Influenza increases the risk of secondary diseases, but other than pneumonia, many of these diseases (e.g., sinusitis, otitis media, acute myocardial infarctions) are not consistently considered in estimates of influenza burden. We used the Merative Marketscan database (2001-2019) and time-series methods to identify age-specific categories of diseases that were temporally associated with patterns of influenza activity. Next, we estimated hypothetical reductions in the incidence and costs of these diseases if influenza incidence were reduced. Of 282 different disease categories evaluated, 23 (8.2%) were strongly associated with influenza (e.g., acute bronchitis, otitis media, myocardial infarctions, sinusitis, COPD) in at least one age group. For example, we estimated a 20% decrease in peak influenza incidence could decrease acute bronchitis cases by 6.5% and pneumonia cases by 5.3%, corresponding to a $1.6 billion reduction in healthcare costs. Excluding secondary diseases associated with influenza may lead to substantial underestimates of influenza's burden and costs.

PURPOSE:Bicyclist injuries are a major public health concern in the United States, with limited understanding of variations in injury severity and discharge outcomes by rurality. This study provides a national assessment of bicycling-related hospitalizations, focusing on differences by rurality. METHODS:Using HCUP-NIS data (2016-2020), bicycling-related hospitalizations were identified. Descriptive analyses characterized demographic and regional trends. Multivariable logistic regression, stratified by rural/urban patient residence, was used to assess factors associated with non-routine discharges. FINDINGS:Between 2016 and 2020, an estimated 124,000 bicyclist-related hospitalizations occurred, resulting in more than $10 billion in hospital costs. Overall, 31.2% resulted in non-routine discharge, including 1.4% deaths. Hospitalizations were stable through 2019 but increased by >20% in 2020. Urban residents accounted for most cases (91.1%). Cases were predominantly male (80%); aged 31-70 (65.4%) and hospitalized in the South (31.2%) or West (36.4%). Increasing age showed a strong dose-response relationship with non-routine discharge in both settings (e.g., age ≥ 71: ORrural = 15.71, 95% confidence interval [CI]: 9.52-25.93; ORurban = 12.18, 95% CI: 10.21-14.52). Motor-vehicle involvement increased the odds of non-routine discharge in both settings (ORrural = 2.53, 95% CI: 1.89-3.40; ORurban = 1.68, 95% CI: 1.55-1.82). CONCLUSIONS:Bicyclist hospitalizations persisted and slightly increased over the study period. Age was the strongest predictor of non-routine discharge across settings, whereas sex and income effects were significantly associated with outcomes in urban areas. Findings highlight the need for tailored prevention strategies and equitable infrastructure improvements across rural and urban settings.

BACKGROUND:Among adults aged 65 and older, motor-vehicle crashes are the second leading cause of injury-related death-following falls. State driver license renewal laws commonly have provisions targeting older drivers, but limited evidence exists on their effectiveness in reducing crash and injury rates and how this may vary by rurality. This study aimed to investigate the impact of state driver license renewal policies on older driver crash and injury outcomes, by rurality. METHODS:Crash data, license renewal policies, and other relevant state policies were drawn from 13 U.S. states for the years 2000 to 2019. The primary exposures analyzed included the length of the license renewal cycle (in years) and the frequency of in-person renewal. Key outcomes included crash and driver injury rates, stratified by rurality. RESULTS:The study population included 15.6 million crash-involved drivers aged 40 and older. State license renewal laws generally became less restrictive during the study period. Among drivers 75 and older, crash rates in urban areas were higher in states where renewal periods and in-person renewal became less restrictive compared to states with no law change (RR = 1.30, 95% CI: 1.14-1.49). Among drivers aged 65 and older, injury rates were elevated in urban areas as renewal laws became less restrictive (RR65-74 = 1.23, 95% CI: 1.02-1.47; RR75+ = 1.32, 95% CI: 1.12-1.57). DISCUSSION:The observed relaxation of driver license renewal policies was correlated with higher crash and injury rates among drivers aged 75 and older in urban areas. Restrictive license renewal policies that rely on age and time cut points should be weighed carefully against possible negative effects from premature license removal. Movement toward a performance-based licensing system and away from arbitrary age and time cut points may more effectively keep unfit drivers off the road, while retaining those who remain fit to drive.

BACKGROUND:Chronic rhinosinusitis (CRS) is an inflammatory disease characterized by congestion and nasal discharge, facial pain and pressure, and loss of smell, with symptoms lasting longer than 3 months. CRS is common among people with cystic fibrosis (CF) and CF carriers are also more at risk for CRS than non-CF carriers. We evaluate risk for CRS across the lifespan for CF carriers and determine how CF carriers with CRS may differ from non-CF carriers with chronic sinusitis. METHODS:Using 2001 to 2022 MarketScan data, we developed 2 study populations: (1) a matched cohort consisting of CF carriers who were matched to non-CF carriers, and (2) a cohort of patients with chronic sinusitis. We used the matched cohorts of CF carriers and non-CF carriers to estimate age-group-specific incidence rate ratios for experiencing chronic sinusitis. Next, we used the chronic-sinusitis cohort to compare the severity of chronic sinusitis events between CF carriers and non-carriers. Specifically, we estimated the odds of a sinus procedure or the receipt of antibiotic prescriptions to evaluate the severity and healthcare utilization among CF carriers and non-carriers with CRS. Finally, we compared the odds for developing other CF-related conditions among CF carriers with CRS to non-CF carriers with CRS. RESULTS:We found that CRS incidence for CF carriers relative to non-CF carriers was highest for those above 40 years of age. We also found that among people with CRS, CF carriers were more likely to undergo a diagnostic evaluation and endoscopic sinus surgery. CF carriers were also more likely to fill antibiotic prescriptions, use multiple antibiotics, and take antibiotics for longer periods. CONCLUSIONS:CF carriers are more likely than non-carriers to suffer from CRS, have more severe CRS, and to exhibit certain features of CF-associated CRS.

Abstract Background Motor vehicle crashes are the second leading cause of injury death among adults aged 65 and older in the U.S., second only to falls. A common state-level approach to mitigating older adult crash risk is the implementation of driver license renewal policies which vary largely between states and data on their effectiveness in preventing crashes and injuries are limited. To fill this gap, the aim of this study is to examine the association between state driver license renewal policies and older driver crash and injury rates. Methods Historical crash data, license renewal policy data, and other relevant policy and demographic data were gathered from 13 U.S. states (CO, IL, IA, KS, MN, MO, NE, ND, OH, SD, UT, WI, WY) for years 2000 through 2019, inclusive. Main exposures included six license renewal policies: renewal period, in-person renewal frequency, vision testing, knowledge testing, on-road drive testing, and mandatory physician reporting. The primary outcomes were crash and injury rates per 100,000 population. Results The study population included 19,010,179 crash-involved drivers aged 40 and older. State policies became less restrictive in many states over the study period, even for drivers aged 75 and older, resulting in longer times between renewals and fewer in-person renewal requirements. Loosening of in-person renewal from every time to less than every time was associated with increased crash rates, among drivers aged 65 to 74 (RRcrash = 1.08, 95% CI: 1.01–1.16). A longer duration between in-person renewals was associated with increased injury rates among drivers 75 and older (RRinjury = 1.18, 95% CI: 1.00–1.39). Conclusions Generally, state policies became less restrictive and resulted in longer required intervals between license renewal. Loosening of driver license renewal policies was associated with increased crash and injury rates. However, safety benefits of restrictive older driver licensing policies should be carefully weighed against costs to older adult well-being and quality of life following licensure loss. Additional methods to assess fitness to drive are necessary to identify the mechanisms behind the increased rates.

IMPORTANCE:Delays in diagnosing sepsis may increase morbidity and mortality, but the frequency of delays is poorly understood. OBJECTIVES:The aim of this study was to estimate the frequency and duration of diagnostic delays for sepsis and potential risk factors for delay. DESIGN, SETTING, AND PARTICIPANTS:We conducted a retrospective case-crossover analysis of sepsis cases from 2016 to 2019 using claims from Merative MarketScan. We ascertained the index diagnosis of sepsis and corresponding hospitalization. We analyzed healthcare visits in the 180 days before diagnosis and then compared the observed and expected trends in signs or symptoms of infection, immune or organ dysfunction (e.g., fever, dyspnea) during the 14 days before diagnosis. A bootstrapping approach was used to estimate the frequency and duration of potential diagnostic delays along with possible risk-factors for experiencing a delay. MAIN OUTCOMES AND MEASURES:The number of patients who experienced a potential diagnostic delay, duration of delay, and number of potential missed opportunities. RESULTS:We identified a total of 649,756 cases of sepsis from 2016 to 2019 meeting inclusion criteria. There was an increase in visits with signs or symptoms of infection, immune or organ dysfunction just before the index diagnosis of sepsis. We estimated that around 16.57% (95% CI, 16.38-16.78) of patients experienced a potential diagnostic delay, with a mean delay duration of 3.21 days (95% CI, 3.13-3.27) and a median of 2 days. Most delays occurred in outpatient settings. Potential diagnostic delays were more frequent among younger age groups and patients who received antibiotics (odds ratio [OR] 2.58 [95% CI, 2.54-2.62]), or treatments for particular symptoms, including opioids (OR 1.43 [95% CI, 1.40-1.46]) and inhalers (OR 1.37 [95% CI, 1.33-1.40]). CONCLUSIONS AND RELEVANCE:There may be a substantial number of potential missed opportunities to diagnose sepsis, especially in outpatient settings. Multiple factors might contribute to delays in diagnosing sepsis including commonly prescribed medications for symptoms.

OBJECTIVE:The aim of the study was to calculate rates of suicide by lethal means and occupational group during 2013-2019 for US workers. METHODS:This descriptive study included suicide rates for workers 24-65 years of age which were calculated using decedents from the National Violent Death Reporting System and population estimates from the American Community Survey Public Use Microdata Sample. Rates were stratified by lethal means, occupation, and biological sex. RESULTS:Firearm-related suicides rates were highest among construction and extraction; installation, maintenance, and repair; and protective service occupations. Poisoning-related suicide rates were highest among arts, design, entertainment, sports, and media; construction and extraction; and healthcare practitioners and technical occupations. CONCLUSIONS:Occupational groups with access to firearms at work and low-wage jobs have higher rates of firearm-related suicide. Future investigations should examine how occupational access to firearms contributes to suicide risk among workers.

Information criteria provide a cogent approach for identifying models that provide an optimal balance between the competing objectives of goodness-of-fit and parsimony. Models that better conform to a dataset are often more complex, yet such models are plagued by greater variability in estimation and prediction. Conversely, overly simplistic models reduce variability at the cost of increases in bias. Asymptotically efficient criteria are those that, for large samples, select the fitted candidate model whose predictors minimize the mean squared prediction error, optimizing between prediction bias and variability. In the context of prediction, asymptotically efficient criteria are thus a preferred tool for model selection, with the Akaike information criterion (AIC) being among the most widely used. However, asymptotic efficiency relies upon the assumption of a panel of validation data generated independently from, but identically to, the set of training data. We argue that assuming identically distributed training and validation data is misaligned with the premise of prediction and often violated in practice. This is most apparent in a regression context, where assuming training/validation data homogeneity requires identical panels of regressors. We therefore develop a new class of predictive information criteria (PIC) that do not assume training/validation data homogeneity and are shown to generalize AIC to the more practically relevant setting of training/validation data heterogeneity. The analytic properties and predictive performance of these new criteria are explored within the traditional regression framework. We consider both simulated and real-data settings. Software for implementing these methods is provided in the R package, picR, available through CRAN.

Cystic fibrosis (CF) is an autosomal recessive disease characterized by loss-of-function mutations in the CF transmembrane conductance regulator (CFTR) gene, which encodes a chloride and bicarbonate channel.1Cutting G.R. Cystic fibrosis genetics: from molecular understanding to clinical application.Nat Rev Genet. 2015; 16: 45-56https://doi.org/10.1038/nrg3849Crossref PubMed Scopus (643) Google Scholar,2Stoltz D.A. Meyerholz D.K. Welsh M.J. Origins of cystic fibrosis lung disease.N Engl J Med. 2015; 372: 1574-1575https://doi.org/10.1056/NEJMc1502191Crossref PubMed Scopus (119) Google Scholar CFTR is expressed in many different organ systems, including sweat glands.3Quinton P.M. Cystic fibrosis: lessons from the sweat gland.Physiology (Bethesda). 2007; 22: 212-225https://doi.org/10.1152/physiol.00041.2006Crossref PubMed Scopus (163) Google Scholar,4Quinton P.M. Bijman J. Higher bioelectric potentials due to decreased chloride absorption in the sweat glands of patients with cystic fibrosis.N Engl J Med. 1983; 308: 1185-1189https://doi.org/10.1056/NEJM198305193082002Crossref PubMed Scopus (172) Google Scholar Although people with CF secrete normal primary sweat,3Quinton P.M. Cystic fibrosis: lessons from the sweat gland.Physiology (Bethesda). 2007; 22: 212-225https://doi.org/10.1152/physiol.00041.2006Crossref PubMed Scopus (163) Google Scholar,5Quinton P.M. Physiology of sweat secretion.Kidney Int Suppl. 1987; 21: S102-S108PubMed Google Scholar they fail to reabsorb chloride (and sodium), resulting in sweat sodium and chloride concentrations 3-5 times higher than in people without CF.6Farrell P.M. Koscik R.E. Sweat chloride concentrations in infants homozygous or heterozygous for F508 cystic fibrosis.Pediatrics. 1996; 97: 524-528PubMed Google Scholar Accordingly, excessive sweating, without replenishment of fluids and electrolytes, can result in profound sodium and chloride depletion, secondary hyperaldosteronism, and hypokalemic metabolic alkalosis.7Scurati-Manzoni E. Fossali E.F. Agostoni C. et al.Electrolyte abnormalities in cystic fibrosis: systematic review of the literature.Pediatr Nephrol. 2014; 29: 1015-1023https://doi.org/10.1007/s00467-013-2712-4Crossref PubMed Scopus (58) Google Scholar Traditionally, people with only 1 CFTR mutation (CF carriers) were not thought to be at risk for CF-related diseases.8Castellani C. Quinzii C. Altieri S. Mastella G. Assael B.M. A pilot survey of cystic fibrosis clinical manifestations in CFTR mutation heterozygotes.Genet Test. 2001; 5: 249-254https://doi.org/10.1089/10906570152742317Crossref PubMed Scopus (51) Google Scholar,9Castellani C. Assael B.M. Cystic fibrosis: a clinical view.Cell Mol Life Sci. 2017; 74: 129-140https://doi.org/10.1007/s00018-016-2393-9Crossref PubMed Scopus (161) Google Scholar However, CF carriers may be at increased risk for almost all CF-related conditions, albeit at substantially less risk than people with CF.10Miller A.C. Comellas A.P. Hornick D.B. et al.Cystic fibrosis carriers are at increased risk for a wide range of cystic fibrosis-related conditions.Proc Natl Acad Sci U S A. 2020; 117: 1621-1627https://doi.org/10.1073/pnas.1914912117Crossref PubMed Scopus (112) Google Scholar Here we examine the association between CF carrier status and the risk of developing dehydration and specific fluid and electrolyte disorders. We used the MarketScan Research Database, which includes commercial claims from employer-sponsored and Medicare Advantage plans, including inpatient and outpatient visits, prescriptions, demographics, and enrollment information for 2001-2021. We focused on CF carriers that were identified via a genetic test. Each CF carrier was matched to 10 controls based on age, sex, and enrollment period. (See Item S1.) This study was deemed non–human subjects research by The University of Iowa Institutional Review Board (HawkIRB). Outcomes for this study were CF-associated electrolyte- and heat-related disorders, including dehydration and unspecified volume depletion, hypo-osmolality and hyponatremia, hypokalemia, and alkalosis. We also created an aggregated electrolyte variable (Table S1). We first identified patients from our study cohort with diagnoses of interest from all hospitalizations, emergency room visits, and outpatient visits. We then fitted a conditional logistic regression model for each diagnostic outcome with only 1 variable: a CF carrier indicator. (The matching process accounts for age, sex, and enrollment time.) We also examined hospitalizations for each outcome using the same univariable modeling framework. We used Holm's method to control for multiplicity. Next, we evaluated whether any differences we observed between cases and controls could be attributable to differences in weather exposures. (See Item S2 and Tables S2 and S3.) We also conducted a sensitivity analysis where we included mothers of children with CF (obligate carriers) in the analysis. (See Item S3 and Tables S4 and S5.) For analyses, we used R version 4.0.2. Because these data are de-identified, it would be impossible to obtain individual-level informed consent and this study was deemed non–human subjects research. The study cohort contained 29,907 CF carriers and 299,070 matched controls. Baseline characteristics are presented in Table 1. The sample was relatively young: 70.2% of the cohort were between the ages of 18 and 34, and 83.9% were female.Table 1Baseline Characteristics of Study CohortPrimary Cohort (CF Carriers Identified Through Genetic Screening)Carriers (%)Controls (%)N (%)29,907 (9%)299,070 (91%)Age group (years) <184,432 (14.8 %)44,320 (14.8 %) 18-3420,980 (70.2 %)209,800 (70.2 %) 35-443,973 (13.3 %)39,730 (13.3) 45-54337 (1.1 %)3,370 (1.1 %) 55-64151 (0.5 %)1,510 (0.5 %) ≥6534 (0.1 %)340 (0.1 %)Sex Female25,096 (83.9 %)250,960 (83.9 %) Male4,811 (16.1 %)48,110 (16.1 %)Enrollment time <1 year2,888 (9.7 %)28,880 (9.7 %) 1-3 years10,583 (35.4 %)105,830 (35.4 %) 3-5 years8,298 (27.7 %)82,980 (27.7 %) 5-7 years3,586 (12.0 %)35,860 (12.0 %) >7 years4,552 (15.2 %)45,520 (15.2 %)Temperature region of residence Northeast6,475 (14.2 %)39,075 (85.8 %) Southeast6,833 (8.3 %)75,173 (91.7 %) Midwest5,117 (8.9 %)52,305 (91.1 %) Southwest2,334 (6.3 %)34,556 (93.7 %) West3,513 (7.7 %)41,899 (92.3 %) Missing5,635 (9.1 %)56,062 (90.9 %)Mean temperature of residence (°C)13.914.6 Open table in a new tab Diagnosis and hospitalization results are given in Table 2. CF carriers were significantly more likely than controls to have aggregated fluid and electrolyte disorders (OR 1.35, 95% CI 1.28-1.43), dehydration and/or volume depletion (odds ratio [OR], 1.46; 95% CI, 1.36-1.56), hypo-osmolality and/or hyponatremia (OR, 1.33; 95% CI, 1.12-1.58), and hypokalemia (OR, 1.14; 95% CI, 1.03-1.26).Table 2Logistic Regression ResultsDiagnosisAggregated Fluid and Electrolyte DisordersDehydration and Volume DepletionHypoosmolality and/or HyponatremiaHypokalemiaAlkalosisNumber of individuals with each electrolyte disorderCarriers (n)1,4461,01014846613Controls (n)10,8967,0611,1194,10793Odds ratios of electrolyte-related diagnosesOR (95% CI)1.35∗Significance after adjusting for multiplicity (overall significance level=0.05; multiplicity adjustment based on Holm's method). (1.28, 1.43)1.46∗Significance after adjusting for multiplicity (overall significance level=0.05; multiplicity adjustment based on Holm's method). (1.36, 1.56)1.33∗Significance after adjusting for multiplicity (overall significance level=0.05; multiplicity adjustment based on Holm's method). (1.12, 1.58)1.14†Diagnoses for which cystic fibrosis carriers were at significantly higher risk without adjustment (individual significance level=0.05). (1.03, 1.26)1.40 (0.78, 2.50)P value<0.001<0.0010.0010.0090.3Number of individuals with hospitalizations for each electrolyte-related disorderCarriers (n)407207831757Controls (n)3,1671,5937061,47560Odds ratios of hospitalizations for electrolyte-related disordersOR (95% CI)1.29∗Significance after adjusting for multiplicity (overall significance level=0.05; multiplicity adjustment based on Holm's method). (1.17-1.44)1.30∗Significance after adjusting for multiplicity (overall significance level=0.05; multiplicity adjustment based on Holm's method). (1.13-1.51)1.17†Diagnoses for which cystic fibrosis carriers were at significantly higher risk without adjustment (individual significance level=0.05). (0.94-1.48)1.19†Diagnoses for which cystic fibrosis carriers were at significantly higher risk without adjustment (individual significance level=0.05). (1.02-1.39)1.27†Diagnoses for which cystic fibrosis carriers were at significantly higher risk without adjustment (individual significance level=0.05). (0.53-2.55)P value<0.001<0.0010.20.040.7∗ Significance after adjusting for multiplicity (overall significance level = 0.05; multiplicity adjustment based on Holm's method).† Diagnoses for which cystic fibrosis carriers were at significantly higher risk without adjustment (individual significance level = 0.05). Open table in a new tab CF carriers were also significantly more likely than controls to be hospitalized owing to aggregated fluid and electrolyte disorders (OR, 1.29; 95% CI, 1.17-1.44), dehydration and/or volume depletion (OR, 1.30; 95% CI, 1.13-1.51), and hypokalemia (OR, 1.19; 95% CI, 1.02-1.39). Finally, we determined that weather was not an important confounder or effect modifier. (See Section S2.) Also, in our sensitivity analysis, we found that CF carriers were more likely to be diagnosed and hospitalized for the preceding fluid and electrolyte conditions as well as alkalosis. Our findings suggest that CF carriers are at increased risk, compared to non-CF carriers, for fluid and electrolyte disorders traditionally associated with CF and that known CF carriers may benefit from counseling to maintain adequate fluid and electrolyte replacement and to avoid drinking beyond thirst with water. In addition, given the commercial availability of CF genetic testing, these findings support implementation of additional research examining the potential value of testing for CF carrier status in patients who present with repeated thermal dehydration and hyponatremia. Because we used administrative data to identify CF carriers and fluid and electrolyte disorders, the present work is associated with some limitations. Only insured patients were included. There may be inaccuracies in diagnosis codes, and laboratory values were not available to confirm diagnoses. We did not measure comorbidities, medication use, or occupations that are associated with dehydration. We were only able to identify a limited number of CF carriers and were unable to account for the type of CFTR mutation. Finally, we did not compare the risk of outcomes in CF carriers to those with CF. Despite our limitations, our results collectively demonstrate that CF carriers are at risk for the same fluid and electrolyte abnormalities that are associated with CF. Because approximately 1 out of 33 people in the United States are CF carriers, our results suggest that a substantial number of people are more prone to developing dehydration and electrolyte abnormalities. Study design: PMP, JES; data preparation: ACM; data analysis: JEC, LAP, SL, LMH; data interpretation: ACM, JMN, MHA, PMP. Each author contributed important intellectual content during manuscript drafting or revision and agrees to be personally accountable for the individual's own contributions and to ensure that questions pertaining to the accuracy or integrity of any portion of the work, even one in which the author was not directly involved, are appropriately investigated and resolved, including with documentation in the literature if appropriate. Research reported in this publication was supported by the National Institute for Allergy and Infectious Diseases under award number R01AI143671 (to PMP) and the National Center for Advancing Translational Sciences of the National Institutes of Health under award number UL1TR002537 (to PMP). The funders had no role in the study design; the collection, analysis, or interpretation of data; manuscript writing; or the decision to submit the manuscript for publication. The authors declare that they have no relevant financial interests. Received November 29, 2022. Evaluated by 2 external peer reviewers, with direct editorial input from a Statistics/Methods Editor, an Associate Editor, and the Editor-in-Chief. Accepted in revised form September 7, 2023. Download .pdf (.21 MB) Help with pdf files Supplementary File (PDF)Items S1-S3, Tables S1-S5.

Purpose: To characterize the relationship between implementation of an antibullying law and bullying rates among high school youth. Methods: School staff (administrators, counselors, and teachers) from public high schools in Maine completed a survey assessing: (1) the frequency with which they implemented 17 components of their district's antibullying policy as mandated by state law; and (2) confidence in implementing the law. Their responses were linked to data on bullying victimization among high school respondents to the Maine Integrated Youth Health Survey, which created a population-based dataset of 84 high schools with 29,818 student responses. Results: Students in schools where administrators (adjusted odds ratio = 0.93; 95% CI: 0.89, 0.97) and counselors (adjusted odds ratio = 0.86; 95% CI: 0.81, 0.92) reported implementing more mandated components of the law experienced notable reductions in the odds of bullying, controlling for student-level characteristics (sex, race, grade) and for school-level bullying rates assessed prior to the passage of the law. With respect to specific implementation components, bullying was most consistently reduced in schools where staff reported increased referrals for counseling and other supports for targets of bullying and in schools where counselors and teachers were interviewed as part of bullying investigations. Students in schools where teachers reported increased confidence in implementing the antibullying law also had reduced odds of bullying. Discussion: These data provide some of the first evidence that the efficacy of a state's antibullying law depends in part on the extent to which school personnel implement the law.(c) 2023 Society for Adolescent Health and Medicine. All rights reserved.

INTRODUCTION:Given the largely autocentric nature of the United States, drivers continue to operate vehicles with varying levels of driving ability and self-restriction as they advance into older age. This study explores the associations of vehicle actions and traffic control devices with older drivers' driving errors contributing to crashes, incorporating age group as effect modifiers of these relationships. METHOD:This study includes crashes reported to the Iowa Department of Transportation from 2010 to 2020. Analysis was completed for drivers involved in a crash who were aged 45 years and older (n = 254,912). Driving errors were identified based on driver contributing factors reported in the Iowa crash data. A multivariable logistic regression model was built to model predictors of driving errors, focusing on crash-related vehicle actions and traffic control devices. Additionally, interaction terms were incorporated to examine the moderating effect of age groups (45-64; 65-74; 75-84; 85+). RESULTS:Driving errors increased with age, especially in the middle-old age group (75-84). A higher probability of driving errors was observed in changing lanes, merging, and turning, with right turns showing the most substantive increase in the middle-old age group compared to the other age groups. Stop and yield signs were associated with a higher probability of driving errors, increasing monotonically with age. The middle-old age group exhibited a notable increase in driving errors at uncontrolled or traffic signaled locations compared to the other age groups. CONCLUSIONS:The significant increase in driving errors at and beyond the middle-old age group may demonstrate higher age-related declines in safe driving compared to younger age groups. PRACTICAL APPLICATIONS:Careful evaluations for older drivers' fitness to drive during license renewal periods are needed once drivers reach the middle-old age. Additionally, effective combinations of advanced technologies, traffic systems, and policies are necessary to reduce the burdens associated with aging.

INTRODUCTION:Alcohol impairment is a major contributor to road traffic crashes and has increased across the United States in recent years. In 2022, over 13,000 people were killed in drunk driving crashes. Enforcement of impaired driving laws is an essential strategy to reduce alcohol-impaired driving and subsequent crashes. However, little is known about conviction outcomes related to alcohol-involved crashes. The aim of this study is to examine the association between charge combinations and conviction rates among alcohol-influenced drivers involved in crashes. METHODS:Data for this study included 2016-2019 Iowa Department of Transportation crash data linked to charges and convictions from the Iowa Court Information System. The study sample included drivers with reported BAC ≥ 0.08 g/dl and/or driver condition reported as under influence of alcohol. Charges were divided into three categories: alcohol, moving, and administrative/miscellaneous. Two logistic regression models were built with any conviction and alcohol conviction as the outcomes. The main predictor was charge combination. RESULTS:The study sample included 8,238 alcohol-impaired drivers, of whom 6,846 (83.1%) were charged with any type of traffic offense and 6,253 (75.8%) were charged with alcohol-related traffic offenses. Among charged drivers, 96.2% were convicted on any traffic charge and 87.7% were convicted on an alcohol charge. Drivers with a combination of alcohol, administrative, and moving violation charges had higher odds of any conviction (OR = 2.6, 95% CI = 1.7-4.3) compared to drivers with only alcohol charges. CONCLUSIONS:Charging impaired drivers with multiple types of charges was associated with increased odds of conviction on any charge but not on alcohol charges, which had high conviction rates overall. PRACTICAL APPLICATIONS:Results from this study can help guide law enforcement to ensure appropriate charges are made in all relevant categories and optimal combinations of charges are administered to impaired drivers to increase odds of conviction.

4-to-3 lane conversions, often called road diets, have been implemented throughout the U.S. as a means to reduce crashes. However, the reduction in lanes has led to community wide concerns across the country regarding the possible negative effect on emergency responses. This study investigates the impact of 4-to-3-lane roadway conversions on emergency response in Iowa through surveys and a retrospective analysis of EMS data. The 170 survey responses were analyzed descriptively, and a text analysis was done on two open text survey questions. Generalized linear models were constructed to examine the impact of lane conversions on emergency response times. Over half of EMS respondents believed there was no effect or a positive effect on responses, while 40% believed there was a negative effect. The negative effect was often attributed to driver confusion on how to properly yield to EMS vehicles. Despite the differing perceptions, EMS response rates from before to after the implementation of 4-to-3 lane conversions did not meaningfully differ. Overall, there was a lack of evidence of an effect of 4-to-3 lane conversions on EMS response rates in Cedar Rapids, Iowa. However, survey results showed that public guidance on how to properly respond to the presence of EMS vehicles on these roadways may be needed. This study provides evidence for addressing local concerns about road diets and emergency response to add to other known safety benefits. Results of this analysis may be applicable to other lane conversion sites when appropriately combined with local context relevant to the target area.

One of the primary issues that arises in statistical modeling pertains to the assessment of the relative importance of each variable in the model. A variety of techniques have been proposed to quantify variable importance for regression models. However, in the context of best subset selection, fewer satisfactory methods are available. With this motivation, we here develop a variable importance measure expressly for this setting. We investigate and illustrate the properties of this measure, introduce algorithms for the efficient computation of its values, and propose a procedure for calculating p-values based on its sampling distributions. We present multiple simulation studies to examine the properties of the proposed methods, along with an application to demonstrate their practical utility.

We developed a novel machine learning (ML) algorithm with the goal of producing transparent models (i.e., understandable by humans) while also flexibly accounting for nonlinearity and interactions. Our method is based on ranked sparsity, and it allows for flexibility and user control in varying the shade of the opacity of black box machine learning methods. The main tenet of ranked sparsity is that an algorithm should be more skeptical of higher-order polynomials and interactions a priori compared to main effects, and hence, the inclusion of these more complex terms should require a higher level of evidence. In this work, we put our new ranked sparsity algorithm (as implemented in the open source R package, sparseR) to the test in a predictive model “bakeoff” (i.e., a benchmarking study of ML algorithms applied “out of the box”, that is, with no special tuning). Algorithms were trained on a large set of simulated and real-world data sets from the Penn Machine Learning Benchmarks database, addressing both regression and binary classification problems. We evaluated the extent to which our human-centered algorithm can attain predictive accuracy that rivals popular black box approaches such as neural networks, random forests, and support vector machines, while also producing more interpretable models. Using out-of-bag error as a meta-outcome, we describe the properties of data sets in which human-centered approaches can perform as well as or better than black box approaches. We found that interpretable approaches predicted optimally or within 5% of the optimal method in most real-world data sets. We provide a more in-depth comparison of the performances of random forests to interpretable methods for several case studies, including exemplars in which algorithms performed similarly, and several cases when interpretable methods underperformed. This work provides a strong rationale for including human-centered transparent algorithms such as ours in predictive modeling applications.

Most statistical modeling applications involve the consideration of a candidate collection of models based on various sets of explanatory variables. The candidate models may also differ in terms of the structural formulations for the systematic component and the posited probability distributions for the random component. A common practice is to use an information criterion to select a model from the collection that provides an optimal balance between fidelity to the data and parsimony. The analyst then typically proceeds as if the chosen model was the only model ever considered. However, such a practice fails to account for the variability inherent in the model selection process, which can lead to inappropriate inferential results and conclusions. In recent years, inferential methods have been proposed for multimodel frameworks that attempt to provide an appropriate accounting of modeling uncertainty. In the frequentist paradigm, such methods should ideally involve model selection probabilities, i.e., the relative frequencies of selection for each candidate model based on repeated sampling. Model selection probabilities can be conveniently approximated through bootstrapping. When the Akaike information criterion is employed, Akaike weights are also commonly used as a surrogate for selection probabilities. In this work, we show that the conventional bootstrap approach for approximating model selection probabilities is impacted by bias. We propose a simple correction to adjust for this bias. We also argue that Akaike weights do not provide adequate approximations for selection probabilities, although they do provide a crude gauge of model plausibility.

Background: Pertussis is a highly contagious respiratory illness that can be especially dangerous to young children. Transmission of pertussis often occurs in household settings and is impacted by the timing of treatment and postexposure chemoprophylaxis. This study analyzes the risk for secondary household transmission and if delays in diagnosing pertussis increased the risk for household transmission. Methods: We conducted 2 population-based studies using a large nationally representative administrative claims database. The first study utilized a stratified monthly incidence model to compare the incidence of pertussis among enrollees exposed to a family member with pertussis versus those not exposed. The second study was conducted at a household level following the index case of pertussis in each household. We identified diagnostic delays in the initial household case and used a logistic regression model to evaluate if such delays were associated with a greater risk for transmission. Results: The incidence rate ratio of pertussis was 938.99 [95% confidence interval (CI): 880.19-1001.73] among enrollees exposed to a family member with pertussis relative to those not exposed. The odds of secondary household transmission in households where the index case experienced a diagnostic delay was 5.10 (CI: 4.44-5.85) times the odds of transmission when the index case was not delayed. We found that longer delays were associated with a greater risk for secondary household transmission (P < 0.0001). Conclusions: There is a high rate of secondary transmission of pertussis in household settings. Diagnostic delays increase the likelihood that pertussis will transmit in the household.

Background People with cystic fibrosis (CF) are at increased risk for bronchiectasis, and several reports suggest that CF carriers may also be at higher risk for developing bronchiectasis. The purpose of this study was to determine if CF carriers are at risk for more severe courses or complications of bronchiectasis.Methods Using MarketScan data (2001-2021), we built a cohort consisting of 105 CF carriers with bronchiectasis and 300 083 controls with bronchiectasis but without a CF carrier diagnosis. We evaluated if CF carriers were more likely to be hospitalized for bronchiectasis. In addition, we examined if CF carriers were more likely to be infected with Pseudomonas aeruginosa or nontuberculous mycobacteria (NTM) or to have filled more antibiotic prescriptions. We considered regression models for incident and rate outcomes that controlled for age, sex, smoking status, and comorbidities.Results The odds of hospitalization were almost 2.4 times higher (95% CI, 1.116-5.255) for CF carriers with bronchiectasis when compared with non-CF carriers with bronchiectasis. The estimated odds of being diagnosed with a Pseudomonas infection for CF carriers vs noncarriers was about 4.2 times higher (95% CI, 2.417-7.551) and 5.4 times higher (95% CI, 3.398-8.804) for being diagnosed with NTM. The rate of distinct antibiotic fill dates was estimated to be 2 times higher for carriers as compared with controls (95% CI, 1.735-2.333), and the rate ratio for the total number of days of antibiotics supplied was estimated as 2.8 (95% CI, 2.290-3.442).Conclusions CF carriers with bronchiectasis required more hospitalizations and more frequent administration of antibiotics as compared with noncarriers. Given that CF carriers were also more likely to be diagnosed with Pseudomonas and NTM infections, CF carriers with bronchiectasis may have a phenotype more resembling CF-related bronchiectasis than non-CF bronchiectasis. Using Marketscan data (2001-2021), we found that cystic fibrosis (CF) carriers with bronchiectasis face nearly 2.4 higher odds of hospitalization, increased rates of Pseudomonas and NTM infections and antibiotic use compared to non-CF-carriers with bronchiectasis suggesting a unique bronchiectasis phenotype.