Association between high school students’ cigarette smoking, asthma and related beliefs: a population-based study

Background Smoking has a detrimental effect on the symptoms and severity of asthma, a common chronic disease among adolescents. The purpose of this study was to examine the association between asthma and smoking among high school students and assess provider-patient communication with asthmatic adolescents regarding smoking and adolescents’ beliefs about the harms of smoking. Methods In fall 2014, data from high school students, ages 14–18 years, completing the 2009-2010 Virginia Youth Tobacco Survey (N = 1796) were used in descriptive analyses and multivariable logistic regression models adjusting for model-specific confounders as appropriate. Results Overall, an estimated 19 % of high school students in Virginia smoked and 16 % had asthma. Odds of smoking did not differ by asthma status; however, asthmatics had 1.5 times higher odds of being asked if they smoke (95 % CI 1.06–2.13) and being advised not to smoke by a health professional (95 % CI 1.10–2.14) compared to non-asthmatics. Asthmatics who believed second-hand smoke or smoking 1–5 cigarettes/day was not harmful had respectively 4.2 and 2.8 times higher odds of smoking than those who thought each was harmful. Further, asthmatics who thought smoking 1−2 years is safe had 3.4 times higher odds of smoking than those who did not (95 % CI 1.57–10.1). Conclusions While asthmatic adolescents are just as likely to smoke as non-asthmatics, less healthy beliefs about the risks of smoking increase the odds of smoking among asthmatics. Thus, targeted asthma-specific smoking prevention and education to change attitudes and beliefs could be an effective tool for adolescents

Harnessing Information Technology to Inform Patients Facing Routine Decisions: Cancer Screening as a Test Case

PURPOSE Technology could transform routine decision making by anticipating patients’ information needs, assessing where patients are with decisions and preferences, personalizing educational experiences, facilitating patient-clinician information exchange, and supporting follow-up. This study evaluated whether patients and clinicians will use such a decision module and its impact on care, using 3 cancer screening decisions as test cases. METHODS Twelve practices with 55,453 patients using a patient portal participated in this prospective observational cohort study. Participation was open to patients who might face a cancer screening decision: women aged 40 to 49 who had not had a mammogram in 2 years, men aged 55 to 69 who had not had a prostate-specific antigen test in 2 years, and adults aged 50 to 74 overdue for colorectal cancer screening. Data sources included module responses, electronic health record data, and a postencounter survey. RESULTS In 1 year, one-fifth of the portal users (11,458 patients) faced a potential cancer screening decision. Among these patients, 20.6% started and 7.9% completed the decision module. Fully 47.2% of module completers shared responses with their clinician. After their next office visit, 57.8% of those surveyed thought their clinician had seen their responses, and many reported the module made their appointment more productive (40.7%), helped engage them in the decision (47.7%), broadened their knowledge (48.1%), and improved communication (37.5%). CONCLUSIONS Many patients face decisions that can be anticipated and proactively facilitated through technology. Although use of technology has the potential to make visits more efficient and effective, cultural, workflow, and technical changes are needed before it could be widely disseminated

Assessing the current and desired levels of training and applied experiences in chronic disease prevention of students during medical school

Introduction Chronic diseases account for approximately 70% of deaths in the U.S. annually. Though physicians are uniquely positioned to provide behavior change counseling for chronic disease prevention, they often lack the necessary training and self-efficacy. This study examined medical student interest in receiving chronic disease prevention training as a formal part of their education as part of an effort to enhance their ability to provide guidance to patients in the future. Methods A 23-question, online survey was sent to all undergraduate medical students enrolled in a large medical education program. The survey assessed medical student interest in receiving training related to chronic disease prevention. Survey topics included student awareness of primary prevention programs, perceived importance of receiving training and applied experience in chronic disease prevention, and preferences for how and when to receive this training. Results Of 793 eligible medical students, 432 completed the survey (54.5%). Overall, 92.4% of students reported receiving formal training in physical activity, public health, nutrition, obesity, smoking cessation, and chronic diseases was of “very high” or “high” importance. Despite this level of importance, students most frequently reported receiving no or 1–5 h of formal training in a number of topics, including physical activity (35.4% and 47.0%, respectively) and nutrition (16.9% and 56.3%, respectively). The level of importance given to public health training was significantly greater across degree type (p = 0.0001) and future specialty (p = 0.03) for MD/MPH students and those interested in primary care, respectively. Conclusions While medical students perceive chronic disease prevention as an important topic, most reported receiving little to no formal training. To address the growing prevalence of chronic disease across our society, programs schools should place greater emphasis on integrating training in physical activity, nutrition, and obesity-related content into the medical education curriculum

Randomised Trial to Evaluate the Effectiveness and Impact of Offering Postvisit Decision Support and Assistance in Obtaining Physician-Recommended Colorectal Cancer Screening: The e-Assist: Colon Health Study - A Protocol Study

INTRODUCTION: How to provide practice-integrated decision support to patients remains a challenge. We are testing the effectiveness of a practice-integrated programme targeting patients with a physician recommendation for colorectal cancer (CRC) screening. METHODS AND ANALYSIS: In partnership with healthcare teams, we developed \u27e-assist: Colon Health\u27, a patient-targeted, postvisit CRC screening decision support programme. The programme is housed within an electronic health record (EHR)-embedded patient portal. It leverages a physician screening recommendation as the cue to action and uses the portal to enrol and intervene with patients. Programme content complements patient-physician discussions by encouraging screening, addressing common questions and assisting with barrier removal. For evaluation, we are using a randomised trial in which patients are randomised to receive e-assist: Colon Health or one of two controls (usual care plus or usual care). Trial participants are average-risk, aged 50-75 years, due for CRC screening and received a physician order for stool testing or colonoscopy. Effectiveness will be evaluated by comparing screening use, as documented in the EHR, between trial enrollees in the e-assist: Colon Health and usual care plus (CRC screening information receipt) groups. Secondary outcomes include patient-perceived benefits of, barriers to and support for CRC screening and patient-reported CRC screening intent. The usual care group will be used to estimate screening use without intervention and programme impact at the population level. Differences in outcomes by study arm will be estimated with hierarchical logit models where patients are nested within physicians. ETHICS AND DISSEMINATION: All trial aspects have been approved by the Institutional Review Board of the health system in which the trial is being conducted. We will disseminate findings in diverse scientific venues and will target clinical and quality improvement audiences via other venues. The intervention could serve as a model for filling the gap between physician recommendations and patient action. TRIAL REGISTRATION NUMBER: NCT02798224; Pre-results

Nourishing Our Understanding of Role Modeling to Improve Support and Health (NOURISH): Design and methods

Pediatric overweight is associated with numerous physical and psychological health risks, and overweight children are at significant risk for obesity in adulthood. African-American children are at particularly high risk for obesity and related health complications. However, this racial group has traditionally had limited access to obesity treatment and relatively few studies have included sufficient numbers of lower-SES, African American participants. Further, although parental involvement in treatment for pediatric overweight has been found to be beneficial, few studies have examined the efficacy of offering treatment exclusively to parents, a potentially cost-effective approach which could benefit the entire family. This pilot project will evaluate the efficacy of an intensive parenting intervention, (NOURISH; Nourishing Our Understanding of Role modeling to Improve Support and Health), targeting racially diverse parents of overweight children (ages 6–11). NOURISH addresses several urgent research priorities by targeting the underserved and addressing the significant disparity in obesity treatment services. Parents meeting study criteria (having a child between the ages of 6 and 11 with a BMI ≥ the 85th percentile) will be offered participation in the randomized trial comparing NOURISH with a control group. We hypothesize that children whose parents participate in NOURISH will manifest greater decreases in BMI, and greater improvements in dietary intake, and quality of life compared to children whose parents do not participate. This study is designed explicitly to gather preliminary feasibility, acceptability, and effectiveness data to inform a subsequent larger randomized controlled trial

Alternative processing of its precursor is related to miR319 decreasing in melon plants exposed to cold

[EN] miRNAs are fundamental endogenous regulators of gene expression in higher organisms. miRNAs modulate multiple biological processes in plants. Consequently, miRNA accumulation is strictly controlled through miRNA precursor accumulation and processing. Members of the miRNA319 family are ancient ribo-regulators that are essential for plant development and stress responses and exhibit an unusual biogenesis that is characterized by multiple processing of their precursors. The significance of the high conservation of these non-canonical biogenesis pathways remains unknown. Here, we analyze data obtained by massive sRNA sequencing and 5 ' - RACE to explore the accumulation and infer the processing of members of the miR319 family in melon plants exposed to adverse environmental conditions. Sequence data showed that miR319c was down regulated in response to low temperature. However, the level of its precursor was increased by cold, indicating that miR319c accumulation is not related to the stem loop levels. Furthermore, we found that a decrease in miR319c was inversely correlated with the stable accumulation of an alternative miRNA (#miR319c) derived from multiple processing of the miR319c precursor. Interestingly, the alternative accumulation of miR319c and #miR319c was associated with an additional and non-canonical partial cleavage of the miR319c precursor during its loop-to-base-processing. Analysis of the transcriptional activity showed that miR319c negatively regulated the accumulation of HY5 via TCP2 in melon plants exposed to cold, supporting its involvement in the low temperature signaling pathway associated with anthocyanin biosynthesis. Our results provide new insights regarding the versatility of plant miRNA processing and the mechanisms regulating them as well as the hypothetical mechanism for the response to cold-induced stress in melon, which is based on the alternative regulation of miRNA biogenesis.Bustamante-González, AJ.; Marques Romero, MC.; Sanz-Carbonell, A.; Mulet, JM.; Gomez, GG. (2018). Alternative processing of its precursor is related to miR319 decreasing in melon plants exposed to cold. Scientific Reports. 8:1-13. https://doi.org/10.1038/s41598-018-34012-7S1138Borges, F. & Martienssen, R. A. The expanding world of small RNAs in plants. Nat Rev Mol Cell Biol 16, 727–741 (2015).Shriram, V., Kumar, V., Devarumath, R. M., Khare, T. S. & Wani, S. H. MicroRNAs As Potential Targets for Abiotic Stress Tolerance in Plants. Front Plant Sci 7, 817 (2016).Xie, M., Zhang, S. & Yu, B. microRNA biogenesis, degradation and activity in plants. Cell Mol Life Sci 72, 87–99 (2015).Bologna, N. G., Schapire, A. L. & Palatnik, J. F. Processing of plant microRNA precursors. Brief Funct Genomics 12, 37–45 (2012).Achkar, N. P., Cambiagno, D. A. & Manavella, P. A. miRNA Biogenesis: A Dynamic Pathway. Trends Plant Sci 21, 1034–1044 (2016).Dong, Z., Han, M. H. & Fedoroff, N. The RNA-binding proteins HYL1 and SE promote accurate in vitro processing of pri-miRNA by DCL1. Proc Natl Acad Sci USA 105, 9970–9975 (2008).Bologna, N. G. et al. Multiple RNA recognition patterns during microRNA biogenesis in plants. Genome Research 23, 1675–1689 (2013).Baranauskė, S. et al. Functional mapping of the plant small RNA methyltransferase: HEN1 physically interacts with HYL1 and DICER-LIKE 1 proteins. Nucleic Acids Res 43, 2802–2812 (2015).Zhang, S., Liu, Y. & Yu, B. New insights into pri-miRNA processing and accumulation in plants. WIREs. RNA 6, 533–545 (2015).Ren, G. et al. Regulation of miRNA abundance by RNA binding protein TOUGH in Arabidopsis. Proc Natl Acad Sci USA 109, 12817–12821 (2012).Cuperus, J. T., Fahlgren, N. & Carrington, J. C. Evolution and functional diversification of MIRNA genes. Plant Cell 23, 431–442 (2011).Zhang, W. et al. Multiple distinct small RNAs originate from the same microRNA precursors. Genome Biol 11(8), r81 (2010).Addo-Quaye, C. et al. Sliced microRNA targets and precise loop-first processing of MIR319 hairpins revealed by analysis of the Physcomitrella patens degradome. RNA 15, 2112–2121 (2009).Axtell, M. J., Snyder, J. A. & Bartel, D. P. Common functions for diverse small RNAs of land plants. Plant Cell 19, 1750–1769 (2007).Bologna, N. G., Mateos, J. L., Bresso, E. G. & Palatnik, J. F. A loop-to-base processing mechanism underlies the biogenesis of plant microRNAs miR319 and miR159. EMBO J 28, 3646–3656 (2009).Li, Y., Li, C., Ding, G. & Jin, Y. Evolution of MIR159/319 microRNA genes and their post-transcriptional regulatory link to siRNA pathways. BMC Evol Biol 11, 122 (2011).Sobkowiak, L., Karlowski, W., Jarmolowski, A. & Szweykowska-Kulinska, Z. Non-Canonical Processing of Arabidopsis pri-miR319a/b/c Generates Additional microRNAs to Target One RAP2.12 mRNA Isoform. Front Plant Sci 3, 46 (2012).Achard, P., Herr, A., Baulcombe, D. C. & Harberd, N. P. Modulation of floral development by a gibberellin-regulated microRNA. Development 131, 3357–3365 (2004).Allen, R. S. et al. Genetic analysis reveals functional redundancy and the major target genes of the Arabidopsis miR159 family. Proc Natl Acad Sci USA 104, 16371–16376 (2007).Jones-Rhoades, M. W. & Bartel, D. P. Computational identification of plant microRNAs and their targets, including a stress-induced miRNA. Mol Cell 14, 787–799 (2004).Palatnik, J. F. et al. Control of leaf morphogenesis by microRNAs. Nature 425, 257–263 (2003).Wang, S. T. et al. MicroRNA319 positively regulates cold tolerance by targeting OsPCF6 and OsTCP21 in rice (Oryza sativa). PLoS One 9(3), e91357 (2014).Thiebaut, F. et al. Regulation of miR319 during cold stress in sugarcane. Plant Cell Environ 35, 502–512 (2012).Sunkar, R. & Zhu, J. K. Novel and stress-regulated microRNAs and other small RNAs from Arabidopsis. Plant Cell 16, 2001–2019 (2004).Chen, H. et al. A comparison of the low temperature transcriptomes of two tomato genotypes that differ in freezing tolerance: Solanum lycopersicum and Solanum habrochaites. BMC Plant Biol 15, 132 (2015).Garcia-Mas, J. et al. The genome of melon (Cucumis melo L.). Proc Natl Acad Sci USA 109, 11872–11877 (2012).Nuñez-Palenius, H. G. et al. Melon fruits: genetic diversity, physiology, and biotechnology features. Crit Rev Biotechnol 28, 13–55 (2008).Gonzalez-Ibeas, D. et al. Analysis of the melon (Cucumis melo) small RNAome by high-throughput pyrosequencing. BMC Genomics 12, 393 (2011).Herranz, M. C., Navarro, J. A., Sommen, E. & Pallas, V. Comparative analysis among the small RNA populations of source, sink and conductive tissues in two different plant-virus pathosystems. BMC Genomics 16, 117 (2015).Sattar, S. et al. Expression of small RNA in Aphis gossypii and its potential role in the resistance interaction with melon. PLoS One 7(11), e48579 (2012).Dai, X. & Zhao, P. X. psRNATarget: a plant small RNA target analysis server. Nucleic Acids Res. 39, W155–9 (2011).Palatnik, J. F. et al. Sequence and expression differences underlie functional specialization of Arabidopsis microRNAs miR159 and miR319. Dev Cell 13, 115–125 (2007).He, Z., Zhao, X., Kong, F., Zuo, Z. & Liu, X. TCP2 positively regulates HY5/HYH and photomorphogenesis in Arabidopsis. J Exp Bot 67, 775–785 (2016).Lau, O. S. & Deng, X. W. Plant hormone signaling lightens up: integrators of light and hormones. Curr Opin Plant Biol 13, 571–577 (2010).Oyama, T., Shimura, Y. & Okada, K. The Arabidopsis HY5 gene encodes a bZIP protein that regulates stimulus-induced development of root and hypocotyl. Genes Dev 11, 2983–2995 (1997).Ahmed, N. U., Park, J. I., Jung, H. J., Hur, Y. & Nou, I. S. Anthocyanin biosynthesis for cold and freezing stress tolerance and desirable color in Brassica rapa. Funct Integr Genomics 15, 383–394 (2015).Catalá, R., Medina, J. & Salinas, J. Integration of low temperature and light signaling during cold acclimation response in Arabidopsis. Proc Natl Acad Sci USA 108, 16475–16480 (2011).Schulz, E., Tohge, T., Zuther, E., Fernie, A. R. & Hincha, D. K. Natural variation in flavonol and anthocyanin metabolism during cold acclimation in Arabidopsis thaliana accessions. Plant Cell Environ 38, 1658–1672 (2015).Perea-Resa, C., Rodríguez-Milla, M. A., Iniesto, E., Rubio, V. & Salinas, J. Prefoldins Negatively Regulate Cold Acclimation in Arabidopsis thaliana by Promoting Nuclear Proteasome-Mediated HY5 Degradation. Mol Plant 10, 791–804 (2017).Solfanelli, C., Poggi, A., Loreti, E., Alpi, A. & Perata, P. Sucrose-Specific Induction of the Anthocyanin Biosynthetic Pathway in Arabidopsis. Plant Physiol 140, 637–646 (2006).Reis, R. S., Eamens, A. L. & Waterhouse, P. M. Missing Pieces in the Puzzle of Plant MicroRNAs. Trends Plant Sci 20, 721–728 (2015).Kumar, R. Role of microRNAs in biotic and abiotic stress responses in crop plants. Appl Biochem Biotech 174, 93–115 (2014).Ma, C., Burd, S. & Lers, A. miR408 is involved in abiotic stress responses in Arabidopsis. Plant J 84, 169–187 (2015).Song, L., Axtell, M. J. & Fedoroff, N. V. RNA secondary structural determinants of miRNA precursor processing in Arabidopsis. Curr Biol 20, 37–41 (2010).Bracken, C. P. et al. Global analysis of the mammalian RNA degradome reveals widespread miRNA-dependent and miRNA-independent endonucleolytic cleavage. Nucleic Acids Res 39, 5658–5668 (2011).Gurtan, A. M., Lu, V., Bhutkar, A. & Sharp, P. A. In vivo structure-function analysis of human Dicer reveals directional processing of precursor miRNAs. RNA 18, 1116–1122 (2012).Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet Journal 17, 10–12 (2011).Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq-2. Genome Biol 15, 550 (2014).Robinson, M. D. & Oshlack, A. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol 11, 3–r25 (2010).Griffiths-Jones, S. miRBase: microRNA sequences and annotation. Current protocols in bioinformatics 12, 9 (2010).Li, H. et al. 1000 Genome Project Data Processing Subgroup The sequence alignment/map format & SAMtools. Bioinformatics 25, 2078–2079 (2009).Quinlan, A. & Hall, I. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).Livak, K. J. & Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 25, 402–408 (2001).Llave, C., Xie, Z., Kasschau, K. D. & Carrington, J. C. Cleavage of Scarecrow-like mRNA targets directed by a class of Arabidopsis miRNA. Science 297, 2053–2056 (2002).Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10, 3–r25 (2009)

Estimating an area-level socioeconomic status index and its association with colonoscopy screening adherence.

Socioeconomic status (SES) is often considered a risk factor for health outcomes. SES is typically measured using individual variables of educational attainment, income, housing, and employment variables or a composite of these variables. Approaches to building the composite variable include using equal weights for each variable or estimating the weights with principal components analysis or factor analysis. However, these methods do not consider the relationship between the outcome and the SES variables when constructing the index. In this project, we used weighted quantile sum (WQS) regression to estimate an area-level SES index and its effect in a model of colonoscopy screening adherence in the Minnesota-Wisconsin Metropolitan Statistical Area. We considered several specifications of the SES index including using different spatial scales (e.g., census block group-level, tract-level) for the SES variables. We found a significant positive association (odds ratio = 1.17, 95% CI: 1.15-1.19) between the SES index and colonoscopy adherence in the best fitting model. The model with the best goodness-of-fit included a multi-scale SES index with 10 variables at the block group-level and one at the tract-level, with home ownership, race, and income among the most important variables. Contrary to previous index construction, our results were not consistent with an assumption of equal importance of variables in the SES index when explaining colonoscopy screening adherence. Our approach is applicable in any study where an SES index is considered as a variable in a regression model and the weights for the SES variables are not known in advance

Association between high school students’ cigarette smoking, asthma and related beliefs: a population-based study

Abstract Background Smoking has a detrimental effect on the symptoms and severity of asthma, a common chronic disease among adolescents. The purpose of this study was to examine the association between asthma and smoking among high school students and assess provider-patient communication with asthmatic adolescents regarding smoking and adolescents’ beliefs about the harms of smoking. Methods In fall 2014, data from high school students, ages 14–18 years, completing the 2009-2010 Virginia Youth Tobacco Survey (N = 1796) were used in descriptive analyses and multivariable logistic regression models adjusting for model-specific confounders as appropriate. Results Overall, an estimated 19 % of high school students in Virginia smoked and 16 % had asthma. Odds of smoking did not differ by asthma status; however, asthmatics had 1.5 times higher odds of being asked if they smoke (95 % CI 1.06–2.13) and being advised not to smoke by a health professional (95 % CI 1.10–2.14) compared to non-asthmatics. Asthmatics who believed second-hand smoke or smoking 1–5 cigarettes/day was not harmful had respectively 4.2 and 2.8 times higher odds of smoking than those who thought each was harmful. Further, asthmatics who thought smoking 1−2 years is safe had 3.4 times higher odds of smoking than those who did not (95 % CI 1.57–10.1). Conclusions While asthmatic adolescents are just as likely to smoke as non-asthmatics, less healthy beliefs about the risks of smoking increase the odds of smoking among asthmatics. Thus, targeted asthma-specific smoking prevention and education to change attitudes and beliefs could be an effective tool for adolescents

SES index weights estimated in the training set for variables using census block group and tract ESRI 2012 demographic data and American Community Survey 2009–2013 data.

<p>SES index weights estimated in the training set for variables using census block group and tract ESRI 2012 demographic data and American Community Survey 2009–2013 data.</p