MODERN DISEASE PREVENTION
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If you want to inspire confidence, give plenty of statistics. It does not matter that they should be accurate, or even intelligible, as long as there is enough of them.   —  Lewis Carroll

FIBBING WITH NUMBERS
New York Times Book Review by Steven Strogatz
Proofiness: The Dark Arts of Mathematical Deception by Charles Seife. Publisher Viking Adult (September 23, 2010). Before joining the Department of Journalism at New York University, Charles Seife was writer for Science magazine -specializing in physics and mathematics- and had been a U.S. correspondent for New Scientist. He holds an A.B. in mathematics from Princeton University, an M.S. in mathematics from Yale University, and an M.S. in journalism from Columbia University. His research interests include science and mathematics journalism.
     Charles Seife is steaming mad about all the ways that numbers are being twisted to erode our democracy. We’re used to being lied to with words (“I am not a crook”; “I did not have sexual relations with that woman”). But numbers? They’re supposed to be cold, hard and objective. Numbers don’t lie, and they brook no argument. They’re the best kind of facts we have.
     And that’s precisely why they can be so powerfully, persuasively misleading, as Seife argues in his passionate new book, “Proofiness.” Seife, a veteran science writer who teaches journalism at New York University, examines the many ways that people fudge with numbers, sometimes just to sell more moisturizer but also to ruin our economy, rig our elections, convict the innocent and undercount the needy. Many of his stories would be darkly funny if they weren’t so infuriating.
     Although Seife never says so explicitly, the book’s title alludes to “truthiness” — the Word of the Year in 2005, according to the American Dialect Society, which defined it as “the quality of preferring concepts or facts one wishes to be true, rather than concepts or facts known to be true.” The term was popularized by Stephen Colbert in the first episode of “The Colbert Report.” The numerical cousin of truthiness is proofiness: “the art of using bogus mathematical arguments to prove something that you know in your heart is true — even when it’s not.”
     Seife emphasizes that numbers impress us. They carry authority. Joe McCarthy, for example, didn’t simply allege that the government was infested with Communists; he held up a sheaf of papers and claimed it contained the names of 205 members of the Communist Party working in the State Department. The specificity of the accusation made it seem more believable. So what if the number soon went up to 207, then shrank to 57 a day later when McCarthy wrote to President Truman? What mattered is that the numbers intimidated McCarthy’s critics. As it turned out, he never had any list and couldn’t identify a single Communist working in the State Department. None of that stopped him from rising to national prominence on the back of his numerical lies.
     Falsifying numbers is the crudest form of proofiness. Seife lays out a rogues’ gallery of more subtle deceptions. “Potemkin numbers” are phony statistics based on erroneous or nonexistent calculations. Justice Antonin Scalia’s assertion that only 0.027 percent of convicted felons are wrongly imprisoned was a Potemkin number derived from a prosecutor’s back-of-the-envelope estimate; more careful studies suggest the rate might be between 3 and 5 percent.
     “Disestimation” involves ascribing too much meaning to a measurement, relative to the uncertainties and errors inherent in it. In the most provocative and detailed part of the book, Seife analyzes the recounting process in the astonishingly close 2008 Minnesota Senate race between Norm Coleman and Al Franken. The winner, he claims, should have been decided by a coin flip; anything else is disestimation, considering that the observed errors in counting the votes were always much larger than the number of votes (roughly 200 to 300) separating the two candidates.
     “Comparing apples and oranges” is another perennial favorite. The conservative Blue Dog Democrats indulged in it when they accused the Bush administration of borrowing more money from foreign governments in four years than had all the previous administrations in our nation’s history, combined. True enough, but only if one conveniently forgets to correct for inflation.
     Seife is evenhanded about exposing the proofiness on both sides of the political aisle, though we all know who’s responsible for a vast majority of it: the other side. He calls Al Gore to task for “cherry-picking” data about global warming. Although Seife doesn’t dispute that the warming is real and that human activities are to blame for a sizable portion of it, he chastises Gore for showing terrifying simulations of what would happen to Florida and Louisiana if sea levels were to rise by 20 feet, as could occur if the ice sheets in Greenland or West Antarctica were to melt almost completely. That possibility, while not out of the question, is generally considered an unlikely “very-worst-case” scenario, Seife writes.
     Meanwhile, the Bush administration committed a more insidious form of proofiness when it crowed, in 2004, that its tax cuts would save the average family $1,586. This is technically correct, but deliberately misleading — a trick that Seife calls “apple polishing.” (Again with the fruit!) The average is the wrong measure to use when a set of numbers contains extreme outliers — in this case, the whopping refunds received by a very few, very wealthy families. In such situations, the average is far from typical. That’s why, paradoxical as it might seem, most families received less than $650.
     In one of the book’s lighter moments, Seife even looks askance at the wholesome folks at Quaker Oats, who in addition to selling a “bland and relatively unappetizing product” once presented a graph that gave the visual impression that their “barely digestible oat fiber” was a “medicinal vacuum cleaner” that would reduce your cholesterol far more than it actually does. For the most part, though, he is deadly serious. A few other recent books have explored how easily we can be deceived — or deceive ourselves — with numbers. But “Proofiness” reveals the truly corrosive effects on a society awash in numerical mendacity. This is more than a math book; it’s an eye-opening civics lesson.
Steven Strogatz. Ph.D. (1986 Harvard University) is a professor in the Department of Theoretical and Applied Mechanics and the Center for Applied Mathematics at Cornell University. In 2007 he received the Communications Award, a lifetime achievement award for the communication of mathematics to the general public. He previously taught at the Massachusetts Institute of Technology, where he received the E.M. Baker Award, an institute-wide teaching prize selected solely by students.
Steven Strogatz. Fibbing With Numbers. New York Times Book Review Published: September 17, 2010.
NUMBERS AND DEFINITIONS
     The Diagnostic and Statistical Manual of Mental Disorders (DSM) is the standard classification of mental disorders used by mental health professionals in the United States. It is intended to be applicable in a wide array of contexts and used by clinicians and researchers of many different orientations (e.g., biological, psychodynamic, cognitive, behavioral, interpersonal, family/systems).
     The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) has been designed for use across clinical settings (inpatient, outpatient, partial hospital, consultation-liaison, clinic, private practice, and primary care), with community populations. It can be used by a wide range of health and mental health professionals, including psychiatrists and other physicians, psychologists, social workers, nurses, occupational and rehabilitation therapists, and counselors. It is also a necessary tool for collecting and communicating accurate public health statistics.
     The American Psychiatric Association is currently completing work on the fifth edition of its Diagnostic and Statistical Manual of Mental Disorders (DSM-5), which will be published in May 2013. The DSM is the standard reference that healthcare providers use to diagnose mental and behavioral conditions. As such, it influences availability of treatments as well as insurance coverage.
     The work group is proposing that Asperger's Disorder be subsumed into an existing disorder: Autistic Disorder (Autism Spectrum Disorder). In making the recommendation to delete Asperger’s disorder, the following questions were considered:
Q.1. Have the DSM-IV diagnostic criteria for Asperger Disorder worked?
Q.2. Does the existing research literature allow us to suggest new criteria to diagnose Asperger Disorder, in contrast to Autistic Disorder/ASD?
Q.3. If Asperger disorder does not appear in DSM-V as a separate diagnostic category, how will  continuity and clarity be maintained for those with the diagnosis?
     Autism Spectrum Disorders (ASDs) are a group of developmental disabilities that can cause significant social, communication and behavioral challenges. Centers for Disease Control and Prevention (CDC) estimates that an average of 1 in 110 children in the U.S have an Autism Spectrum Disorder. CDC is working to find out how many children have Autism Spectrum Disorders, discover the risk factors, and raise awareness of the signs. Recent studies have estimated that the lifetime cost to care for an individual with an Autism Spectrum Disorder is $3.2 million.
SLEEP DURATION AND ALL-CAUSE MORTALITY: A SYSTEMATIC REVIEW AND META-ANALYSIS OF PROSPECTIVE STUDIES
     Sleep is an ancestral and primitive behavior that is shared across the planet by over a billion people on a daily basis. Its underlying mechanisms, interactions, and long-term effects are still poorly understood. Increasing evidence suggests an association between both short and long duration of habitual sleep with adverse health outcomes.
     The aims of this study were to (a) systematically review published prospective population-based studies, (b) carry out a meta-analysis to assess whether the global evidence supports the presence of a relationship between either short or long duration of sleep and all-cause mortality, and (c) obtain a quantitative estimate of the risk to assess the consistency and potential public health relevance.
     A meta-analysis allows the combination of the results of different studies, increasing the overall statistical power and the precision of estimates while controlling for bias and limiting random error. We performed a systematic search of publications using MEDLINE (1966-2009), EMBASE (from 1980), the Cochrane Library, and manual searches without language restrictions.
     We included studies if they were prospective, had follow-up >3 years, had duration of sleep at baseline, and all-cause mortality prospectively. We extracted relative risks (RR) and 95% confidence intervals (CI) and pooled them using a random effect model. We carried out sensitivity analyses and assessed heterogeneity and publication bias. Overall, the 16 studies analyzed provided 27 independent cohort samples. They included 1,382,999 male and female participants (follow-up range 4 to 25 years), and 112,566 deaths.
     Sleep duration was assessed by questionnaire and outcome through death certification. In the pooled analysis, short duration of sleep was associated with a greater risk of death (RR: 1.12; 95% CI 1.06 to 1.18; P < 0. 01) with no evidence of publication bias (P = 0.74) but heterogeneity between studies (P = 0.02). Long duration of sleep was also associated with a greater risk of death (1.30; [1.22 to 1.38]; P < 0.0001) with no evidence of publication bias (P = 0.18) but significant heterogeneity between studies (P < 0.0001).
     We found both short and long duration of sleep are significant predictors of death in prospective population studies.
Francesco P. Cappuccio, MD, FRCP; Lanfranco D'Elia, MD; Pasquale Strazzullo, MD; and Michelle A. Miller, PhD. Sleep Duration and All-Cause Mortality: A Systematic Review and Meta-Analysis of Prospective Studies. SLEEP. Abstract [edited]. 2010 May 1; 33(5): 585–592. SLEEP is the official journal of the Associated Professional Sleep Societies, LLC. Sponsored by the American Academy of Sleep Medicine and the Sleep Research Society. Accessed 31 Dec 2011.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2864873/
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