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<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 development. 
The journal emphasizes the application of epidemiologic methods to issues that affect the distribution and determinants of human illness 
in diverse contexts. Its primary focus is on chronic and acute conditions of diverse etiologies and of major importance to clinical medicine, 
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   acepidemiology.org  .   </description><link>http://www.annalsofepidemiology.org/?rss=yes</link><dc:publisher>Elsevier Inc.</dc:publisher><dc:language>en</dc:language><dc:rights> © 2012 Published by Elsevier Inc. All rights reserved. </dc:rights><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:issn>1047-2797</prism:issn><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:publicationDate>May 2012</prism:publicationDate><prism:copyright> © 2012 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/PIIS1047279712000695/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279712000439/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279712000026/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279712000464/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279712000427/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279712000178/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279712000063/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279712000415/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279712000221/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279712000105/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS104727971200018X/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279712000403/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279712000452/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279712000701/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279712000713/abstract?rss=yes"/><rdf:li rdf:resource="http://www.annalsofepidemiology.org/article/PIIS1047279712000725/abstract?rss=yes"/></rdf:Seq></items></channel><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279712000695/abstract?rss=yes"><title>Editorial Board</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279712000695/abstract?rss=yes</link><description></description><dc:title>Editorial Board</dc:title><dc:creator></dc:creator><dc:identifier>10.1016/S1047-2797(12)00069-5</dc:identifier><dc:source>Annals of Epidemiology 22, 5 (2012)</dc:source><dc:date>2012-05-01</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2012-05-01</prism:publicationDate><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:issueIdentifier>S1047-2797(11)X0016-9</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/PIIS1047279712000439/abstract?rss=yes"><title>Coronary Death and Myocardial Infarction among Hispanics in the Northern Manhattan Study: Exploring the Hispanic Paradox</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279712000439/abstract?rss=yes</link><description>Purpose: Prior studies have reported that Hispanics have lower cardiovascular disease (CVD) mortality despite a higher burden of risk factors. We examined whether Hispanic ethnicity was associated with a lower risk of nonfatal myocardial infarction (MI) coronary death (CD) and vascular death.Methods: A total of 2671 participants in the Northern Manhattan Study without clinical CVD were prospectively evaluated. Cox models were used to calculate hazard ratios (HR) and 95% confidence intervals (CI) for the association of race–ethnicity with nonfatal MI, CD, and vascular death after adjusting for demographic and CVD risk factors.Results: Mean age was 68.8 (10.4) years; 52.8% were Hispanic (88% Caribbean-Hispanic). Hispanics were more likely to have hypertension (73.1% vs. 62.2%, p &lt; .001) and diabetes (22.0% vs. 13.3%, p &lt; .001), and less likely to perform any physical activity (50.1% vs. 69.2%, p &lt; .001) compared to non-Hispanic whites (NHW). During a mean 10 years of follow-up there were 154 nonfatal MIs, 186 CD, and 386 vascular deaths. In fully adjusted models, Hispanics had a lower risk of CD (adjusted HR = 0.36, 95% CI: 0.21–0.60), and vascular death (adjusted HR = 0.62, 95% CI: 0.43–0.89), but not nonfatal MI (adjusted HR = 0.95, 95% CI: 0.56–1.60) when compared to NHW.Conclusions: We found a “Hispanic paradox” for coronary and vascular deaths, but not nonfatal MI.</description><dc:title>Coronary Death and Myocardial Infarction among Hispanics in the Northern Manhattan Study: Exploring the Hispanic Paradox</dc:title><dc:creator>Joshua Z. Willey, Carlos J. Rodriguez, Yeseon Park Moon, Myunghee C. Paik, Marco R. Di Tullio, Shunichi Homma, Ralph L. Sacco, Mitchell S.V. Elkind</dc:creator><dc:identifier>10.1016/j.annepidem.2012.02.014</dc:identifier><dc:source>Annals of Epidemiology 22, 5 (2012)</dc:source><dc:date>2012-03-19</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2012-03-19</prism:publicationDate><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:issueIdentifier>S1047-2797(11)X0016-9</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>303</prism:startingPage><prism:endingPage>309</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279712000026/abstract?rss=yes"><title>Metabolic Syndrome and 16-Year Cognitive Decline in Community-Dwelling Older Adults</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279712000026/abstract?rss=yes</link><description>Purpose: To determine whether metabolic syndrome is associated with accelerated cognitive decline in community-dwelling older adults.Methods: A longitudinal study of 993 adults (mean 66.8 ± 8.7 years) from the Rancho Bernardo Study. Metabolic syndrome components, defined by 2001 NCEP-ATP III criteria, were measured in 1984-1987. Cognitive function was first assessed in 1988-1992. Cognitive assessments were repeated approximately every 4 years, for a maximum 16-year follow-up. Mixed-effects models examined longitudinal rate of cognitive decline by metabolic syndrome status, controlling for factors plausibly associated with cognitive function (diabetes, inflammation).Results: Metabolic syndrome was more common in men than women (14% vs. 9%, p = .01). In women, metabolic syndrome was associated with greater executive function and long-term memory decline. These associations did not differ by inflammatory biomarker levels. Diabetes did not alter the association of metabolic syndrome with long-term recall but modified the association with executive function: metabolic syndrome was associated with accelerated executive function decline in diabetic women only. Metabolic syndrome was not related to rate of decline on any cognitive measure in men.Conclusions: Metabolic syndrome was a risk factor for accelerated cognitive decline, but only in women. Prevention of metabolic syndrome may aid in maintenance of cognitive function with age.</description><dc:title>Metabolic Syndrome and 16-Year Cognitive Decline in Community-Dwelling Older Adults</dc:title><dc:creator>Linda K. McEvoy, Gail A. Laughlin, Elizabeth Barrett-Connor, Jaclyn Bergstrom, Donna Kritz-Silverstein, Claudia Der-Martirosian, Denise von Mühlen</dc:creator><dc:identifier>10.1016/j.annepidem.2011.12.003</dc:identifier><dc:source>Annals of Epidemiology 22, 5 (2012)</dc:source><dc:date>2012-01-30</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2012-01-30</prism:publicationDate><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:issueIdentifier>S1047-2797(11)X0016-9</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>310</prism:startingPage><prism:endingPage>317</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279712000464/abstract?rss=yes"><title>Bodybuilding, Energy, and Weight-Loss Supplements Are Associated With Deployment and Physical Activity in U.S. Military Personnel</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279712000464/abstract?rss=yes</link><description>Purpose: The characteristics of U.S. military personnel who use dietary supplements have not been well described. This study aimed to determine whether deployment experience and physical activity were associated with the use of bodybuilding, energy, or weight-loss supplement among U.S. military personnel.Methods: Self-reported data from active-duty, Reserve, and National Guard participants of the Millennium Cohort Study collected from 2007–2008 (n = 106,698) on supplement use, physical activity, and other behavioral data were linked with deployment and demographic data. We used multivariable logistic regression sex-stratified models to compare the adjusted odds of each type of supplement use among those with deployment experience in support of operations in Iraq or Afghanistan and those engaged in aerobic or strength-training activities.Results: Overall, 46.7% of participants reported using at least one type of supplement, and 22.0% reported using multiple supplements. Male deployers were more likely to use bodybuilding supplements, whereas female deployers were more likely to use weight-loss supplements. Physically active and younger subjects reported all types of supplement use. Men and women reporting 5 or less hours of sleep per night were more likely to use energy supplements.Conclusions: The high prevalence of supplement use and important characteristics found to be associated with their use, including deployment, physical activity, and suboptimal sleep, suggest focus areas for future research and adverse event monitoring.</description><dc:title>Bodybuilding, Energy, and Weight-Loss Supplements Are Associated With Deployment and Physical Activity in U.S. Military Personnel</dc:title><dc:creator>Isabel G. Jacobson, Jaime L. Horton, Besa Smith, Timothy S. Wells, Edward J. Boyko, Harris R. Lieberman, Margaret A.K. Ryan, Tyler C. Smith, Millennium Cohort Study Team</dc:creator><dc:identifier>10.1016/j.annepidem.2012.02.017</dc:identifier><dc:source>Annals of Epidemiology 22, 5 (2012)</dc:source><dc:date>2012-03-26</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2012-03-26</prism:publicationDate><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:issueIdentifier>S1047-2797(11)X0016-9</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>318</prism:startingPage><prism:endingPage>330</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279712000427/abstract?rss=yes"><title>Health Behaviors Associated With Use of Body Building, Weight Loss, and Performance Enhancing Supplements</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279712000427/abstract?rss=yes</link><description>Purpose: To identify health-related behaviors associated with potentially harmful dietary supplements (DS) - body building (BB), weight loss (WL) and performance enhancing (PE), explore common reasons and sources of information for DS use.Methods: Based on the 2005 Survey of 16,146 U.S. military personnel, BB users were dichotomized as yes (regular use - taking any supplement of BB at least once a week in past 12 months) or no; similarly defined for WL and PE. Weighted logistic regression models are used.Results: BB, WL and PE were used by 19.4%, 17.0%, and 8.0% of participants, respectively. Significantly more users were overweight or obese: BMI ≥25 (vs. BMI&lt;25); heavy drinkers (vs. abstainers); and users of taking steroids in their lifetime (vs. not). Most common reasons of BB, WL, and PE users wanted to increase muscle mass, lose weight, and improve physical performance (BB: 45.8%, WL: 54.8%, PE: 38.5%). Fewer than 30% discussed dietary supplements use with their healthcare providers. The leading source of dietary supplements information (BB: 27.8%, WL: 23.6%, PE: 30.0%) was magazines.Conclusions: The dietary supplements: BB, WL and PE were used by significant proportions of service members, and associated with risk-taking behaviors that may affect overall military readiness and public health.</description><dc:title>Health Behaviors Associated With Use of Body Building, Weight Loss, and Performance Enhancing Supplements</dc:title><dc:creator>Tzu-Cheg Kao, Patricia A. Deuster, Daniel Burnett, Mark Stephens</dc:creator><dc:identifier>10.1016/j.annepidem.2012.02.013</dc:identifier><dc:source>Annals of Epidemiology 22, 5 (2012)</dc:source><dc:date>2012-03-14</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2012-03-14</prism:publicationDate><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:issueIdentifier>S1047-2797(11)X0016-9</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>331</prism:startingPage><prism:endingPage>339</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279712000178/abstract?rss=yes"><title>Breast Density, Body Mass Index, and Risk of Tumor Marker-Defined Subtypes of Breast Cancer</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279712000178/abstract?rss=yes</link><description>Purpose: Breast density and body mass index (BMI) are correlated attributes and are both potentially modifiable risk factors for breast cancer. However, relationships between these factors and risk of molecularly-defined subtypes of breast cancer have not been established.Methods: We used breast density and BMI data collected by the Breast Cancer Surveillance Consortium from 1,054,466 women ages 40 to 84 years receiving mammography, including 13,797 women subsequently diagnosed with breast cancer. Cases were classified into three groups on the basis of expression of the estrogen receptor (ER), progesterone receptor (PR), and HER2:1) ER-positive (ER+, n = 10,026), 2) HER2-expressing (ER-negative/PR-negative/HER2-positive, n = 308), or triple-negative (ER-negative/PR-negative/HER2-negative, n = 705). Using Cox regression, we evaluated subtype-specific associations with breast density and BMI.Results: Breast density was similarly positively associated with risk of all subtypes, especially among women ages 40 to 64 years. BMI was positively associated with risks of ER+ and triple-negative breast cancer in women ages 50 to 84 who were not users of hormone therapy.Conclusions: Breast density is positively associated with breast cancer risk, regardless of disease subtype. Associations with BMI appear to vary more by breast cancer subtype. Additional studies are needed to confirm and further characterize risk factors for HER2-expressing and triple-negative breast cancer.</description><dc:title>Breast Density, Body Mass Index, and Risk of Tumor Marker-Defined Subtypes of Breast Cancer</dc:title><dc:creator>Amanda I. Phipps, Diana S.M. Buist, Kathleen E. Malone, William E. Barlow, Peggy L. Porter, Karla Kerlikowske, Ellen S. O'Meara, Christopher I. Li</dc:creator><dc:identifier>10.1016/j.annepidem.2012.02.002</dc:identifier><dc:source>Annals of Epidemiology 22, 5 (2012)</dc:source><dc:date>2012-02-27</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2012-02-27</prism:publicationDate><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:issueIdentifier>S1047-2797(11)X0016-9</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>340</prism:startingPage><prism:endingPage>348</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279712000063/abstract?rss=yes"><title>Management of Obesity in the National Health and Nutrition Examination Survey (NHANES), 2007–2008</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279712000063/abstract?rss=yes</link><description>Purpose: The prevalence of obesity has been increasing in the United States. We set out to investigate the use of pharmacologic and non-pharmacologic therapy for the treatment of obesity in recent years.Methods: We included 2630 men and 2702 women who took part in the National Health and Nutrition Examination Survey from 2007 to 2008. We analyzed their demographic and anthropometric data and their weight and drug history.Results: A total of 45.9% of men and 45.0% of women were candidates for treatment (body mass index ≥30 kg/m2, or ≥27 kg/m2 with risk factors). Among these participants, 85.1% considered themselves overweight, 90.1% would like to lose weight, 61.9% had dietary changes, 36.5% exercised, 3.7% took nonprescription drugs, and 2.2% took prescription drugs to control weight during the preceding year. During the preceding month, 0.5% and 0.1% of participants were taking phentermine and orlistat, respectively. There were no participants on sibutramine.Conclusions: Although obesity is highly prevalent, only a small percentage of obese Americans are on anti-obesity medication. The withdrawal of sibutramine would have minimal impact on the general population. There is a need for more lifestyle changes in the majority of obese individuals.</description><dc:title>Management of Obesity in the National Health and Nutrition Examination Survey (NHANES), 2007–2008</dc:title><dc:creator>Nithushi R. Samaranayake, Kwok L. Ong, Raymond Y.H. Leung, Bernard M.Y. Cheung</dc:creator><dc:identifier>10.1016/j.annepidem.2012.01.001</dc:identifier><dc:source>Annals of Epidemiology 22, 5 (2012)</dc:source><dc:date>2012-02-03</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2012-02-03</prism:publicationDate><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:issueIdentifier>S1047-2797(11)X0016-9</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>349</prism:startingPage><prism:endingPage>353</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279712000415/abstract?rss=yes"><title>Evaluating Consistency in Repeat Surveys of Injection Drug Users Recruited by Respondent-Driven Sampling in the Seattle Area: Results from the NHBS-IDU1 and NHBS-IDU2 Surveys</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279712000415/abstract?rss=yes</link><description>Purpose: We compared data from two respondent-driven sampling (RDS) surveys of Seattle-area injection drug users (IDU) to evaluate consistency in repeat RDS surveys.Methods: The RDS-adjusted estimates for 16 key sociodemographic, drug-related, sexual behavior, and HIV- and hepatitis C virus-related variables were compared in the 2005 and the 2009 National HIV Behavioral Surveillance system surveys (NHBS-IDU1 and NHBS-IDU2). Time trends that might influence the comparisons were assessed by the use of data from reported HIV cases in IDU, surveys of needle exchange users, and two previous IDU studies.Results: NHBS-IDU2 participants were more likely than NHBS-IDU1 participants to report older age, heroin as their primary injection drug, male-to-male sex, unprotected sex with a partner of nonconcordant HIV status, and to self-report HIV-positive status. NHBS-IDU2 participants were less likely to report residence in downtown Seattle, amphetamine injection, and a recent HIV test. Time trends among Seattle-area IDU in age, male-to-male sex, and HIV testing could have influenced these differences.Conclusions: The number and magnitude of the estimated differences between the two RDS surveys appeared to describe materially different populations. This could be a result of changes in the characteristics of Seattle-area IDU over time, of accessing differing subpopulations of Seattle IDU, or of high variability in RDS measurements.</description><dc:title>Evaluating Consistency in Repeat Surveys of Injection Drug Users Recruited by Respondent-Driven Sampling in the Seattle Area: Results from the NHBS-IDU1 and NHBS-IDU2 Surveys</dc:title><dc:creator>Richard D. Burt, Hanne Thiede</dc:creator><dc:identifier>10.1016/j.annepidem.2012.02.012</dc:identifier><dc:source>Annals of Epidemiology 22, 5 (2012)</dc:source><dc:date>2012-03-16</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2012-03-16</prism:publicationDate><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:issueIdentifier>S1047-2797(11)X0016-9</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>354</prism:startingPage><prism:endingPage>363</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279712000221/abstract?rss=yes"><title>Nonsignificance Plus High Power Does Not Imply Support for the Null Over the Alternative</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279712000221/abstract?rss=yes</link><description>This article summarizes arguments against the use of power to analyze data, and illustrates a key pitfall: Lack of statistical significance (e.g., p &gt; .05) combined with high power (e.g., 90%) can occur even if the data support the alternative more than the null. This problem arises via selective choice of parameters at which power is calculated, but can also arise if one computes power at a prespecified alternative. As noted by earlier authors, power computed using sample estimates (“observed power”) replaces this problem with even more counterintuitive behavior, because observed power effectively double counts the data and increases as the P value declines. Use of power to analyze and interpret data thus needs more extensive discouragement.</description><dc:title>Nonsignificance Plus High Power Does Not Imply Support for the Null Over the Alternative</dc:title><dc:creator>Sander Greenland</dc:creator><dc:identifier>10.1016/j.annepidem.2012.02.007</dc:identifier><dc:source>Annals of Epidemiology 22, 5 (2012)</dc:source><dc:date>2012-03-05</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2012-03-05</prism:publicationDate><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:issueIdentifier>S1047-2797(11)X0016-9</prism:issueIdentifier><prism:section></prism:section><prism:startingPage>364</prism:startingPage><prism:endingPage>368</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279712000105/abstract?rss=yes"><title>Not Continuing Along Previous Lines: Exploring How New Directions Emerge in Epidemiologic Research</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279712000105/abstract?rss=yes</link><description>Epidemiologic (and other) research is often incremental: Each new study in a particular etiologic path replicates previous findings, or not, and extends our knowledge a little bit or, more rarely, a lot. This is the process Kuhn referred to as normal science, wherein research is guided by a dominant paradigm theory that provides the foundation for future work, and that future work is largely a process of elaboration of the dominant paradigm . We teach our students to examine the evidence for gaps or for logical extensions of a line of thought. We believe, with ample evidence, that implementing the next incremental advance is the safest route to obtaining research funding and achieving peer-reviewed publication. Reviewers for grant panels and journals look for the justification, that is, the foundation in current knowledge that would make spending money or publishing an article seem justified. Rationale leads to hypothesis, which leads to study design. It’s all very thoughtful and considered and sensible and yields new information, albeit slowly. The requirement of “replication” enforces this process because we are taught to believe research findings only after there is an adequate number of studies with confirmatory, or at least compatible, results.</description><dc:title>Not Continuing Along Previous Lines: Exploring How New Directions Emerge in Epidemiologic Research</dc:title><dc:creator>Sandra I. Sulsky, Nancy Kreiger, Robert E. Mckeown</dc:creator><dc:identifier>10.1016/j.annepidem.2011.12.007</dc:identifier><dc:source>Annals of Epidemiology 22, 5 (2012)</dc:source><dc:date>2012-02-13</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2012-02-13</prism:publicationDate><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:issueIdentifier>S1047-2797(11)X0016-9</prism:issueIdentifier><prism:section>Notes and Views</prism:section><prism:startingPage>369</prism:startingPage><prism:endingPage>371</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS104727971200018X/abstract?rss=yes"><title>Risk of Gambling Onset in Youth Who are Younger than Same-Grade Peers</title><link>http://www.annalsofepidemiology.org/article/PIIS104727971200018X/abstract?rss=yes</link><description>Purpose: To assess whether a child’s age relative to the median age of classmates in the same grade is associated with the onset of gambling.Methods: Grade 7 students (n = 647) from 10 Montreal secondary schools were followed for 8 years. Relative age was expressed as years above or below the school-specific grade 7 median age. Hazard ratios and 95% confidence intervals (CI) were estimated for the association between relative age and age of gambling onset, with adjustment for sex, ethnicity, parent education, and impulsivity.Results: A greater proportion of students in the youngest quartile gambled compared with the oldest (85.8% vs 74.7%). Hazards of gambling onset for students younger than the median age were elevated after age 10.5 years, but hazards were protective beforehand. At age 17 years, for example, the hazard for gambling onset was 61% greater (95% CI 1.4–1.9) for youth who were 1 year younger, but at age 8 years the hazard was 23% lower (95% CI 0.7–0.9).Conclusions: Younger relative age may be a risk factor for gambling onset in older youth.</description><dc:title>Risk of Gambling Onset in Youth Who are Younger than Same-Grade Peers</dc:title><dc:creator>Nathalie Auger, Ernest Lo, Jennifer O’Loughlin</dc:creator><dc:identifier>10.1016/j.annepidem.2012.02.003</dc:identifier><dc:source>Annals of Epidemiology 22, 5 (2012)</dc:source><dc:date>2012-03-02</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2012-03-02</prism:publicationDate><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:issueIdentifier>S1047-2797(11)X0016-9</prism:issueIdentifier><prism:section>Brief Communication</prism:section><prism:startingPage>372</prism:startingPage><prism:endingPage>375</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279712000403/abstract?rss=yes"><title>Statistical Thinking in Epidemiology</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279712000403/abstract?rss=yes</link><description>When I received the request from an editor of Annals of Epidemiology inviting me to review a book on “methods,” the instant thought that flashed across my mind was “Why another book on statistical methods in epidemiology?” Little did I realize that this was not just another book on statistical methods (well, it in fact is, but is much more than about “methods”), but one that is quite unique in its contents—it's a book on statistical thinking in epidemiology! In the preface, the authors note that “the main difference between other textbooks and this book is that we emphasize statistical thinking more than applications of specific statistical methods in epidemiological research”—their description is right on—and the book does indeed fulfill that mission. The authors further note that they “… believe it is vital to appreciate the context and for this to happen, one has to stop and reflect, rather than plough in.” I couldn't agree more.</description><dc:title>Statistical Thinking in Epidemiology</dc:title><dc:creator>Cande V. Ananth</dc:creator><dc:identifier>10.1016/j.annepidem.2012.02.011</dc:identifier><dc:source>Annals of Epidemiology 22, 5 (2012)</dc:source><dc:date>2012-03-14</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2012-03-14</prism:publicationDate><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:issueIdentifier>S1047-2797(11)X0016-9</prism:issueIdentifier><prism:section>Book Review</prism:section><prism:startingPage>376</prism:startingPage><prism:endingPage>376</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279712000452/abstract?rss=yes"><title>Erratum</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279712000452/abstract?rss=yes</link><description>In the article by Kanarek, M.S., “ Mesothelioma from Chrysotile Asbestos: Update,” published September 2011, Volume 21, Issue 9, pages 688−697, there were a few errors of transcription from the text in Table 1. A corrected Table 1, which also adds specification of body site of mesothelioma occurrence for each reviewed study in the article, is shown.</description><dc:title>Erratum</dc:title><dc:creator></dc:creator><dc:identifier>10.1016/j.annepidem.2012.02.016</dc:identifier><dc:source>Annals of Epidemiology 22, 5 (2012)</dc:source><dc:date>2012-03-16</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2012-03-16</prism:publicationDate><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:issueIdentifier>S1047-2797(11)X0016-9</prism:issueIdentifier><prism:section>Erratum</prism:section><prism:startingPage>377</prism:startingPage><prism:endingPage>377</prism:endingPage></item><item rdf:about="http://www.annalsofepidemiology.org/article/PIIS1047279712000701/abstract?rss=yes"><title>Contents</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279712000701/abstract?rss=yes</link><description></description><dc:title>Contents</dc:title><dc:creator></dc:creator><dc:identifier>10.1016/S1047-2797(12)00070-1</dc:identifier><dc:source>Annals of Epidemiology 22, 5 (2012)</dc:source><dc:date>2012-05-01</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2012-05-01</prism:publicationDate><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:issueIdentifier>S1047-2797(11)X0016-9</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/PIIS1047279712000713/abstract?rss=yes"><title>Masthead</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279712000713/abstract?rss=yes</link><description></description><dc:title>Masthead</dc:title><dc:creator></dc:creator><dc:identifier>10.1016/S1047-2797(12)00071-3</dc:identifier><dc:source>Annals of Epidemiology 22, 5 (2012)</dc:source><dc:date>2012-05-01</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2012-05-01</prism:publicationDate><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:issueIdentifier>S1047-2797(11)X0016-9</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/PIIS1047279712000725/abstract?rss=yes"><title>Information for Authors</title><link>http://www.annalsofepidemiology.org/article/PIIS1047279712000725/abstract?rss=yes</link><description></description><dc:title>Information for Authors</dc:title><dc:creator></dc:creator><dc:identifier>10.1016/S1047-2797(12)00072-5</dc:identifier><dc:source>Annals of Epidemiology 22, 5 (2012)</dc:source><dc:date>2012-05-01</dc:date><prism:publicationName>Annals of Epidemiology</prism:publicationName><prism:publicationDate>2012-05-01</prism:publicationDate><prism:volume>22</prism:volume><prism:number>5</prism:number><prism:issueIdentifier>S1047-2797(11)X0016-9</prism:issueIdentifier><prism:section>Frontmatter</prism:section><prism:startingPage>A5</prism:startingPage><prism:endingPage>A6</prism:endingPage></item></rdf:RDF>
