Search

Background: The National Asthma Education and Prevention Program guidelines emphasize environmental control as an integral part of asthma management; however, limited national-level data exist on how clinicians implement environmental control recommendations., Objective: We analyzed data on clinicians' self-reported use of recommended environmental control practices in a nationally representative sample (n = 1645) of primary care physicians, asthma specialists, and advanced practice providers from the National Asthma Survey of Physicians, a supplemental questionnaire to the 2012 National Ambulatory Medical Care Survey., Methods: We examined clinician and practice characteristics as well as clinicians' decisions and strategies regarding environmental trigger assessment and environmental control across provider groups. Regression modeling was used to identify clinician and practice characteristics associated with implementation of guideline recommendations., Results: A higher percentage of specialists assessed asthma triggers at home, school, and/or work than primary care or advanced practice providers (almost always: 53.6% vs 29.4% and 23.7%, respectively, P  < .001). Almost all clinicians (>93%) recommended avoidance of secondhand tobacco smoke, whereas recommendations regarding cooking appliances (eg, proper ventilation) were infrequent. Although assessment and recommendation practices differed between clinician groups, modeling results showed that clinicians who reported almost always assessing asthma control were 5- to 6-fold more likely to assess environmental asthma triggers. Use of asthma action plans was also strongly associated with implementation of environmental control recommendations., Conclusions: Environmental assessment and recommendations to patients varied among asthma care providers. High adherence to other key guideline components, such as assessing asthma control, was associated with environmental assessment and recommendation practices on environmental control., Competing Interests: Supported in part by the Intramural Research Program of the 10.13039/100000002National Institutes of Health, the 10.13039/100000066National Institute of Environmental Health Sciences (Z01-ES-025041), and through a contract to Social & Scientific Systems funded by the National Institute of Environmental Health Sciences (HHSN273201600002I). The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention or the US Environmental Protection Agency. Disclosure of potential conflict of interest: The authors declare that they have no relevant conflicts of interest.

Despite the prominent use of complex survey data and the growing popularity of machine learning methods in epidemiologic research, few machine learning software implementations offer options for handling complex samples. A major challenge impeding the broader incorporation of machine learning into epidemiologic research is incomplete guidance for analyzing complex survey data, including the importance of sampling weights for valid prediction in target populations. Using data from 15, 820 participants in the 1988-1994 National Health and Nutrition Examination Survey cohort, we determined whether ignoring weights in gradient boosting models of all-cause mortality affected prediction, as measured by the F1 score and corresponding 95% confidence intervals. In simulations, we additionally assessed the impact of sample size, weight variability, predictor strength, and model dimensionality. In the National Health and Nutrition Examination Survey data, unweighted model performance was inflated compared to the weighted model (F1 score 81.9% [95% confidence interval: 81.2%, 82.7%] vs 77.4% [95% confidence interval: 76.1%, 78.6%]). However, the error was mitigated if the F1 score was subsequently recalculated with observed outcomes from the weighted dataset (F1: 77.0%; 95% confidence interval: 75.7%, 78.4%). In simulations, this finding held in the largest sample size (N = 10,000) under all analytic conditions assessed. For sample sizes <5,000, sampling weights had little impact in simulations that more closely resembled a simple random sample (low weight variability) or in models with strong predictors, but findings were inconsistent under other analytic scenarios. Failing to account for sampling weights in gradient boosting models may limit generalizability for data from complex surveys, dependent on sample size and other analytic properties. In the absence of software for configuring weighted algorithms, post-hoc re-calculations of unweighted model performance using weighted observed outcomes may more accurately reflect model prediction in target populations than ignoring weights entirely., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Background: Oxidative stress plays a key role in the pathogenesis of respiratory diseases; however, studies on antioxidant vitamins and respiratory outcomes have been conflicting. We evaluated whether lower serum levels of vitamins A, C, D, and E are associated with respiratory morbidity and mortality in the U.S. adult population., Methods: We conducted a pooled analysis of data from the 1988-1994 and 1999-2006 National Health and Nutrition Examination Survey (participants aged ≥ 20 years). We estimated covariate-adjusted odds ratios (aOR) per interquartile decrease in each serum vitamin level to quantify associations with respiratory morbidity, and covariate-adjusted hazard ratios (aHR) to quantify associations with respiratory mortality assessed prospectively through 2015. Vitamin supplementation and smoking were evaluated as potential effect modifiers., Results: Lower serum vitamin C increased the odds of wheeze among all participants (overall aOR: 1.08, 95% CI: 1.01-1.16). Among smokers, lower serum α-tocopherol vitamin E increased the odds of wheeze (aOR: 1.11, 95% CI: 1.04-1.19) and chronic bronchitis/emphysema (aOR: 1.13, 95% CI: 1.03-1.24). Conversely, lower serum γ-tocopherol vitamin E was associated with lower odds of wheeze and chronic bronchitis/emphysema (overall aORs: 0.85, 95% CI: 0.79-0.92 and 0.85, 95% CI: 0.76-0.95, respectively). Lower serum vitamin C was associated with increased chronic lower respiratory disease (CLRD) mortality in all participants (overall aHR: 1.27, 95% CI: 1.07-1.51), whereas lower serum 25-hydroxyvitamin D (25-OHD) tended to increase mortality from CLRD and influenza/pneumonia among smokers (aHR range: 1.33-1.75). Mortality from influenza/ pneumonia increased with decreasing serum vitamin A levels in all participants (overall aHR: 1.21, 95% CI: 0.99-1.48). In pooled analysis, vitamin C deficiency and 25-OHD insufficiency were associated with mortality from influenza/pneumonia, increasing mortality risk up to twofold., Conclusions: Our analysis of nationally representative data on over 34,000 participants showed that lower serum levels of vitamins A, C, D, and α-tocopherol vitamin E are associated with increased respiratory morbidity and/or mortality in U.S. adults. The results underscore the importance of antioxidant vitamins in respiratory health., (© 2022. The Author(s).)