<?xml version="1.0" encoding="UTF-8"?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:prism="http://prismstandard.org/namespaces/1.2/basic/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns="http://purl.org/rss/1.0/"><channel rdf:about="http://www.annalsofepidemiology.org/?rss=yes"><title>Annals of Epidemiology</title><description>Annals of Epidemiology RSS feed: Current Issue.     Annals of Epidemiology  is a peer reviewed, international journal devoted to  epidemiologic research  and methodological 
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   </description><link>http://www.annalsofepidemiology.org/?rss=yes</link><dc:publisher>Elsevier Inc.</dc:publisher><dc:language>en</dc:language><dc:rights> © 2013 Published by Elsevier Inc. All rights reserved. </dc:rights><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:issn>1047-2797</prism:issn><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:publicationDate>June 2013</prism:publicationDate><prism:copyright> © 2013 Published by Elsevier Inc. All rights reserved. </prism:copyright><prism:rightsAgent>healthpermissions@elsevier.com</prism:rightsAgent><items><rdf:Seq><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279713001075/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279713000951/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279713000902/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279713000872/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279713000859/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279713000537/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279713000896/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS104727971300094X/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279713000963/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279713000914/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279713000926/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279713000938/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279713000884/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279713001087/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279713001099/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279713001129/abstract?rss=yes"/></rdf:Seq></items></channel><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279713001075/abstract?rss=yes"><title>Editorial Board</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279713001075/abstract?rss=yes</link><description></description><dc:title>Editorial Board</dc:title><dc:creator></dc:creator><dc:identifier>10.1016/S1047-2797(13)00107-5</dc:identifier><dc:source>Annals of Epidemiology 23, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S1047-2797(13)X0005-5</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>IFC</prism:startingPage><prism:endingPage>IFC</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279713000951/abstract?rss=yes"><title>Bayesian estimation of the effective reproduction number for pandemic influenza A H1N1 in Guangdong Province, China</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279713000951/abstract?rss=yes</link><description>Abstract: Purpose: During the course of a pandemic, it is necessary to understand its transmissibility, which is often summarized by the effective reproduction number. Accurate estimation of the effective reproduction number (R) is of vital significance in real-time decision making for coping with pandemic influenza.Methods: We used daily case notification data in Guangdong Province, China, in conjunction with Bayesian inference of two different stochastic susceptible, infectious, recovered (SIR) models to estimate the effective reproduction number. The duration of infectiousness was taken from published literature, and the proportion of imported cases was obtained from individual-level data.Results: At the initial epidemic phase, 40% of the first 261 cases were not locally acquired. Explicitly accounting for imported cases and different infectious periods, the possible range of basic reproduction number was preliminarily estimated to be between 1.05 and 1.46. We showed how the daily case reports provided valuable information to estimate the effective reproduction number. We also found the potential delay in reporting had a relatively minor impact on estimating R.Conclusions: Our proposed models and findings provide a relevant contribution towards establishing a basis for monitoring the evolution of emerging infectious diseases in real time and understanding the characteristics of pandemic influenza A H1N1 in Guangdong Province.</description><dc:title>Bayesian estimation of the effective reproduction number for pandemic influenza A H1N1 in Guangdong Province, China</dc:title><dc:creator>Fen Yang, Lingling Yuan, Xuhui Tan, Cunrui Huang, Jun Feng</dc:creator><dc:identifier>10.1016/j.annepidem.2013.04.005</dc:identifier><dc:source>Annals of Epidemiology 23, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S1047-2797(13)X0005-5</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>301</prism:startingPage><prism:endingPage>306</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279713000902/abstract?rss=yes"><title>Hospitalized prenatal and childhood infections and obesity in Danish male conscripts</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279713000902/abstract?rss=yes</link><description>Abstract: Purpose: We examined the relation between early life infections and adult obesity.Methods: A cohort of Danish males who underwent mandatory army fitness examinations was studied. Hospitalizations for childhood infections and their mothers' hospitalization for infection during pregnancy were identified via the Danish National Registry of Patients. The outcome was obesity (body mass index ≥ 30 kg/m2) at conscription. We calculated prevalence odds ratios (OR) and 95% confidence intervals (CI) associating the obesity with whether the conscript had a hospitalization for infection up to age 5, and separately, whether the conscript's mother was hospitalized for an infection prenatally.Results: Of the 17,456 men, 13% had a childhood infection (8.2% of whom were obese, compared with 7.4% without childhood infection); 1.2% of conscripts were exposed to a prenatal infection (10% of whom were obese, compared with 7.4% without prenatal infection). For childhood infection, the adjusted OR was 1.21 (95% CI, 1.01–1.44); stratified analyses suggested the association may be greater among conscripts born preterm (adjusted OR, 2.08; 95% CI, 1.06–4.09), whereas among the conscripts who were full term, the adjusted OR was 1.15 (95% CI, 0.96–1.38). For prenatal infection, the adjusted OR was 1.34 (95% CI, 0.82–2.19).Conclusions: We found a small association between both prenatal and childhood infections and prevalent obesity in early adulthood, although the results may be partly explained by unmeasured confounders.</description><dc:title>Hospitalized prenatal and childhood infections and obesity in Danish male conscripts</dc:title><dc:creator>Noelle M. Cocoros, Timothy L. Lash, Mette Nørgaard, Dóra Körmendiné Farkas, Alfred DeMaria, Henrik Toft Sørensen</dc:creator><dc:identifier>10.1016/j.annepidem.2013.04.002</dc:identifier><dc:source>Annals of Epidemiology 23, 6 (2013)</dc:source><dc:date>2013-04-25</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2013-04-25</prism:publicationDate><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S1047-2797(13)X0005-5</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>307</prism:startingPage><prism:endingPage>313</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279713000872/abstract?rss=yes"><title>Early childhood diarrhea and cardiometabolic risk factors in adulthood: the Institute of Nutrition of Central America and Panama Nutritional Supplementation Longitudinal Study</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279713000872/abstract?rss=yes</link><description>Abstract: Background: Nutritional deficits in early life have been associated with a higher prevalence of the metabolic syndrome (MetS) in adulthood. Early childhood diarrhea contributes to undernutrition and may potentially increase the risk for adult noncommunicable diseases. Our objective was to examine associations between early childhood diarrhea burden and later development of MetS.Methods: We studied individuals who participated in the Institute of Nutrition of Central America and Panama Nutritional Supplementation Longitudinal Study (1969–1977) and were followed up in 2002–2004. We used logistic regression to determine associations of diarrhea burden at ages 0 to 6, 6 to 12, and 12 to 24 months with odds of MetS and elevations in its components as adults.Results: Among 389 adults age 25 to 42 years at follow-up, the prevalence of MetS was 29%. Adjusting for several confounders including adult body mass index (BMI), each absolute 1% increase in diarrhea burden at age 0 to 6 months (but not at other time periods) was associated with increased odds of MetS (odds ratio [OR], 1.03; 95% confidence interval [CI], 1.01–1.06). This was attributable primarily to associations with elevated blood pressure (OR, 1.03; 95% CI, 1.00–1.06) and waist circumference (OR, 1.03; 95% CI, 1.00–1.06).Conclusions: Childhood diarrhea burden at 0 to 6 months is associated with MetS in adulthood after controlling for childhood growth parameters and adult BMI.</description><dc:title>Early childhood diarrhea and cardiometabolic risk factors in adulthood: the Institute of Nutrition of Central America and Panama Nutritional Supplementation Longitudinal Study</dc:title><dc:creator>Mark D. DeBoer, David Chen, David R. Burt, Manuel Ramirez-Zea, Richard L. Guerrant, Aryeh D. Stein, Reynaldo Martorell, Max A. Luna</dc:creator><dc:identifier>10.1016/j.annepidem.2013.03.012</dc:identifier><dc:source>Annals of Epidemiology 23, 6 (2013)</dc:source><dc:date>2013-04-22</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2013-04-22</prism:publicationDate><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S1047-2797(13)X0005-5</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>314</prism:startingPage><prism:endingPage>320</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279713000859/abstract?rss=yes"><title>The association of whole grain consumption with incident type 2 diabetes: the Women's Health Initiative Observational Study</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279713000859/abstract?rss=yes</link><description>Abstract: Purpose: Whole grains may offer protection from diabetes by decreasing energy intake, preventing weight gain, and direct effects on insulin resistance. This study examined associations of whole and refined grains with incident type 2 diabetes (T2D) ascertained by self-reported medication use in a cohort of postmenopausal women.Methods: We included 72,215 women free of diabetes at baseline from the Women's Health Initiative Observational Study. Whole grain consumption was categorized as 0, less than 0.5, 0.5 to 1.0, 1.0 to less than 1.5, 1.5 to less than 2.0, and 2.0 or more servings per day. Proportional hazards regression was performed to estimate hazard ratios (HR) and 95% confidence intervals adjusting for potential confounders.Results: There were 3465 cases of incident T2D over median follow-up of 7.9 years. Adjusted for age and energy intake per day, successively increasing categories of whole grain consumption were associated with statistically significant reduced risk of incident T2D (HRs, 1.00, 0.83, 0.73, 0.69, 0.61, and 0.57; P for trend &lt; 0.0001). Results were attenuated after adjustment for confounders and other dietary components. The reduction in risk of T2D was greater among nonsmokers and those who maintained their weight within 5 pounds with higher consumption of whole grains than smokers and women who gained more weight.Conclusions: This large, prospective study found an inverse dose–response relationship between whole grain consumption and incident T2D in postmenopausal women.</description><dc:title>The association of whole grain consumption with incident type 2 diabetes: the Women's Health Initiative Observational Study</dc:title><dc:creator>Emily D. Parker, Simin Liu, Linda Van Horn, Leslie F. Tinker, James M. Shikany, Charles B. Eaton, Karen L. Margolis</dc:creator><dc:identifier>10.1016/j.annepidem.2013.03.010</dc:identifier><dc:source>Annals of Epidemiology 23, 6 (2013)</dc:source><dc:date>2013-04-22</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2013-04-22</prism:publicationDate><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S1047-2797(13)X0005-5</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>321</prism:startingPage><prism:endingPage>327</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279713000537/abstract?rss=yes"><title>Sociodemographic, clinical, and psychological factors associated with attrition in a prospective study of cardiovascular prevention: the Heart Strategies Concentrating on Risk Evaluation study</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279713000537/abstract?rss=yes</link><description>Abstract: Purpose: To identify factors associated with attrition in a longitudinal study of cardiovascular prevention.Methods: Demographic, clinical, and psychosocial variables potentially associated with attrition were investigated in 1841 subjects enrolled in the southwestern Pennsylvania Heart Strategies Concentrating on Risk Evaluation study. Attrition was defined as study withdrawal, loss to follow-up, or missing 50% or more of study visits.Results: Over 4 years of follow-up, 291 subjects (15.8%) met criteria for attrition. In multivariable regression models, factors that were independently associated with attrition were black race (odds ratio [OR], 2.21; 95% confidence interval [CI], 1.55–3.16; P &lt; .001), younger age (OR per 5-year increment, 0.88; 95% CI, 0.79–0.99; P &lt; .05), male gender (OR, 1.79; 95% CI, 1.27–2.54; P &lt; .05), no health insurance (OR, 2.04; 95% CI, 1.20–3.47; P &lt; .05), obesity (OR, 1.80; 95% CI, 1.07–3.02; P &lt; .05), CES-D depression score 16 or higher (OR, 2.02; 95% CI, 1.29–3.19; P &lt; .05), and higher ongoing life events questionnaire score (OR, 1.09; 95% CI, 1.04–1.13; P &lt; .001). Having a spouse/partner participating in the study was associated with lower odds of attrition (OR, 0.60; 95% CI, 0.37–0.97; P &lt; .05). A synergistic interaction was identified between black race and depression.Conclusions: Attrition over 4 years was influenced by sociodemographic, clinical, and psychological factors that can be readily identified at study entry. Recruitment and retention strategies targeting these factors may improve participant follow-up in longitudinal cardiovascular prevention studies.</description><dc:title>Sociodemographic, clinical, and psychological factors associated with attrition in a prospective study of cardiovascular prevention: the Heart Strategies Concentrating on Risk Evaluation study</dc:title><dc:creator>Claudia E. Bambs, Kevin E. Kip, Suresh R. Mulukutla, Aryan N. Aiyer, Cheryl Johnson, Lee Ann McDowell, Karen Matthews, Steven E. Reis</dc:creator><dc:identifier>10.1016/j.annepidem.2013.02.007</dc:identifier><dc:source>Annals of Epidemiology 23, 6 (2013)</dc:source><dc:date>2013-03-27</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2013-03-27</prism:publicationDate><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S1047-2797(13)X0005-5</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>328</prism:startingPage><prism:endingPage>333</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279713000896/abstract?rss=yes"><title>Assessing the component associations of the healthy worker survivor bias: occupational asbestos exposure and lung cancer mortality</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279713000896/abstract?rss=yes</link><description>Abstract: Background: The healthy worker survivor bias is well-recognized in occupational epidemiology. Three component associations are necessary for this bias to occur: i) prior exposure and employment status; ii) employment status and subsequent exposure; and iii) employment status and mortality. Together, these associations result in time-varying confounding affected by prior exposure. We illustrate how these associations can be assessed using standard regression methods.Methods: We use data from 2975 asbestos textile factory workers hired between January 1940 and December 1965 and followed for lung cancer mortality through December 2001.Results: At entry, median age was 24 years, with 42% female and 19% non-Caucasian. Over follow-up, 21% and 17% of person-years were classified as at work and exposed to any asbestos, respectively. For a 100 fiber-year/mL increase in cumulative asbestos, the covariate-adjusted hazard of leaving work decreased by 52% (95% confidence interval [CI], 46–58). The association between employment status and subsequent asbestos exposure was strong due to nonpositivity: 88.3% of person-years at work (95% CI, 87.0–89.5) were classified as exposed to any asbestos; no person-years were classified as exposed to asbestos after leaving work. Finally, leaving active employment was associated with a 48% (95% CI, 9–71) decrease in the covariate-adjusted hazard of lung cancer mortality.Conclusions: We found strong associations for the components of the healthy worker survivor bias in these data. Standard methods, which fail to properly account for time-varying confounding affected by prior exposure, may provide biased estimates of the effect of asbestos on lung cancer mortality under these conditions.</description><dc:title>Assessing the component associations of the healthy worker survivor bias: occupational asbestos exposure and lung cancer mortality</dc:title><dc:creator>Ashley I. Naimi, Stephen R. Cole, Michael G. Hudgens, M. Alan Brookhart, David B. Richardson</dc:creator><dc:identifier>10.1016/j.annepidem.2013.03.013</dc:identifier><dc:source>Annals of Epidemiology 23, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S1047-2797(13)X0005-5</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>334</prism:startingPage><prism:endingPage>341</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS104727971300094X/abstract?rss=yes"><title>Waist-to-thigh ratio is a predictor of internal organ cancers in humans: findings from a cohort study</title><link>http://www.annalsofepidemiology.org/article/PIIS104727971300094X/abstract?rss=yes</link><description>Abstract: Objective: Studies have shown that some specific body measures are associated with the occurrence of cancers. Few studies have demonstrated the relationship with more comprehensive approaches. This study aims to explore body measures and the combinations associated with internal organ cancers.Methods: Three-dimensional anthropometric body surface scanning data collected 10,215 participants from the health examination department in a medical center of Taiwan during 2000–2010. Follow-up was conducted for an average of 8 years, and 244 internal organ cancer cases were identified.Results: An increased risk of internal organ cancers was observed among the subjects with larger waist circumference/smaller thigh circumference, in which waist-to-thigh ratio (WTR) was constructed. Comparing the subjects in the fourth quartile for WTR to the subjects in the first quartile with multiple Cox regression analysis yielded a hazard ratio of 1.842 (95% confidence interval, 1.131∼2.999). The association between WTR quartile and internal organ cancers was stronger among male participants, older participants, and participants with chronic conditions.Conclusions: The study has revealed that WTR is the most significant predictor for the occurrence of cancer in Asian populations. Because it is easy to measure and open to modification, WTR may be more useful in clinical and preventive medicine in the future.</description><dc:title>Waist-to-thigh ratio is a predictor of internal organ cancers in humans: findings from a cohort study</dc:title><dc:creator>Kuang-Hung Hsu, Chia-Pang Shih, Pei-Ju Liao</dc:creator><dc:identifier>10.1016/j.annepidem.2013.04.004</dc:identifier><dc:source>Annals of Epidemiology 23, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S1047-2797(13)X0005-5</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>342</prism:startingPage><prism:endingPage>348</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279713000963/abstract?rss=yes"><title>Risk of non-Hodgkin lymphoma in relation to tricyclic antidepressant use</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279713000963/abstract?rss=yes</link><description>Abstract: Purpose: We investigated the relationship between use of tricyclic antidepressants (TCAs) and risk of non-Hodgkin lymphoma (NHL). Previous studies provided some evidence of an association, but did not assess risk of NHL subtypes.Methods: Cases and controls were members of Group Health, an integrated healthcare delivery system. Cases were persons diagnosed with NHL between 1980 and 2011 at age 25 years or older; eight control subjects were matched to each case on age, sex, and length of enrollment. Information on previous TCA use was ascertained from automated pharmacy data. Conditional logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (95% CIs) for NHL, overall and for common subtypes, for various patterns of TCA use.Results: We identified 2768 cases and 22,127 matched control subjects. We did not observe an appreciably increased risk of NHL among TCA ever-users compared to non-users (OR, 1.1; 95% CI, 1.0–1.2). Overall risk of NHL was associated to at most a small degree with longer-term use (OR, 1.2; 95% CI, 1.0–1.4; ≥10 prescriptions), high-dose use (OR, 1.1; 95% CI, 0.8–1.5; ≥50 mg), or non-recent use (OR, 1.0; 95% CI, 0.9 = 1.2; &gt;5 years previously). TCA use was not associated with NHL subtypes, except chronic lymphocytic leukemia/small lymphocytic lymphoma (OR, 1.5; 95% CI, 1.1–2.0; longer-term use).Conclusions: We found little evidence that the use of TCAs increases the risk of NHL overall or for specific common subtypes of NHL.</description><dc:title>Risk of non-Hodgkin lymphoma in relation to tricyclic antidepressant use</dc:title><dc:creator>Sarah J. Lowry, Jessica Chubak, Oliver W. Press, Barbara McKnight, Noel S. Weiss</dc:creator><dc:identifier>10.1016/j.annepidem.2013.04.006</dc:identifier><dc:source>Annals of Epidemiology 23, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S1047-2797(13)X0005-5</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>349</prism:startingPage><prism:endingPage>354</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279713000914/abstract?rss=yes"><title>Do the psychosocial risks associated with television viewing increase mortality? Evidence from the 2008 General Social Survey–National Death Index dataset</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279713000914/abstract?rss=yes</link><description>Abstract: Background: Television viewing is associated with an increased risk of mortality, which could be caused by a sedentary lifestyle, the content of television programming (e.g., cigarette product placement or stress-inducing content), or both.Methods: We examined the relationship between self-reported hours of television viewing and mortality risk over 30 years in a representative sample of the American adult population using the 2008 General Social Survey–National Death Index dataset. We also explored the intervening variable effect of various emotional states (e.g., happiness) and beliefs (e.g., trust in government) of the relationship between television viewing and mortality.Results: We find that, for each additional hour of viewing, mortality risks increased 4%. Given the mean duration of television viewing in our sample, this amounted to about 1.2 years of life expectancy in the United States. This association was tempered by a number of potential psychosocial mediators, including self-reported measures of happiness, social capital, or confidence in institutions. Although none of these were clinically significant, the combined mediation power was statistically significant (P &lt; .001).Conclusions: Television viewing among healthy adults is correlated with premature mortality in a nationally representative sample of U.S. adults, and this association may be partially mediated by programming content related to beliefs or affective states. However, this mediation effect is the result of many small changes in psychosocial states rather than large effects from a few factors.</description><dc:title>Do the psychosocial risks associated with television viewing increase mortality? Evidence from the 2008 General Social Survey–National Death Index dataset</dc:title><dc:creator>Peter Muennig, Zohn Rosen, Gretchen Johnson</dc:creator><dc:identifier>10.1016/j.annepidem.2013.03.014</dc:identifier><dc:source>Annals of Epidemiology 23, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S1047-2797(13)X0005-5</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>355</prism:startingPage><prism:endingPage>360</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279713000926/abstract?rss=yes"><title>Sleep duration and all-cause mortality: a critical review of measurement and associations</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279713000926/abstract?rss=yes</link><description>Abstract: Purpose: Variation in sleep duration has been linked with mortality risk. The purpose of this review is to provide an updated evaluation of the literature on sleep duration and mortality, including a critical examination of sleep duration measurement and an examination of correlates of self-reported sleep duration.Methods: We conducted a systematic search of studies reporting associations between sleep duration and all-cause mortality and extracted the sleep duration measure and the measure(s) of association.Results: We identified 42 prospective studies of sleep duration and mortality drawing on 35 distinct study populations worldwide. Unlike previous reviews, we find that the published literature does not support a consistent finding of an association between self-reported sleep duration and mortality. Most studies have employed survey measures of sleep duration, which are not highly correlated with estimates based on physiologic measures.Conclusions: Despite a large body of literature, it is premature to conclude, as previous reviews have, that a robust, U-shaped association between sleep duration and mortality risk exists across populations. Careful attention must be paid to measurement, response bias, confounding, and reverse causation in the interpretation of associations between sleep duration and mortality.</description><dc:title>Sleep duration and all-cause mortality: a critical review of measurement and associations</dc:title><dc:creator>Lianne M. Kurina, Martha K. McClintock, Jen-Hao Chen, Linda J. Waite, Ronald A. Thisted, Diane S. Lauderdale</dc:creator><dc:identifier>10.1016/j.annepidem.2013.03.015</dc:identifier><dc:source>Annals of Epidemiology 23, 6 (2013)</dc:source><dc:date>2013-04-25</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2013-04-25</prism:publicationDate><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S1047-2797(13)X0005-5</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>361</prism:startingPage><prism:endingPage>370</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279713000938/abstract?rss=yes"><title>The adoption of chronic fatigue syndrome/myalgic encephalomyelitis case definitions to assess prevalence: a systematic review</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279713000938/abstract?rss=yes</link><description>Abstract: Purpose: Prevalence estimates have been based on several case definitions of chronic fatigue syndrome (CFS). The purpose of this work is to provide a rigorous overview of their application in prevalence research.Methods: A systematic review of primary studies reporting the prevalence of CFS since 1990 was conducted. Studies were summarized according to study design, prevalence estimates, and case definition used to ascertain cases.Results: Thirty-one studies were retrieved, and eight different case definitions were found. Early estimates of CFS prevalence were based on the 1988 Centers for Disease Control and Prevention, Australian, and Oxford. The 1994 Centers for Disease Control and Prevention, however, has been adopted internationally, as a general standard. Only one study has reported prevalence according to the more recent, Canadian Consensus Criteria. Additional estimates were also found according to definitions by Ho-Yen, the 2005 Centers for Disease Control and Prevention empirical definition, and an epidemiological case definition.Conclusions: Advances in clinical case definitions during the past 10 years such as the Canadian Consensus Criteria have received little attention in prevalence research. Future assessments of prevalence should consider adopting more recent developments, such as the newly available International Consensus Criteria. This move could improve the surveillance of more specific cases found within CFS.</description><dc:title>The adoption of chronic fatigue syndrome/myalgic encephalomyelitis case definitions to assess prevalence: a systematic review</dc:title><dc:creator>Samantha Johnston, Ekua W. Brenu, Donald R. Staines, Sonya Marshall-Gradisnik</dc:creator><dc:identifier>10.1016/j.annepidem.2013.04.003</dc:identifier><dc:source>Annals of Epidemiology 23, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S1047-2797(13)X0005-5</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>371</prism:startingPage><prism:endingPage>376</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279713000884/abstract?rss=yes"><title>Appalachian versus non-Appalachian U.S. traffic fatalities, 2008–2010</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279713000884/abstract?rss=yes</link><description>Abstract: Purpose: Although myriad health disparities exist in Appalachia, limited research has examined traffic fatalities in the region. This study compared traffic fatality rates in Appalachia and the non-Appalachian United States.Methods: Fatality Analysis Reporting System and Census data from 2008 through 2010 were used to calculate traffic fatality rates. Poisson models were used to estimate unadjusted (rate ratio [RR]) and adjusted rate ratios, controlling for age, gender, and county-specific population density levels.Results: The Appalachian traffic fatality rate was 45% (95% confidence interval [CI], 1.42–1.47) higher than the non-Appalachian rate. Although only 29% of fatalities occur in rural counties in non-Appalachia versus 48% in Appalachia, rates in rural counties were similar (RR, 0.97; 95% CI, 0.95–1.00). However, the rate for urban, Appalachian counties was 42% (95% CI, 1.38–1.45) higher than among urban, non-Appalachian counties. Appalachian rates were higher for passenger vehicle drivers, motorcyclists, and all terrain vehicle riders, regardless of rurality, as well as for passenger vehicle passengers overall and for urban counties. Conversely, Appalachia experienced lower rates among pedestrians and bicyclists, regardless of rurality.Conclusions: Disparities in traffic fatality rates exist in Appalachia. Although elevated rates are partially explained by the proportion of residents living in rural settings, overall rates in urban Appalachia were consistently higher than in urban non-Appalachia.</description><dc:title>Appalachian versus non-Appalachian U.S. traffic fatalities, 2008–2010</dc:title><dc:creator>Motao Zhu, Songzhu Zhao, Kelly K. Gurka, Sahiti Kandati, Jeffrey H. Coben</dc:creator><dc:identifier>10.1016/j.annepidem.2013.04.001</dc:identifier><dc:source>Annals of Epidemiology 23, 6 (2013)</dc:source><dc:date>2013-04-25</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2013-04-25</prism:publicationDate><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S1047-2797(13)X0005-5</prism:issueIdentifier><prism:section>Brief Communication</prism:section><prism:startingPage>377</prism:startingPage><prism:endingPage>380</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279713001087/abstract?rss=yes"><title>Contents</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279713001087/abstract?rss=yes</link><description></description><dc:title>Contents</dc:title><dc:creator></dc:creator><dc:identifier>10.1016/S1047-2797(13)00108-7</dc:identifier><dc:source>Annals of Epidemiology 23, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S1047-2797(13)X0005-5</prism:issueIdentifier><prism:section>Frontmatter</prism:section><prism:startingPage>A1</prism:startingPage><prism:endingPage>A1</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279713001099/abstract?rss=yes"><title>Masthead</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279713001099/abstract?rss=yes</link><description></description><dc:title>Masthead</dc:title><dc:creator></dc:creator><dc:identifier>10.1016/S1047-2797(13)00109-9</dc:identifier><dc:source>Annals of Epidemiology 23, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S1047-2797(13)X0005-5</prism:issueIdentifier><prism:section>Frontmatter</prism:section><prism:startingPage>A2</prism:startingPage><prism:endingPage>A2</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279713001129/abstract?rss=yes"><title>Information for Authors</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279713001129/abstract?rss=yes</link><description></description><dc:title>Information for Authors</dc:title><dc:creator></dc:creator><dc:identifier>10.1016/S1047-2797(13)00112-9</dc:identifier><dc:source>Annals of Epidemiology 23, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>23</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S1047-2797(13)X0005-5</prism:issueIdentifier><prism:section>Frontmatter</prism:section><prism:startingPage>A6</prism:startingPage><prism:endingPage>A7</prism:endingPage></item></rdf:RDF>