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        <title>Article Comments - 'Diabetes prevalence and diagnosis in US states: analysis of health surveys'</title>
        <link>http://www.pophealthmetrics.com/content/7/1/16/comments</link>
        <description>The latest comments on the article 'Diabetes prevalence and diagnosis in US states: analysis of health surveys'</description>
        <dc:date>2009-10-30T00:12:47Z</dc:date>
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        <title>Authors&apos; response to reader comment</title>
        <link>http://www.pophealthmetrics.com/content/7/1/16/comments#375658</link>
        <description>&lt;p&gt;We appreciate the attention to this detail by Dr Cheng. The point raised is correct and was indeed due to a skip pattern in the NHANES questionnaire. We repeated the analysis to evaluate the influence on the coefficients of regression within NHANES and predicted diabetes prevalence. Three coefficients (smoking, age 60-69, and age 70+) changed by less than 10%, and the rest remained unchanged. Predicted diabetes prevalence for different state-sex-age-race-insurance categories changed on average by 1.3% and at the most by 3.5% of the values reported in the manuscript, and hence were not sensitive to this error.  &lt;br/&gt;Goodarz Danaei and Majid Ezzati, on behalf of the authors&lt;/p&gt;</description>
                <dc:creator>Jolayne Houtz</dc:creator>
                <dc:date>2009-10-30T00:12:47Z</dc:date>
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        <prism:person>Danaei et al.</prism:person>
        <prism:publicationName>Population Health Metrics</prism:publicationName>
        <prism:volume>7</prism:volume>
        <prism:startingPage>16</prism:startingPage>
        <prism:publicationDate>Fri Sep 25 09:40:08 BST 2009</prism:publicationDate>
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        <title>Comments on the missing values of smoking and insurance status</title>
        <link>http://www.pophealthmetrics.com/content/7/1/16/comments#374660</link>
        <description>&lt;p&gt;This article demonstrated a simple and innovative approach to answer an important question that is what the total diabetes prevalences by US states are. I read it with great interesting and noticed the authors mentioned that there were &amp;#8220;&amp;#8230;50.2% of observations in NHANES were missing either smoking or insurance status&amp;#8230;&amp;#8221; According to the documentations, this is extremely too high. For example, in NHANES 2003-2004, persons aged 20 years or older had one missing value on question &amp;#8220;Smoked at least 100 cigarettes in life&amp;#8221; (http://www.cdc.gov/nchs/data/nhanes/nhanes_03_04/smq_c.pdf) and persons aged 0 years or older had only 133 missing values on question &amp;#8220;Covered by health insurance&amp;#8221;(http://www.cdc.gov/nchs/data/nhanes/nhanes_03_04/hiq_c.pdf). The authors might ignore the skip pattern of these two variables. Incorrectly handling these variables may make incorrect predictions and  incorrect conclusions. I am wondering whether the authors can check the document and dataset again and rerun the analyses.&lt;/p&gt;</description>
                <dc:creator>Yiling Cheng</dc:creator>
                <dc:date>2009-10-29T15:59:34Z</dc:date>
        <prism:references>http://www.pophealthmetrics.com/content/7/1/16</prism:references>
        <prism:person>Danaei et al.</prism:person>
        <prism:publicationName>Population Health Metrics</prism:publicationName>
        <prism:volume>7</prism:volume>
        <prism:startingPage>16</prism:startingPage>
        <prism:publicationDate>Fri Sep 25 09:40:08 BST 2009</prism:publicationDate>
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