with dementia. An important increase in service use may be associated with these interventions. Further research is urgently needed to identify effective interventions for this vulnerable population to limit rising acute hospital use, associated costs and adverse outcomes. Systematic review registration PROSPERO CRD42016046444. [ABSTRACT FROM AUTHOR]

Objective: Assessing the epidemiological association between herpes simplex virus type 1 (HSV-1) and type 2 (HSV-2) infections in the United States, and characterizing the trends in the standardized HSV-1 and HSV-2 antibody prevalences (seroprevalences), 1999–2016. Methods: Source of data was the cross-sectional and nationally-representative biennial surveys of the National Health and Nutrition Examination Survey (NHANES). All nine NHANES rounds for 1999–2016 were included in analysis. Datasets of these rounds were combined and analyzed accounting for survey design and applying weighting procedures. Logistic regressions were used to identify associations with seropositivity. Sensitivity analyses were conducted. Results: Odds of HSV-1 infection declined by 2.84% (95% CI: 1.70%-4.00%) annually among men, and by 2.22% (95% CI: 1.23%-3.21%) among women. Declines were highest at younger ages. Odds of HSV-2 infection declined by 2.23% (95% CI: 0.71%-3.82%) annually among men, and by 2.89% (95% CI: 1.57%-4.28%) among women. Odds ratio of the association between HSV-2 and HSV-1 seropositivity was 0.71 (95% CI: 0.60–0.84) for men and 0.81 (95% CI: 0.72–0.91) for women, after adjustment for age, ethnicity, and year. Conclusion: HSV-1 and HSV-2 seroprevalences showed a strong declining trend for at least two decades, for both sexes and for the different ethnicities, possibly reflecting improvements in hygiene and living conditions (for HSV-1), and safer sexual behavior (for HSV-2). HSV-1 seroprevalence declines are most pronounced among young individuals. There is evidence for cross protection between the two infections, suggestive of HSV-1 seropositivity being partially protective against HSV-2 infection. [ABSTRACT FROM AUTHOR]

Background: Foliar fungicide applications to corn (Zea mays L.) occur at one or more application timings ranging from early vegetative growth stages to mid-reproductive stages. Previous studies indicated that fungicide applications are profitable under high disease pressure when applied during the tasseling to silking growth stages. Few comprehensive studies in corn have examined the impact of fungicide applications at an early vegetative growth stage (V6) compared to late application timings (VT) for yield response and return on fungicide investment (ROI) across multiple locations. Objective: Compare yield response of fungicide application timing across multiple fungicide classes and calculate the probability of positive ROI. Methods: Data were collected specifically for this analysis using a uniform protocol conducted in 13 states in the United States and one province in Canada from 2014–2015. Data were subjected to a primary mixed-model analysis of variance. Subsequent univariate meta-analyses, with and without moderator variables, were performed using standard meta-analytic procedures. Follow-up power and prediction analyses were performed to aid interpretation and development of management recommendations. Results: Fungicide application resulted in a range of yield responses from -2,683.0 to 3,230.9 kg/ha relative to the non-treated control, with 68.2% of these responses being positive. Evidence suggests that all three moderator variables tested (application timing, fungicide class, and disease base level), had some effect (α = 0.05) on the absolute difference in yield between fungicide treated and non-treated plots (). Application timing influenced , with V6 + VT and the VT application timings resulting in greater yield responses than the V6 application timing alone. Fungicide formulations that combined demethylation inhibitor and quinone outside inhibitor fungicides significantly increased yield response. Conclusion: Foliar fungicide applications can increase corn grain yield. To ensure the likelihood of a positive ROI, farmers should focus on applications at VT and use fungicides that include a mix of demethylation inhibitor and quinone outside inhibitor active ingredients. [ABSTRACT FROM AUTHOR]

Objectives: Reviews of violence against children in disaster settings focus on armed conflict. Little is understood about natural disasters which has implications in planning humanitarian response. We examined the magnitude and direction of the association between exposure to natural disasters and physical, emotional, and sexual violence against children, and assessed the quality of the evidence. Methods: We searched 15 health and social science databases from first record until May 16, 2018. Publications describing all types of quantitative study design were eligible for inclusion. We presented study characteristics and quality in a narrative form and generated pooled estimates using a three-level random effects model. We evaluated Cochrane’s Q with p-values below 0.10 and radial plots to assess heterogeneity. Planned subgroup analyses explored differential results by violence form, study design, and analysis method. Results: 11 publications met inclusion criteria. The majority were cross-sectional studies examining physical or sexual violence in the United States. We found no evidence of a consistent association or directional influence between natural disasters and violence against children. Combined categorical violence outcomes had substantial heterogeneity [Q (df = 66) = 252.83, p < 0.001]. Subgroups without evidence of heterogeneity had confidence intervals that included a possible null effect. Our findings were mainly limited by inconsistencies in operational definitions of violence, a lack of representative sampling, and unclear establishment of temporal order between natural disaster exposure and violence outcomes. Conclusions: Based on the available evidence, we cannot confidently conclude that natural disasters increase the level or severity of violence against children above non-disaster settings, however heterogeneity and study quality hamper our ability to draw firm conclusions. More nuanced and rigorous research is needed to inform practice and policy as natural disasters increasingly affect human populations. [ABSTRACT FROM AUTHOR]

Health planners use forecasts of key metrics associated with influenza-like illness (ILI); near-term weekly incidence, week of season onset, week of peak, and intensity of peak. Here, we describe our participation in a weekly prospective ILI forecasting challenge for the United States for the 2016-17 season and subsequent evaluation of our performance. We implemented a metapopulation model framework with 32 model variants. Variants differed from each other in their assumptions about: the force-of-infection (FOI); use of uninformative priors; the use of discounted historical data for not-yet-observed time points; and the treatment of regions as either independent or coupled. Individual model variants were chosen subjectively as the basis for our weekly forecasts; however, a subset of coupled models were only available part way through the season. Most frequently, during the 2016-17 season, we chose; FOI variants with both school vacations and humidity terms; uninformative priors; the inclusion of discounted historical data for not-yet-observed time points; and coupled regions (when available). Our near-term weekly forecasts substantially over-estimated incidence early in the season when coupled models were not available. However, our forecast accuracy improved in absolute terms and relative to other teams once coupled solutions were available. In retrospective analysis, we found that the 2016-17 season was not typical: on average, coupled models performed better when fit without historically augmented data. Also, we tested a simple ensemble model for the 2016-17 season and found that it underperformed our subjective choice for all forecast targets. In this study, we were able to improve accuracy during a prospective forecasting exercise by coupling dynamics between regions. Although reduction of forecast subjectivity should be a long-term goal, some degree of human intervention is likely to improve forecast accuracy in the medium-term in parallel with the systematic consideration of more sophisticated ensemble approaches. [ABSTRACT FROM AUTHOR]

Rationale: As part of the End TB Strategy, the World Health Organization calls for low-tuberculosis (TB) incidence settings to achieve pre-elimination (<10 cases per million) and elimination (<1 case per million) by 2035 and 2050, respectively. These targets require testing and treatment for latent tuberculosis infection (LTBI). Objectives: To estimate the ability and costs of testing and treatment for LTBI to reach pre-elimination and elimination targets in California. Methods: We created an individual-based epidemic model of TB, calibrated to historical cases. We evaluated the effects of increased testing (QuantiFERON-TB Gold) and treatment (three months of isoniazid and rifapentine). We analyzed four test and treat targeting strategies: (1) individuals with medical risk factors (MRF), (2) non-USB, (3) both non-USB and MRF, and (4) all Californians. For each strategy, we estimated the effects of increasing test and treat by a factor of 2, 4, or 10 from the base case. We estimated the number of TB cases occurring and prevented, and net and incremental costs from 2017 to 2065 in 2015 U.S. dollars. Efficacy, costs, adverse events, and treatment dropout were estimated from published data. We estimated the cost per case averted and per quality-adjusted life year (QALY) gained. Measurements and main results: In the base case, 106,000 TB cases are predicted to 2065. Pre-elimination was achieved by 2065 in three scenarios: a 10-fold increase in the non-USB and persons with MRF (by 2052), and 4- or 10-fold increase in all Californians (by 2058 and 2035, respectively). TB elimination was not achieved by any intervention scenario. The most aggressive strategy, 10-fold in all Californians, achieved a case rate of 8 (95% UI 4–16) per million by 2050. Of scenarios that reached pre-elimination, the incremental net cost was $20 billion (non-USB and MRF) to $48 billion. These had an incremental cost per QALY of $657,000 to $3.1 million. A more efficient but somewhat less effective single-lifetime test strategy reached as low as $80,000 per QALY. Conclusions: Substantial gains can be made in TB control in coming years by scaling-up current testing and treatment in non-USB and those with medical risks. [ABSTRACT FROM AUTHOR]

Background: Emergency department (ED) crowding is associated with negative health outcomes, patient dissatisfaction, and longer length of stay (LOS). The addition of advanced diagnostic imaging (ADI), namely CT, ultrasound (U/S), and MRI to ED encounter work up is a predictor of longer length of stay. Earlier and improved prediction of patients’ need for advanced imaging may improve overall ED efficiency. The aim of the study was to detect the association between ADI utilization and the structured and unstructured information immediately available during ED triage, and to develop and validate models to predict utilization of ADI during an ED encounter. Methods: We used the United States National Hospital Ambulatory Medical Care Survey data from 2009 to 2014 to examine which sociodemographic and clinical factors immediately available at ED triage were associated with the utilization of CT, U/S, MRI, and multiple ADI during a patient’s ED stay. We used natural language processing (NLP) topic modeling to incorporate free-text reason for visit data available at time of ED triage in addition to other structured patient data to predict the use of ADI using multivariable logistic regression models. Results: Among the 139,150 adult ED visits from a national probability sample of hospitals across the U.S, 21.9% resulted in ADI use, including 16.8% who had a CT, 3.6% who had an ultrasound, 0.4% who had an MRI, and 1.2% of the population who had multiple types of ADI. The c-statistic of the predictive models was greater than or equal to 0.78 for all imaging outcomes, and the addition of text-based reason for visit information improved the accuracy of all predictive models. Conclusions: Patient information immediately available during ED triage can accurately predict the eventual use of advanced diagnostic imaging during an ED visit. Such models have the potential to be incorporated into the ED triage workflow in order to more rapidly identify patients who may require advanced imaging during their ED stay and assist with medical decision-making. [ABSTRACT FROM AUTHOR]

Diabetes, a chronic disease affecting over 29 million people in the United States, requires the integration of complex medical tasks into a person’s daily life. Patient-centered care and compassion are recognized as essential dimensions of the quality care experience. This research examined provider attributes that influence adherence to type 2 diabetes mellitus (T2DM) regimens and sought to understand the phenomena of provider attributes, treatment adherence, and their relationship to coping ability and treatment outcomes. This quantitative study sampled 474 people with T2DM using a 62-item online survey administered to three different groups. The sample population included people over age 18 diagnosed with T2DM. The first group included 91 persons with T2DM identified through a Facebook group and personal social media connections, the second group included 120 Amazon Mechanical Turk participants with T2DM, and the third group included 263 respondents from a Qualtrics panel who had T2DM. Results indicated that perceived provider compassion (β = .41, ρ < .001) and optimism (β = .48, ρ < .001) positively affected coping ability. Additionally, full mediation effects for self-management were revealed, with coping ability positively mediating the effect of compassion on self-management and the effects of optimism on self-management. Furthermore, full mediation effects were found for treatment satisfaction, with coping ability positively mediating the effect of compassion on treatment satisfaction and the effects of optimism on treatment satisfaction. This research has implications for patients, healthcare professionals, and leaders suggesting that providers who communicate with optimism and compassion positively affect coping ability. As a result, healthcare providers and professionals have an opportunity to enhance self-management adherence by helping their patients cope with the burdens of diabetes. In addition, this study has implications for developing provider communication tools aimed at assessing patients’ coping capacity and increasing compassionate communication. [ABSTRACT FROM AUTHOR]

The ability to produce timely and accurate flu forecasts in the United States can significantly impact public health. Augmenting forecasts with internet data has shown promise for improving forecast accuracy and timeliness in controlled settings, but results in practice are less convincing, as models augmented with internet data have not consistently outperformed models without internet data. In this paper, we perform a controlled experiment, taking into account data backfill, to improve clarity on the benefits and limitations of augmenting an already good flu forecasting model with internet-based nowcasts. Our results show that a good flu forecasting model can benefit from the augmentation of internet-based nowcasts in practice for all considered public health-relevant forecasting targets. The degree of forecast improvement due to nowcasting, however, is uneven across forecasting targets, with short-term forecasting targets seeing the largest improvements and seasonal targets such as the peak timing and intensity seeing relatively marginal improvements. The uneven forecasting improvements across targets hold even when “perfect” nowcasts are used. These findings suggest that further improvements to flu forecasting, particularly seasonal targets, will need to derive from other, non-nowcasting approaches. [ABSTRACT FROM AUTHOR]

Reports of emotions experienced over the past week can be influenced by memory bias, which is more pronounced for people with depression. No studies, however, have examined memory bias for specific emotion clusters (e.g., sadness, anxiety, and anger) experienced on a day-to-day basis among people with depression or a history of depression. Participants (N = 1,657) from the Midlife in the United States Study were assessed for depression. Approximately 6 months later, participants reported their emotional experiences for 8 days and recalled these experiences on the final day. Differences in recalled and reported emotion were compared between participants with and without a history of depression. Participants overestimated experience only of negative emotions, particularly anger, and this negativity bias was greatest for participants with a history of depression. Feelings related to anger were prone to greater overestimation than sadness or anxiety. These findings emphasize the role of memory bias in retrospective reports of specific emotions and illustrate the presence of an amplified memory bias among people who are at a greater risk for recurrent depressive episodes. [ABSTRACT FROM AUTHOR]

Background: No prior study to our knowledge has examined the joint contribution of a polygenic risk score (PRS), mammographic density (MD), and postmenopausal endogenous hormone levels-all well-confirmed risk factors for invasive breast cancer-to existing breast cancer risk prediction models.Methods and Findings: We conducted a nested case-control study within the prospective Nurses' Health Study and Nurses' Health Study II including 4,006 cases and 7,874 controls ages 34-70 years up to 1 June 2010. We added a breast cancer PRS using 67 single nucleotide polymorphisms, MD, and circulating testosterone, estrone sulfate, and prolactin levels to existing risk models. We calculated area under the curve (AUC), controlling for age and stratified by menopausal status, for the 5-year absolute risk of invasive breast cancer. We estimated the population distribution of 5-year predicted risks for models with and without biomarkers. For the Gail model, the AUC improved (p-values < 0.001) from 55.9 to 64.1 (8.2 units) in premenopausal women (Gail + PRS + MD), from 55.5 to 66.0 (10.5 units) in postmenopausal women not using hormone therapy (HT) (Gail + PRS + MD + all hormones), and from 58.0 to 64.9 (6.9 units) in postmenopausal women using HT (Gail + PRS + MD + prolactin). For the Rosner-Colditz model, the corresponding AUCs improved (p-values < 0.001) by 5.7, 6.2, and 6.5 units. For estrogen-receptor-positive tumors, among postmenopausal women not using HT, the AUCs improved (p-values < 0.001) by 14.3 units for the Gail model and 7.3 units for the Rosner-Colditz model. Additionally, the percentage of 50-year-old women predicted to be at more than twice 5-year average risk (≥2.27%) was 0.2% for the Gail model alone and 6.6% for the Gail + PRS + MD + all hormones model. Limitations of our study included the limited racial/ethnic diversity of our cohort, and that general population exposure distributions were unavailable for some risk factors.Conclusions: In this study, the addition of PRS, MD, and endogenous hormones substantially improved existing breast cancer risk prediction models. Further studies will be needed to confirm these findings and to determine whether improved risk prediction models have practical value in identifying women at higher risk who would most benefit from chemoprevention, screening, and other risk-reducing strategies. [ABSTRACT FROM AUTHOR]

Background: The Cardiac Arrest Survival Postresuscitation In-hospital (CASPRI) score is a useful tool for predicting neurological outcome following in-hospital cardiac arrest (IHCA), and was derived from a cohort selected from the Get With The Guidelines-Resuscitation registry between 2000 and 2009 in the United States. In an East Asian population, we aimed to identify the factors associated with outcomes of resuscitated IHCA patients and assess the validity of the CASPRI score. Methods: A retrospective study was conducted in a single centre in Taiwan. Patients with IHCA between 2006 and 2014 were screened. Results: Among the 796 included patients, 94 (11.8%) patients achieved neurologically intact survival. Multivariable logistic regression analyses identified factors significantly associated with neurological outcome. Six of these factors were also components of the CASPRI score, including duration of resuscitation, neurological status before IHCA, malignant disease, initial arrest rhythms, renal insufficiency and age. In univariate logistic regression analysis, the CASPRI score was significantly associated with neurological outcome (odds ratio [OR]: 0.83, 95% confidence interval [CI]: 0.80–0.87); the area under the receiver operating characteristics curve was 0.79 (95% CI: 0.74–0.84). Conclusion: In this retrospective study conducted in a single centre at Taiwan, we identified the common prognosticators of IHCA shared by both East Asian and Western societies. As a composite prognosticator, CASPRI score predicts outcomes with excellent accuracy among successfully resuscitated IHCA patients in an East Asian population. This tool allows accurate IHCA prognostication in an East Asian population. [ABSTRACT FROM AUTHOR]

Introduction: Early diagnosis of cutaneous melanoma is critical in preventing melanoma-associated deaths, but the role of primary care providers (PCPs) in diagnosing melanoma is underexplored. We aimed to explore the association of PCP density with melanoma incidence and mortality. Methods: All cases of cutaneous melanoma diagnosed in the United States from 2008–2012 and reported in the Surveillance, Epidemiology, and End Results (SEER) database were analyzed in 2016. County-level primary care physician density was obtained from the Area Health Resources File (AHRF). We conducted multivariate linear regression using 1) average annual melanoma incidence or 2) average annual melanoma mortality by county as primary outcomes, adjusting for demographic confounders and dermatologist density. Cox proportional hazard regression was conducted using individual outcome data from SEER with the same covariates. Results: Across 611 counties, 167,305 cases of melanoma were analyzed. Per 100,000 people, an additional 10 PCPs per county was associated with 1.62 additional cases of melanoma per year (95% CI 1.06–2.18, p<0.001). This increased incidence occurred disproportionally in early-stage melanoma (Stage 0: 0.69 cases (0.38–1.00), p<0.001; Stage I: 0.63 cases (0.37–0.89), p<0.001; Stage II: 0.11 cases (0.03–0.19), p = 0.005). There was no statistically significant association between PCP density and incidence of stage III or IV melanoma, or with melanoma-specific mortality. Survival analysis demonstrated elimination of 5-year post-diagnosis mortality risk in medically underserved counties after adjusting for stage. Conclusions: Higher densities of PCPs may be linked to increased diagnosis of early-stage melanoma without corresponding decreases in late-stage diagnoses or melanoma-associated mortality. [ABSTRACT FROM AUTHOR]

For patients with chronic lower respiratory disease, hypobaric hypoxia at a high altitude is considered a risk factor for mortality. However, the effects of residing at moderately high altitudes remain unclear. We investigated the association between moderate altitude and chronic lower respiratory disease mortality. In particular, we examined the lower 48 United States counties for age-adjusted chronic lower respiratory disease mortality rates, altitude, and socioeconomic factors, including tobacco use, per capita income, population density, sex ratio, unemployment, poverty, and education between 1979 and 1998. The socioeconomic factors were incorporated into the correlation analysis as potential covariates. Considerable positive (R = 0.235; P <0.001) and partial (R = 0.260; P <0.001) correlations were observed between altitude and chronic lower respiratory disease mortality rate. In the subgroup with high COPD prevalence subgroup, even stronger positive (R = 0.346; P <0.001) and partial (R = 0.423, P <0.001) correlations were observed. Multivariate regression analysis of all available socioeconomic factors revealed that additional knowledge on altitude improved the adjusted R2 values from 0.128 to 0.186 for all counties and from 0.301 to 0.421 for counties with high COPD prevalence. We concluded that in the lower 48 United States counties, even a moderate altitude may pose considerable risks in patients with chronic lower respiratory disease. [ABSTRACT FROM AUTHOR]

Background: Promising school policies to improve children’s diets include providing fresh fruits and vegetables (F&V) and competitive food restrictions on sugar-sweetened beverages (SSBs), yet the impact of national implementation of these policies in US schools on cardiometabolic disease (CMD) risk factors and outcomes is not known. Our objective was to estimate the impact of national implementation of F&V provision and SSB restriction in US elementary, middle, and high schools on dietary intake and body mass index (BMI) in children and future CMD mortality. Methods: We used comparative risk assessment (CRA) frameworks to model the impacts of these policies with input parameters from nationally representative surveys, randomized-controlled trials, and systematic reviews and meta-analyses. For children ages 5–18 years, this incorporated national data on current dietary intakes and BMI, impacts of these policies on diet, and estimated effects of dietary changes on BMI. In adults ages 25 and older, we further incorporated the sustainability of dietary changes to adulthood, effects of dietary changes on CMD, and national CMD death statistics, modeling effects if these policies had been in place when current US adults were children. Uncertainty across inputs was incorporated using 1000 Monte Carlo simulations. Results: National F&V provision would increase daily fruit intake in children by as much as 25.0% (95% uncertainty interval (UI): 15.4, 37.7%), and would have small effects on vegetable intake. SSB restriction would decrease daily SSB intake by as much as 26.5% (95% UI: 6.4, 46.4%), and reduce BMI by as much as 0.7% (95% UI: 0.2, 1.2%). If F&V provision and SSB restriction were nationally implemented, an estimated 22,383 CMD deaths/year (95% UI: 18735, 25930) would be averted. Conclusion: National school F&V provision and SSB restriction policies implemented in elementary, middle, and high schools could improve diet and BMI in children and reduce CMD mortality later in life. [ABSTRACT FROM AUTHOR]

Background: Nonalcoholic fatty liver disease (NAFLD) has been reported to have a negative effect on bone mineral density (BMD) in Asian populations. Whether such an association exists in Western populations is less clear. Methods: This cross-sectional analysis of data from NHANES III, a United States national health survey conducted from 1988 to 1994, included 6089 participants aged 40–75 years, selected after excluding people with hepatitis virus serology, elevated alcohol consumption, decreased renal function, or steroid use, and pregnant females. The main outcome, BMD at the femoral neck, was measured using dual-energy X-ray absorptiometry. The primary exposure, NAFLD, was defined as moderate or severe hepatic steatosis diagnosed using abdominal ultrasonography. Result: After controlling for gender and menopausal status, race/ethnicity, age and body mass index, NAFLD was not significantly associated with BMD (beta coefficient: −0.006, 95%CI: −0.016, 0.003). A secondary analysis categorized participants with NAFLD according to their serum alanine aminotransferase (ALT) levels into high and normal ALT NAFLD groups, and compared these with the non-NAFLD group. NAFLD with higher levels of ALT was associated with lower levels of BMD (beta coefficient: −0.023, 95% CI: −0.044, −0.002). Conclusion: This study showed a relationship between NAFLD with high ALT and lower BMD in the general U.S. population. [ABSTRACT FROM AUTHOR]

Background: Risk prediction is crucial in many areas of medical practice, such as cardiac transplantation, but existing clinical risk-scoring methods have suboptimal performance. We develop a novel risk prediction algorithm and test its performance on the database of all patients who were registered for cardiac transplantation in the United States during 1985-2015. Methods and findings: We develop a new, interpretable, methodology (ToPs: Trees of Predictors) built on the principle that specific predictive (survival) models should be used for specific clusters within the patient population. ToPs discovers these specific clusters and the specific predictive model that performs best for each cluster. In comparison with existing clinical risk scoring methods and state-of-the-art machine learning methods, our method provides significant improvements in survival predictions, both post- and pre-cardiac transplantation. For instance: in terms of 3-month survival post-transplantation, our method achieves AUC of 0.660; the best clinical risk scoring method (RSS) achieves 0.587. In terms of 3-year survival/mortality predictions post-transplantation (in comparison to RSS), holding specificity at 80.0%, our algorithm correctly predicts survival for 2,442 (14.0%) more patients (of 17,441 who actually survived); holding sensitivity at 80.0%, our algorithm correctly predicts mortality for 694 (13.0%) more patients (of 5,339 who did not survive). ToPs achieves similar improvements for other time horizons and for predictions pre-transplantation. ToPs discovers the most relevant features (covariates), uses available features to best advantage, and can adapt to changes in clinical practice. Conclusions: We show that, in comparison with existing clinical risk-scoring methods and other machine learning methods, ToPs significantly improves survival predictions both post- and pre-cardiac transplantation. ToPs provides a more accurate, personalized approach to survival prediction that can benefit patients, clinicians, and policymakers in making clinical decisions and setting clinical policy. Because survival prediction is widely used in clinical decision-making across diseases and clinical specialties, the implications of our methods are far-reaching. [ABSTRACT FROM AUTHOR]

Investigating suicides following the death of Robin Williams, a beloved actor and comedian, on August 11th, 2014, we used time-series analysis to estimate the expected number of suicides during the months following Williams’ death. Monthly suicide count data in the US (1999–2015) were from the Centers for Disease Control and Prevention Wide-ranging ONline Data for Epidemiologic Research (CDC WONDER). Expected suicides were calculated using a seasonal autoregressive integrated moving averages model to account for both the seasonal patterns and autoregression. Time-series models indicated that we would expect 16,849 suicides from August to December 2014; however, we observed 18,690 suicides in that period, suggesting an excess of 1,841 cases (9.85% increase). Although excess suicides were observed across gender and age groups, males and persons aged 30–44 had the greatest increase in excess suicide events. This study documents associations between Robin Williams’ death and suicide deaths in the population thereafter. [ABSTRACT FROM AUTHOR]

Men outperform women in many athletic endeavors due to physiological and anatomical differences (e.g. larger and faster muscle); however, the observed sex differences in elite athletic performance are typically larger than expected, and may reflect sex-related differences in opportunity or incentives. As collegiate rowing in the United States has been largely incentivized for women over the last 20 years, but not men, the purpose of this study was to examine sex differences in elite rowing performance over that timeframe. Finishing times from grand finale races for collegiate championship on-water performances (n = 480) and junior indoor performances (n = 1,280) were compared between men and women across 20 years (1997–2016), weight classes (heavy vs. lightweight) and finishing place. Participation of the numbers of men and women rowers were also quantified across years. Men were faster than women across all finishing places, weight classes and years of competition and performance declined across finishing place for both men and women (P<0.001). Interestingly, the reduction in performance time across finishing place was greater (P<0.001) for collegiate men compared to women in the heavyweight division. This result is opposite to other sports (e.g. running and swimming), and to lightweight rowing in this study, which provides women fewer incentives than in heavyweight rowing. Correspondingly, participation in collegiate rowing has increased by ~113 women per year (P<0.001), with no change (P = 0.899) for collegiate men. These results indicate that increased participation and incentives within collegiate rowing for women vs. men contribute to sex differences in athletic performance. [ABSTRACT FROM AUTHOR]

Objectives: As gentrification continues in New York City as well as other urban areas, residents of lower socioeconomic status maybe at higher risk for residential displacement. Yet, there have been few quantitative assessments of the health impacts of displacement. The objective of this paper is to assess the association between displacement and healthcare access and mental health among the original residents of gentrifying neighborhoods in New York City. Methods: We used 2 data sources: 1) 2005–2014 American Community Surveys to identify gentrifying neighborhoods in New York City, and 2) 2006–2014 Statewide Planning and Research Cooperative System. Our cohort included 12,882 residents of gentrifying neighborhoods in 2006 who had records of emergency department visits or hospitalization at least once every 2 years in 2006–2014. Rates of emergency department visits and hospitalizations post-baseline were compared between residents who were displaced and those who remained. Results: During 2006–2014, 23% were displaced. Compared with those who remained, displaced residents were more likely to make emergency department visits and experience hospitalizations, mainly due to mental health (Rate Ratio = 1.8, 95% confidence interval = 1.5, 2.2), after controlling for baseline demographics, health status, healthcare utilization, residential movement, and the neighborhood of residence in 2006. Conclusions: These findings suggest negative impacts of displacement on healthcare access and mental health, particularly among adults living in urban areas and with a history of frequent emergency department visits or hospitalizations. [ABSTRACT FROM AUTHOR]

Recent research has produced a number of methods for forecasting seasonal influenza outbreaks. However, differences among the predicted outcomes of competing forecast methods can limit their use in decision-making. Here, we present a method for reconciling these differences using Bayesian model averaging. We generated retrospective forecasts of peak timing, peak incidence, and total incidence for seasonal influenza outbreaks in 48 states and 95 cities using 21 distinct forecast methods, and combined these individual forecasts to create weighted-average superensemble forecasts. We compared the relative performance of these individual and superensemble forecast methods by geographic location, timing of forecast, and influenza season. We find that, overall, the superensemble forecasts are more accurate than any individual forecast method and less prone to producing a poor forecast. Furthermore, we find that these advantages increase when the superensemble weights are stratified according to the characteristics of the forecast or geographic location. These findings indicate that different competing influenza prediction systems can be combined into a single more accurate forecast product for operational delivery in real time. [ABSTRACT FROM AUTHOR]

Obesity is a disease that has reached epidemic proportions in the United States and has prompted international legislation in an attempt to curtail its prevalence. Despite the fact that one of the most prescribed treatment options for obesity is exercise, the genetic mechanisms underlying exercise response in individuals are still largely unknown. The fruit fly Drosophila melanogaster is a promising new model for studying exercise genetics. Currently, the lack of an accurate method to quantify the amount of exercise performed by the animals is limiting the utility of the Drosophila model for exercise genetics research. To address this limitation, we developed the Rotational Exercise Quantification System (REQS), a novel apparatus that is able to simultaneously induce exercise in flies while recording their activity levels. Thus, the REQS provides a method to standardize Drosophila exercise and ensure that all animals irrespective of genotype and sex experience the same level of exercise. Here, we provide a basic characterization of the REQS, validate its measurements using video-tracking technology, illustrate its potential use by presenting a comparison of two different exercise regimes, and demonstrate that it can be used to detect genotype-dependent variation in activity levels. [ABSTRACT FROM AUTHOR]

While factors such as genetics may mediate the relationship between height and mortality, evidence suggests that larger body size may be an important risk indicator of reduced lifespan longevity in particular. This study critically examined this relationship in professional basketball players. We examined living and deceased players who have played in the National Basketball Association (debut between 1946–2010) and/or the American Basketball Association (1967–1976) using descriptive and Kaplan-Meier and Cox regression analyses. The cut-off date for death data collection was December 11, 2015. Overall, 3,901 living and deceased players were identified and had a mean height of 197.78 cm (± 9.29, Range: 160.02–231.14), and of those, 787 former players were identified as deceased with a mean height of 193.88 cm (± 8.83, Range: 167.6–228.6). Descriptive findings indicated that the tallest players (top 5%) died younger than the shortest players (bottom 5%) in all but one birth decade (1941–1950). Similarly, survival analyses showed a significant relationship between height and lifespan longevity when both dichotomizing [χ2 (1) = 13.04, p < .05] and trichotomizing [χ2 (2) = 18.05, p < .05] the predictor variable height per birth decade, where taller players had a significantly higher mortality risk compared to shorter players through median (HR: 1.30, 95% CI: 1.13–1.50, p < .05) and trichotomized tertile split (HR: 1.40, 95% CI: 1.18–1.68, p <. 05; tallest 33.3% compared to shortest 33.3%) analyses. The uniqueness of examining the height-longevity hypothesis in this relatively homogeneous sub-population should be considered when interpreting these results. Further understanding of the potential risks of early mortality can help generate discourse regarding potential at-risk cohorts of the athlete population. [ABSTRACT FROM AUTHOR]

Background: Despite significant public health implications, the extent to which community-based condom distribution interventions (CDI) prevent HIV infection in the United States is not well understood. Methods: We systematically reviewed research evidence applying Cochrane Collaboration methods. We used a comprehensive search strategy to search multiple bibliographic databases for relevant randomized controlled trials (RCTs) and non-RCTs published from 1986–2017. We focused on CDI that made condoms widely available or accessible in community settings. Eligible outcomes were HIV infection (primary), sexually transmitted infections, condom use, and multiple sexual partnership. Two reviewers independently screened citations to assess their eligibility, extracted study data, and assessed risk of bias. We calculated risk ratios (RR) with 95% confidence intervals (CI) and pooled them using random-effects models. We assessed evidence quality using GRADE. Results: We reviewed 5,110 unique records. Nine studies (including one RCT) met eligibility criteria. Studies were conducted in 10 US states between 1989 and 2011. All studies were at high risk of bias. Interventions were categorized into three groups: “Ongoing” (unlimited access to condoms), “Ongoing-plus” (unlimited access to condoms, with co-interventions), and “Coupon-based” (coupons redeemed for condoms). No studies reported incident HIV. Ongoing CDI (four non-RCTs) modestly reduced condomless sex (RR 0.88, 95% CI 0.78 to 0.99). Ongoing-plus CDI (two non-RCTs) significantly reduced multiple sexual partnership (RR 0.37, 95% CI 0.16 to 0.87). Of two coupon-based studies, one (non-RCT) showed reduction in condomless sex in female participants (Odds Ratio 0.67, 95% CI 0.47 to 0.96), while the other one (RCT) showed no effect on STI incidence (RR 0.91, 95% CI 0.63 to 1.31). Evidence quality was “very low” for all outcomes. Conclusions: CDI may reduce some risky sexual behaviors, but the evidence for any reduction is limited and of low-quality. Lack of biological outcomes precludes assessing the link between CDI and HIV incidence. [ABSTRACT FROM AUTHOR]

This paper forecasts the 2016 canine Anaplasma spp. seroprevalence in the United States from eight climate, geographic and societal factors. The forecast’s construction and an assessment of its performance are described. The forecast is based on a spatial-temporal conditional autoregressive model fitted to over 11 million Anaplasma spp. seroprevalence test results for dogs conducted in the 48 contiguous United States during 2011–2015. The forecast uses county-level data on eight predictive factors, including annual temperature, precipitation, relative humidity, county elevation, forestation coverage, surface water coverage, population density and median household income. Non-static factors are extrapolated into the forthcoming year with various statistical methods. The fitted model and factor extrapolations are used to estimate next year’s regional prevalence. The correlation between the observed and model-estimated county-by-county Anaplasma spp. seroprevalence for the five-year period 2011–2015 is 0.902, demonstrating reasonable model accuracy. The weighted correlation (accounting for different sample sizes) between 2015 observed and forecasted county-by-county Anaplasma spp. seroprevalence is 0.987, exhibiting that the proposed approach can be used to accurately forecast Anaplasma spp. seroprevalence. The forecast presented herein can a priori alert veterinarians to areas expected to see Anaplasma spp. seroprevalence beyond the accepted endemic range. The proposed methods may prove useful for forecasting other diseases. [ABSTRACT FROM AUTHOR]

Background: With the onset of prevention trials for individuals at high risk for Alzheimer disease, there is increasing need for accurate risk prediction to inform study design and enrollment, but available risk estimates are limited. We developed risk estimates for the incidence of mild cognitive impairment (MCI) or dementia among cognitively unimpaired individuals by APOE-e4 dose for the genetic disclosure process of the Alzheimer's Prevention Initiative Generation Study, a prevention trial in cognitively unimpaired APOE-e4/e4 homozygote individuals.Methods and Findings: We included cognitively unimpaired individuals aged 60-75 y, consistent with Generation Study eligibility criteria, from the National Alzheimer's Coordinating Center (NACC) (n = 5,073, 158 APOE-e4/e4), the Rotterdam Study (n = 6,399, 156 APOE-e4/e4), the Framingham Heart Study (n = 4,078, 67 APOE-e4/e4), and the Sacramento Area Latino Study on Aging (SALSA) (n = 1,294, 11 APOE-e4/e4). We computed stratified cumulative incidence curves by age (60-64, 65-69, 70-75 y) and APOE-e4 dose, adjusting for the competing risk of mortality, and determined risk of MCI and/or dementia by genotype and baseline age. We also used subdistribution hazard regression to model relative hazard based on age, APOE genotype, sex, education, family history of dementia, vascular risk, subjective memory concerns, and baseline cognitive performance. The four cohorts varied considerably in age, education, ethnicity/race, and APOE-e4 allele frequency. Overall, cumulative incidence was uniformly higher in NACC than in the population-based cohorts. Among APOE-e4/e4 individuals, 5-y cumulative incidence was as follows: in the 60-64-y age stratum, it ranged from 0% to 5.88% in the three population-based cohorts versus 23.06% in NACC; in the 65-69-y age stratum, from 9.42% to 10.39% versus 34.62%; and in the 70-75-y age stratum, from 18.64% to 33.33% versus 38.34%. Five-year incidence of dementia was negligible except for APOE-e4/e4 individuals and those over 70 y. Lifetime incidence (to age 80-85 y) of MCI or dementia for the APOE-e4/e4 individuals in the long-term Framingham and Rotterdam cohorts was 34.69%-38.45% at age 60-64 y, 30.76%-40.26% at 65-69 y, and 33.3%-35.17% at 70-75 y. Confidence limits for these estimates are often wide, particularly for APOE-e4/e4 individuals and for the dementia outcome at 5 y. In regression models, APOE-e4 dose and age both consistently increased risk, as did lower education, subjective memory concerns, poorer baseline cognitive performance, and family history of dementia. We discuss several limitations of the study, including the small numbers of APOE-e4/e4 individuals, missing data and differential dropout, limited ethnic and racial diversity, and differences in definitions of exposure and outcome variables.Conclusions: Estimates of the absolute risk of MCI or dementia, particularly over short time intervals, are sensitive to sampling and a variety of methodological factors. Nonetheless, such estimates were fairly consistent across the population-based cohorts, and lower than those from a convenience cohort and those estimated in prior studies-with implications for informed consent and design for clinical trials targeting high-risk individuals. [ABSTRACT FROM AUTHOR]

Managed reef fish in the Atlantic Ocean of the southeastern United States (SEUS) support a multi-billion dollar industry. There is a broad interest in locating and protecting spawning fish from harvest, to enhance productivity and reduce the potential for overfishing. We assessed spatiotemporal cues for spawning for six species from four reef fish families, using data on individual spawning condition collected by over three decades of regional fishery-independent reef fish surveys, combined with a series of predictors derived from bathymetric features. We quantified the size of spawning areas used by reef fish across many years and identified several multispecies spawning locations. We quantitatively identified cues for peak spawning and generated predictive maps for Gray Triggerfish (Balistes capriscus), White Grunt (Haemulon plumierii), Red Snapper (Lutjanus campechanus), Vermilion Snapper (Rhomboplites aurorubens), Black Sea Bass (Centropristis striata), and Scamp (Mycteroperca phenax). For example, Red Snapper peak spawning was predicted in 24.7–29.0°C water prior to the new moon at locations with high curvature in the 24–30 m depth range off northeast Florida during June and July. External validation using scientific and fishery-dependent data collections strongly supported the predictive utility of our models. We identified locations where reconfiguration or expansion of existing marine protected areas would protect spawning reef fish. We recommend increased sampling off southern Florida (south of 27° N), during winter months, and in high-relief, high current habitats to improve our understanding of timing and location of reef fish spawning off the southeastern United States. [ABSTRACT FROM AUTHOR]

In the United States (US), cardiovascular (CV) disease accounts for nearly 20% of national health care expenses. Since costs are expected to increase with the aging population, informative research is necessary to address the growing burden of CV disease and sex-related differences in diagnosis, treatment, and outcomes. Hypertension is a major risk factor for CV disease and mortality. To evaluate whether there are sex-related differences in the effect of systolic blood pressure (SBP) on the risk of CV disease and mortality, we performed a systematic review and meta-analysis. We conducted a comprehensive search using PubMed and Google Scholar to identify US-based studies published prior to 31 December, 2015. We identified eight publications for CV disease risk, which provided 9 female and 8 male effect size (ES) observations. We also identified twelve publications for CV mortality, which provided 10 female and 18 male ES estimates. Our meta-analysis estimated that the pooled ES for increased risk of CV disease per 10 mmHg increment in SBP was 25% for women (95% Confidence Interval (CI): 1.18, 1.32) and 15% for men (95% CI: 1.11, 1.19). The pooled increase in CV mortality per 10 mm Hg SBP increment was similar for both women and men (Women: 1.16; 95% CI: 1.10, 1.23; Men: 1.17; 95% CI: 1.12, 1.22). After adjusting for age and baseline SBP, the results demonstrated that the risk of CV disease per 10 mm Hg SBP increment for women was 1.1-fold higher than men (P<0.01; 95% CI: 1.04, 1.17). Heterogeneity was moderate but significant. There was no significant sex difference in CV mortality. [ABSTRACT FROM AUTHOR]

Introduction: Accelerometers are increasingly used in research. Four to 7 days of monitoring is preferred to estimate average activity but may be burdensome for older adults. We aimed to investigate: 1) 7-day accelerometry protocol adherence, 2) demographic predictors of adherence, 3) day of the week effect, and 4) average activity calculated from 7 versus fewer days among older adults. Methods: We used the 2003–2006 older adult hip accelerometry data from the National Health and Nutrition Examination Survey (NHANES) sample. We determined proportions with 1–7 valid (10–20 hours) wear days and identified wear day correlates using ordinal logistic regression. We determined the day of week effect on 5 accelerometry measures (counts per minute, CPM; % sedentary behavior; % light-lifestyle activity; % moderate-vigorous activity, MVPA; total activity counts) using multivariate linear regression and compared averages estimated over 2 or 3 versus 7 days using correlations, linear regression, and Bland-Altman plots. Results: Among 2,208 participants aged 65+, 85% of participants had ≥2 and 44% had 7 valid wear days. Increasing age (p = 0.01) and non-white race (p < 0.001) were associated with fewer days. Daily CPM, % MVPA, and total daily activity counts were similar Monday through Saturday, but significantly lower on Sundays (p < 0.001). Daily % sedentary behavior and % light-lifestyle activity were significantly different on Saturdays (p = 0.04–0.045) and Sundays (p < 0.001) compared to weekdays. Among participants with 7 valid days, 2 or 3 day averages were highly correlated with 7 day averages for all 5 accelerometry measures (2 versus 7 days: r = 0.90–0.93, 3 versus 7 days: r = 0.94–0.96). Conclusions: Protocols of 2–3 days, adjusting for Sundays (average CPM, % moderate-vigorous activity, and average total daily activity counts) or weekends (% sedentary behavior and % light-lifestyle activity), give reliable estimates of older adult activity. [ABSTRACT FROM AUTHOR]

The U.S. is the main country in the world that delivers its food assistance primarily via transoceanic shipments of commodity-based in-kind food. This approach is costlier and less timely than cash-based assistance, which includes cash transfers, food vouchers, and local and regional procurement, where food is bought in or nearby the recipient country. The U.S.’s approach is exacerbated by a requirement that half of its transoceanic food shipments need to be sent on U.S.-flag vessels. We estimate the effect of these U.S. food assistance distribution policies on child mortality in northern Kenya by formulating and optimizing a supply chain model. In our model, monthly orders of transoceanic shipments and cash-based interventions are chosen to minimize child mortality subject to an annual budget constraint and to policy constraints on the allowable proportions of cash-based interventions and non-US-flag shipments. By varying the restrictiveness of these policy constraints, we assess the impact of possible changes in U.S. food aid policies on child mortality. The model includes an existing regression model that uses household survey data and geospatial data to forecast the mean mid-upper-arm circumference Z scores among children in a community, and allows food assistance to increase Z scores, and Z scores to influence mortality rates. We find that cash-based interventions are a much more powerful policy lever than the U.S.-flag vessel requirement: switching to cash-based interventions reduces child mortality from 4.4% to 3.7% (a 16.2% relative reduction) in our model, whereas eliminating the U.S.-flag vessel restriction without increasing the use of cash-based interventions generates a relative reduction in child mortality of only 1.1%. The great majority of the gains achieved by cash-based interventions are due to their reduced cost, not their reduced delivery lead times; i.e., the reduction of shipping expenses allows for more food to be delivered, which reduces child mortality. [ABSTRACT FROM AUTHOR]

Background: Disease-associated malnutrition has been identified as a prevalent condition, particularly for the elderly, which has often been overlooked in the U.S. healthcare system. The state-level burden of community-based disease-associated malnutrition is unknown and there have been limited efforts by state policy makers to identify, quantify, and address malnutrition. The objective of this study was to examine and quantify the state-level economic burden of disease-associated malnutrition. Methods: Direct medical costs of disease-associated malnutrition were calculated for 8 diseases: Stroke, Chronic Obstructive Pulmonary Disease, Coronary Heart Failure, Breast Cancer, Dementia, Musculoskeletal Disorders, Depression, and Colorectal Cancer. National disease and malnutrition prevalence rates were estimated for subgroups defined by age, race, and sex using the National Health and Nutrition Examination Survey and the National Health Interview Survey. State prevalence of disease-associated malnutrition was estimated by combining national prevalence estimates with states’ demographic data from the U.S. Census. Direct medical cost for each state was estimated as the increased expenditures incurred as a result of malnutrition. Principal Findings: Direct medical costs attributable to disease-associated malnutrition vary among states from an annual cost of $36 per capita in Utah to $65 per capita in Washington, D.C. Nationally the annual cost of disease-associated malnutrition is over $15.5 billion. The elderly bear a disproportionate share of this cost on both the state and national level. Conclusions: Additional action is needed to reduce the economic impact of disease-associated malnutrition, particularly at the state level. Nutrition may be a cost-effective way to help address high health care costs. [ABSTRACT FROM AUTHOR]

Background: Policies designed to restrict marketing, access to, and public use of electronic cigarettes (e-cigarettes) are increasingly under debate in various jurisdictions in the US. Little is known about public perceptions of these policies and factors that predict their support or opposition. Methods: Using a sample of US adults from Amazon Mechanical Turk in May 2015, this paper identifies beliefs about the benefits and costs of regulating e-cigarettes and identifies which of these beliefs predict support for e-cigarette restricting policies. Results: A higher proportion of respondents agreed with 8 different reasons to regulate e-cigarettes (48.5% to 83.3% agreement) versus 7 reasons not to regulate e-cigarettes (11.5% to 18.9%). The majority of participants agreed with 7 out of 8 reasons for regulation. When all reasons to regulate or not were included in a final multivariable model, beliefs about protecting people from secondhand vapor and protecting youth from trying e-cigarettes significantly predicted stronger support for e-cigarette restricting policies, whereas concern about government intrusion into individual choices was associated with reduced support. Discussion: This research identifies key beliefs that may underlie public support or opposition to policies designed to regulate the marketing and use of e-cigarettes. Advocates on both sides of the issue may find this research valuable in developing strategic campaigns related to the issue. Implications: Specific beliefs of potential benefits and costs of e-cigarette regulation (protecting youth, preventing exposure to secondhand vapor, and government intrusion into individual choices) may be effectively deployed by policy makers or health advocates in communicating with the public. [ABSTRACT FROM AUTHOR]

The goal of this paper is to estimate peer influence in video gaming time among adolescents. Using a nationally representative sample of the U.S. school-aged adolescents in 2009–2010, we estimate a structural model that accounts for the potential biases in the estimate of the peer effect. Our peer group is exogenously assigned and includes one year older adolescents in the same school grade as the respondent. The peer measure is based on peers’ own reports of video gaming time. We find that an additional one hour of playing video games per week by older grade-mates results in .47 hours increase in video gaming time by male responders. We do not find significant peer effect among female responders. Effective policies aimed at influencing the time that adolescents spend video gaming should take these findings into account. [ABSTRACT FROM AUTHOR]

Adult control of Aedes albopictus via ultra-low volume is difficult because this species occurs primarily in peridomestic habitats where obstacles such as buildings and vegetation can disrupt spray plumes and droplet dispersion. We determined droplet penetration and characterization of a pyrethroid adulticide applied from the ground at mid (46.77 ml/ha) and maximum (93.53 ml/ha) label rates within cryptic habitats of urban and suburban environments. Droplets were collected from all habitats, with no significant differences detected between locations within the same application rate or collection method. No differences were detected in droplet densities (drops per mm2) between rates within urban environments, but more droplets were collected in urban (149.93 ± 11.07 SE) than suburban sites (114.37 ± 11.32) at the maximum label rate (P = 0.003). The excellent penetration of aerosols into cryptic habitats of an urban site was likely due to the shorter spray paths afforded by our network of roads and alleys. Mid label rates displayed similar droplet density values as maximum label rates in urban areas, indicating that lower rates may be used effectively to reduce costs, lessen non-target effects, and increase environmental stewardship. Advances in formulations and technology are driving changes in adulticide applications, leading to use of the minimum effective dose for maximum efficacy, precision, and accountability. [ABSTRACT FROM AUTHOR]

The “fetal origins” hypothesis suggests that fetal conditions not only affect birth characteristics such as birth weight and gestational age, but also have lifelong health implications. Despite widespread interest in this hypothesis, few methodological advances have been proposed to improve the measurement and modeling of fetal conditions. A Statistics in Medicine paper by Bollen, Noble, and Adair examined favorable fetal growth conditions (FFGC) as a latent variable. Their study of Filipino children from Cebu provided evidence consistent with treating FFGC as a latent variable that largely mediates the effects of mother’s characteristics on birth weight, birth length, and gestational age. This innovative method may have widespread utility, but only if the model applies equally well across diverse settings. Our study assesses whether the FFGC model of Cebu replicates and generalizes to a very different population of children from North Carolina (N = 705) and Pennsylvania (N = 494). Using a series of structural equation models, we find that key features of the Cebu analysis replicate and generalize while we also highlight differences between these studies. Our results support treating fetal conditions as a latent variable when researchers test the fetal origins hypothesis. In addition to contributing to the substantive literature on measuring fetal conditions, we also discuss the meaning and challenges involved in replicating prior research. [ABSTRACT FROM AUTHOR]

In this article, we report findings from an original survey experiment investigating the effects of different framings of disease threats on individual risk perceptions and policy priorities. We analyze responses from 1,946 white and African-American participants in a self-administered, web-based survey in the United States. We sought to investigate the effects of: 1) frames emphasizing disparities in the racial prevalence of disease and 2) frames emphasizing non-normative (blameworthy or stigmatized) behavioral risk factors. We find some evidence that when treated with the first frame, African-Americans are more likely to report higher risk of infection (compared to an African-American control group and to whites receiving the same treatment); and that whites are more likely to report trust in government data (compared to a White control group and to African-Americans receiving the same treatment). Notwithstanding, we find no support for our hypotheses concerning the interactive effects of providing both frames, which was a central motivation for our study. We argue that this may be due to very large differences in risk perception at baseline (which generate limits on possible treatment effects) and the fact that in the context of American race relations, it may not be possible to fully differentiate racialized and stigmatized frames. [ABSTRACT FROM AUTHOR]

Despite increased awareness and concern about children with developmental disabilities wandering away from adult supervision, there is a paucity of research about elopement. This is the first study to examine and report the prevalence and correlates of elopement in a nationally representative sample of school-age children in the United States with an autism spectrum disorder (ASD) and/or cognitive impairment. Data were obtained from the CDC's "Pathways" Survey, a follow-up telephone survey of the parents of 4,032 children with a developmental condition. 3,518 children that had ASD, intellectual disability (ID), and/or developmental delay (DD) at the time of survey administration were included for analysis. Children were divided into three condition groups: ASD-only; ID/DD-only; ASD+ID/DD. Logistic regression analyses were used to compare the prevalence of elopement and rates of preventive measure use (barriers and/or electronic devices) across condition groups, and to examine the clinical and demographic correlates of elopement. T-tests were also performed to compare scores on the Children's Social Behavior Questionnaire (CSBQ) between wanderers and non-wanderers. Overall, 26.7% of children had reportedly eloped within the previous year, most commonly from public places. Children with ASD-only and ASD+ID/DD were more likely to have eloped than those with ID/DD-only. Across all groups, wanderers scored higher than non-wanderers on five out of six CSBQ subscales; they were more likely not to realize when there is danger, to have difficulty distinguishing between strangers and familiar people, to show sudden mood changes, to over-react to everything/everyone, to get angry quickly, to get lost easily, and to panic in new situations or if change occurs. Even after controlling for elopement history, parents of children in the ASD+ID/DD group were more likely than those in the other condition groups to report using physical or electronic measures to prevent wandering. [ABSTRACT FROM AUTHOR]

Importance and Objective: Prior influenza infection is a risk factor for invasive meningococcal disease. Quantifying the fraction of meningococcal disease attributable to influenza could improve understanding of viral-bacterial interaction and indicate additional health benefits to influenza immunization. Design, Setting and Participants: A time series analysis of the association of influenza and meningococcal disease using hospitalizations in 9 states from 1989–2009 included in the State Inpatient Databases from the Agency for Healthcare Research and Quality and the proportion of positive influenza tests by subtype reported to the Centers for Disease Control. The model accounts for the autocorrelation of meningococcal disease and influenza between weeks, temporal trends, co-circulating respiratory syncytial virus, and seasonality. The influenza-subtype-attributable fraction was estimated using the model coefficients. We analyzed the synchrony of seasonal peaks in hospitalizations for influenza, respiratory syncytial virus, and meningococcal disease. Results and Conclusions: In 19 of 20 seasons, influenza peaked≤2 weeks before meningococcal disease, and peaks were highly correlated in time (ρ = 0.95; P <.001). H3N2 and H1N1 peaks were highly synchronized with meningococcal disease while pandemic H1N1, B, and respiratory syncytial virus were not. Over 20 years, 12.8% (95% CI, 9.1–15.0) of meningococcal disease can be attributable to influenza in the preceding weeks with H3N2 accounting for 5.2% (95% CI, 3.0–6.5), H1N1 4.3% (95% CI, 2.6–5.6), B 3.0% (95% CI, 0.8–4.9) and pH1N1 0.2% (95% CI, 0–0.4). During the height of influenza season, weekly attributable fractions reach 59%. While vaccination against meningococcal disease is the most important prevention strategy, influenza vaccination could provide further protection, particularly in young children where the meningococcal disease vaccine is not recommended or protective against the most common serogroup. [ABSTRACT FROM AUTHOR]

Background: Little is known about acute hemodialysis in the US. Here we describe predictors of receipt of acute hemodialysis in one state and estimate the marginal impact of acute hemodialysis on survival after accounting for confounding due to illness severity. Materials and Methods: This is a retrospective cohort study of acute-care hospitalizations in Pennsylvania from October 2005 to December 2007 using data from the Pennsylvania Health Care Cost Containment Council. Exposure variable is acute hemodialysis; dependent variable is survival following acute hemodialysis. We used multivariable logistic regression to determine propensity to receive acute hemodialysis and then, for a Cox proportional hazards model, matched acute hemodialysis and non-acute hemodialysis patients 1∶5 on this propensity. Results: In 2,131,248 admissions of adults without end-stage renal disease, there were 6,657 instances of acute hemodialysis. In analyses adjusted for predicted probability of death upon admission plus other covariates and stratified on age, being male, black, and insured were independent predictors of receipt of acute hemodialysis. One-year post-admission mortality was 43% for those receiving acute hemodialysis, compared to 13% among those not receiving acute hemodialysis. After matching on propensity to receive acute hemodialysis and adjusting for predicted probability of death upon admission, patients who received acute hemodialysis had a higher risk of death than patients who did not over at least 1 year of follow-up (hazard ratio 1·82, 95% confidence interval 1·68–1·97). Conclusions: In a populous US state, receipt of acute hemodialysis varied by age, sex, race, and insurance status even after adjustment for illness severity. In a comparison of patients with similar propensity to receive acute hemodialysis, those who did receive it were less likely to survive than those who did not. These findings raise questions about reasons for lack of benefit. [ABSTRACT FROM AUTHOR]

Objective: Reported associations between socioeconomic status (SES) and obesity are inconsistent depending on gender and geographic location. Globally, these inconsistent observations may hide a variation in the contextual effect on individuals' risk of obesity for subgroups of the population. This study explored the regional variability in the association between SES and BMI in the USA and in Canada, and describes the geographical variance patterns by SES category. Methods: The 2009–2010 samples of the Behavioral Risk Factor Surveillance System (BRFSS) and the Canadian Community Health Survey (CCHS) were used for this comparison study. Three-level random intercept and differential variance multilevel models were built separately for women and men to assess region-specific BMI by SES category and their variance bounds. Results: Associations between individual SES and BMI differed importantly by gender and countries. At the regional-level, the mean BMI variation was significantly different between SES categories in the USA, but not in Canada. In the USA, whereas the county-specific mean BMI of higher SES individuals remained close to the mean, its variation grown as SES decreased. At the county level, variation of mean BMI around the regional mean was 5 kg/m2 in the high SES group, and reached 8.8 kg/m2 in the low SES group. Conclusions: This study underlines how BMI varies by country, region, gender and SES. Lower socioeconomic groups within some regions show a much higher variation in BMI than in other regions. Above the BMI regional mean, important variation patterns of BMI by SES and place of residence were found in the USA. No such pattern was found in Canada. This study suggests that a change in the mean does not necessarily reflect the change in the variance. Analyzing the variance by SES may be a good way to detect subtle influences of social forces underlying social inequalities. [ABSTRACT FROM AUTHOR]