CiteULike | Further Information

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Mendeley | Further Information

{"title"=>"The reversal of fortunes: Trends in county mortality and cross-county mortality disparities in the United States", "type"=>"journal", "authors"=>[{"first_name"=>"Majid", "last_name"=>"Ezzati", "scopus_author_id"=>"6701418638"}, {"first_name"=>"Ari B.", "last_name"=>"Friedman", "scopus_author_id"=>"7401879795"}, {"first_name"=>"Sandeep C.", "last_name"=>"Kulkarni", "scopus_author_id"=>"36004905600"}, {"first_name"=>"Christopher J L", "last_name"=>"Murray", "scopus_author_id"=>"55481130700"}], "year"=>2008, "source"=>"PLoS Medicine", "identifiers"=>{"issn"=>"15491277", "scopus"=>"2-s2.0-43249087616", "pui"=>"351649255", "doi"=>"10.1371/journal.pmed.0050066", "isbn"=>"10.1371/journal.pmed.0050066", "sgr"=>"43249087616", "pmid"=>"18433290"}, "id"=>"c2ae1fd4-91d3-3755-8120-ce13c4347acd", "abstract"=>"BACKGROUND: Counties are the smallest unit for which mortality data are routinely available, allowing consistent and comparable long-term analysis of trends in health disparities. Average life expectancy has steadily increased in the United States but there is limited information on long-term mortality trends in the US counties This study aimed to investigate trends in county mortality and cross-county mortality disparities, including the contributions of specific diseases to county level mortality trends.\\n\\nMETHODS AND FINDINGS: We used mortality statistics (from the National Center for Health Statistics [NCHS]) and population (from the US Census) to estimate sex-specific life expectancy for US counties for every year between 1961 and 1999. Data for analyses in subsequent years were not provided to us by the NCHS. We calculated different metrics of cross-county mortality disparity, and also grouped counties on the basis of whether their mortality changed favorably or unfavorably relative to the national average. We estimated the probability of death from specific diseases for counties with above- or below-average mortality performance. We simulated the effect of cross-county migration on each county's life expectancy using a time-based simulation model. Between 1961 and 1999, the standard deviation (SD) of life expectancy across US counties was at its lowest in 1983, at 1.9 and 1.4 y for men and women, respectively. Cross-county life expectancy SD increased to 2.3 and 1.7 y in 1999. Between 1961 and 1983 no counties had a statistically significant increase in mortality; the major cause of mortality decline for both sexes was reduction in cardiovascular mortality. From 1983 to 1999, life expectancy declined significantly in 11 counties for men (by 1.3 y) and in 180 counties for women (by 1.3 y); another 48 (men) and 783 (women) counties had nonsignificant life expectancy decline. Life expectancy decline in both sexes was caused by increased mortality from lung cancer, chronic obstructive pulmonary disease (COPD), diabetes, and a range of other noncommunicable diseases, which were no longer compensated for by the decline in cardiovascular mortality. Higher HIV/AIDS and homicide deaths also contributed substantially to life expectancy decline for men, but not for women. Alternative specifications of the effects of migration showed that the rise in cross-county life expectancy SD was unlikely to be caused by migration.\\n\\nCONCLUSIONS: There was a steady increase in mortality inequality across the US counties between 1983 and 1999, resulting from stagnation or increase in mortality among the worst-off segment of the population. Female mortality increased in a large number of counties, primarily because of chronic diseases related to smoking, overweight and obesity, and high blood pressure.", "link"=>"http://www.mendeley.com/research/reversal-fortunes-trends-county-mortality-crosscounty-mortality-disparities-united-states", "reader_count"=>180, "reader_count_by_academic_status"=>{"Unspecified"=>5, "Professor > Associate Professor"=>12, "Librarian"=>1, "Student > Doctoral Student"=>11, "Researcher"=>33, "Student > Ph. D. Student"=>39, "Student > Postgraduate"=>6, "Student > Master"=>30, "Other"=>15, "Student > Bachelor"=>14, "Lecturer > Senior Lecturer"=>3, "Professor"=>11}, "reader_count_by_user_role"=>{"Unspecified"=>5, "Professor > Associate Professor"=>12, "Librarian"=>1, "Student > Doctoral Student"=>11, "Researcher"=>33, "Student > Ph. D. 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Scopus | Further Information

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Web of Science® | Further Information

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Article Coverage Curated

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• {"referral"=>"http://www.nytimes.com/2008/04/22/health/research/22life.html?_r=1&", "language"=>"", "title"=>"Life Expectancy Is Declining in Some Pockets of the Country", "type"=>"News", "publication"=>"www.nytimes.com", "published_on"=>"2014-01-28T00:00:00.000Z", "link_state"=>"APPROVED", "id"=>7017, "created"=>"2014-01-28T12:15:58.000Z", "crowdsourced"=>false, "article"=>{"id"=>2766, "doi"=>"10.1371/journal.pmed.0050066", "title"=>"The Reversal of Fortunes: Trends in County Mortality and Cross-County Mortality Disparities in the United States ", "published_on"=>"2008-04-22T00:00:00.000Z"}}
• {"referral"=>"https://www.cnn.com/2018/11/22/health/life-expectancy-gap-uk-study/index.html", "language"=>"English", "title"=>"Life expectancy gap grows among rich and poor in UK - CNN", "type"=>"News", "publication"=>"Jacqueline Howard, CNN", "published_on"=>"", "link_state"=>"APPROVED", "id"=>83776, "created"=>"2018-11-24T06:46:25.000Z", "crowdsourced"=>false, "article"=>{"id"=>2766, "doi"=>"10.1371/journal.pmed.0050066", "title"=>"The Reversal of Fortunes: Trends in County Mortality and Cross-County Mortality Disparities in the United States ", "published_on"=>"2008-04-22T00:00:00.000Z"}}

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• {"url"=>"http%3A%2F%2Fjournals.plos.org%2Fplosmedicine%2Farticle%3Fid%3D10.1371%252Fjournal.pmed.0050066", "share_count"=>2, "like_count"=>2, "comment_count"=>1, "click_count"=>0, "total_count"=>5}

Journal Comments | Further Information

• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/ceb55e0c-3d89-4334-9dc4-ced3f8fe55f6", "title"=>"Correction on behalf of the authors", "body"=>"Author: On behalf of Majid Ezzati and colleagues\nPosition: Department of Population and International Health\nInstitution: Harvard School of Public Health\nE-mail: majid_ezzati@harvard.edu\nAdditional Authors: Ari B. Friedman, Sandeep C. Kulkarni, Christopher J.L Murray\nSubmitted Date: April 22, 2008\nPublished Date: April 22, 2008\nThis comment was originally posted as a “Reader Response” on the publication date indicated above. All Reader Responses are now available as comments.\n\nMajid Ezzati and colleagues contacted PLoS Medicine a few days ahead of publication to highlight several errors in the article text, Figure 4 and Dataset S1.\n\nUnfortunately it was too late to make these changes to the paper before it was published but a formal correction is forthcoming. This will be published on the 13th May. A link from the paper to the correction will be available on the top right hand corner of the HTML version, above the navigation bar.\n\nThe conclusions of the paper remain unchanged.\n\nIn the interim, please find the text for the forthcoming correction below, together with links to the correct version of Figure 4 and Dataset S1. These links will open in any browser:\n\nCorrection for: Ezzati M, Friedman AB, Kulkarni SC, Murray CJL (2008) The reversal of fortunes: Trends in county mortality and cross-county mortality disparities in the United States. PLoS Med 5(4): e66. doi:10.1371/journal.pmed.0050066\n\n- In the Methods section under the heading “Effects of Cross-County Migration on Life Expectancy” (Page 0003, column 2 of the PDF), country should be replaced by county in the following sentence: “(2) the life expectancy of all emigrants was 1 y higher than the life expectancy of those who stayed in the country of origin”. The correct text is:\n\n(2) the life expectancy of all emigrants was 1 y higher than the life expectancy of those who stayed in the county of origin.\n\n- In the Results section (Page 0004, three lines from the end of column 2 in the PDF), the text that reads “(women in the worst-performing group, group 6, actually experienced a rise in cardiovascular mortality in the oldest age group)” should be dropped. The correct text is:\n\nThe rise in mortality for these causes in 1983–1999 was no longer compensated by the decline in cardiovascular mortality because cardiovascular decline became substantially smaller than it was in 1961–1983.\n\n- Figure 4 (Page 0008 of the PDF) should be replaced with the corrected Figure 4 (see a link to the corrected figure below). The original figure incorrectly showed the probability of dying in 1999, instead of the difference between 1999 and 1983, for Group 6 for 75 – 84 females in 1983–1999 only. Data for all other groups were correct. This error does not affect the conclusions of the paper.\n\n- In the legend for Figure 4 (Page 0008 of the PDF), “Group 6 for females in 1983–1999 is shown on a different scale to increase resolution for all other groups” should be dropped. The correct legend for Figure 4 is:\n\nFigure 4. Change in Probability of Dying in Specific Age Ranges between 1961 and 1983 and between 1983 and 1999, with Counties Grouped on the Basis of the Level of Change in Life Expectancy as in Figure 3\n\nThe total height of each column shows the change in the probability of dying (from all causes) in the age range shown, divided into the probability of dying from specific diseases and injuries. The change is calculated as the probability of death in the end year minus that of the initial year. Therefore, a positive number indicates an increase in mortality, and a negative number indicates a decline in mortality (disease-specific or all-cause for the net effects of all diseases).\n\nNotes: Results are not shown for 5–14 y because there are few deaths in these ages in the United States. Groups with less than 0.2% of the country’s population (groups 4 and 6 for both sexes in 1961–1983, and group 4 for males in 1983–1999) have not been shown because the results are based on too few deaths. COPD and lung cancer are presented together and changed in the same direction for all age and county group. The other noncommunicable disease group includes diabetes, for which the direction of change in probability of death is identical to other noncommunicable diseases exclusive of diabetes.\n\nCorrected Figure 4: http://www.plos.org/press/plme-05-04-ezzati-figure-4-corrected.pdf\n\n- In Dataset S1, the data for Group 6 for 75 – 84 females in 1983–1999 have been corrected. See the corrected Dataset S1 below.\n\nCorrected Dataset S1:\nhttp://www.plos.org/press/plme-05-04-ezzati-dataset-S1-corrected.xls", "isRemoved"=>false, "created"=>"2009-03-31T00:25:08Z", "lastModified"=>"2009-03-31T00:25:08Z", "creator"=>{"userId"=>"172479"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pmed.0050066", "state"=>"published", "journals"=>{"PLoSMedicine"=>{"journalKey"=>"PLoSMedicine", "eIssn"=>"1549-1676", "title"=>"PLOS Medicine"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2009-03-31T00:25:08Z", "replies"=>[]}
• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/02590fdc-5466-4297-9e22-7b2f881a35af", "title"=>"Some historical and social perspective for these findings", "body"=>"Author: Kelly Rusinack\nPosition: Ph.D. Candidate\nInstitution: University of Miami History Dept.\nE-mail: kellyrusinack@yahoo.com\nSubmitted Date: April 23, 2008\nPublished Date: April 24, 2008\nThis comment was originally posted as a “Reader Response” on the publication date indicated above. All Reader Responses are now available as comments.\n\nIs it beyond the scope of your study to take into account the rise in HMOs as the standard in healthcare since the late-1980s? Prior to the advent of HMOs, almost everyone had a POS that paid for all claims. Most employers paid 100% of employee premiums. Doctors were able to do all that was necessary for their patients without threat of being second-guessed.¶\nWhile your findings are fascinating, they inherently blame the decedents' lifestyles. While the issue of prevention is part of your conclusion, HMOs do not focus on prevention, they focus on illness and injury. Especially in the 1990s, HMOs were stubbornly opposed to providing coverage for tests and treatments that actually prevented disease or caught it in its early stages. One had to be deep in the throes of disease in order to receive any tests or treatments, if they did at all. It is still that way. Patients don't automatically receive the best or most appropriate diagnostic tools, they receive the least expensive ones.¶\nThe conditions that you list as having the greatest impact on life-expectancy are also ones that are generally untreatable or hard to reverse once a patient is symptomatic. In poorer counties, not only are people forced to work and bring home a paycheck regardless of how sick they feel, they also do not receive the medical benefits that would help them understand and prevent these diseases, and are turned away by their HMOs when they first start to complain of symptoms.¶\nPrevention is also a white-collar concept. Dietary changes are just not affordable for many people. The most affordable food available is the worst food for one's health. In economically depressed areas, people don't make enough money to pay for fresh produce and natural foods; eating healthy is expensive. And academicians most likely have never had to live on an average worker's wages to understand how exhausting these jobs are and how little money they can put towards taking care of themselves. Who has time, energy, or money to make those lifestyle changes? I've been on both sides of the fence and I can tell you that the majority of people in the poorer areas of any county do not.¶\nThe roles of women in our society since the early-'80s also play a factor in this problem. In 1983, many women still only held full-time jobs in the home. By the 1990s, more women were in the workforce, but they still had those jobs waiting for them at home. The burdens that women face in our society contribute to their lack of time and energy to pursue a healthy lifestyle and healthcare prevention. Women also tend to ignore the signs of disease, pass it off as the normal strain of life, until it is almost too late. And even then, studies have shown that many husbands still lack the empathy necessary to take over part of the load, or to care for a woman when she is ill. The \"traditional values\" of marriage are more pronounced in poorer areas, where women depend upon the man's paycheck so much (due to disparity in wages) that they put up with much more misery, emotional and physical, than more affluent women.¶\nAll of this doesn't even include how overworked and underpaid doctors are when they participate in HMOs. It is well-documented that this leads to a cattle-call atmosphere in healthcare. Doctors are forced to patch patients up and get them out of treatment as soon and cheaply as possible. The poorer the county, the worse this practice is. This leads to missed or late diagnoses, and lack of time to educate patients about disease prevention.¶\nThis is most likely way beyond the scope of your study. However, future researchers can use this study for further research into why this situation has proliferated. I firmly believe that gender roles, socioeconomic factors, and limitations placed on doctors and patients today in order to save a dime for HMOs and PPOs, play a great role in the untimely deaths of millions of people, especially women. These issues need to become part of this dialogue.", "isRemoved"=>false, "created"=>"2009-03-31T00:25:12Z", "lastModified"=>"2009-03-31T00:25:12Z", "creator"=>{"userId"=>"172479"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pmed.0050066", "state"=>"published", "journals"=>{"PLoSMedicine"=>{"journalKey"=>"PLoSMedicine", "eIssn"=>"1549-1676", "title"=>"PLOS Medicine"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2009-03-31T00:25:12Z", "replies"=>[]}
• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/ae53c53a-6b85-407a-bfa1-d8b38a7ee754", "title"=>"Hispanic origin should be interpreted with caution", "body"=>"Author: Steven vandorne\nE-mail: svandorne@live.com\nSubmitted Date: April 22, 2008\nPublished Date: April 24, 2008\nThis comment was originally posted as a “Reader Response” on the publication date indicated above. All Reader Responses are now available as comments.\n\nThe CDC pointed out a number of times that their data on Hispanic numbers are wrong but it doesn’t seem like you took that into account.\n\n“Data for Hispanic origin should be interpreted with caution because of inconsistencies between reporting Hispanic origin...”\n\nWhat that means when you look at undocumented immigrant's there would be more deaths then births.\n\nWhich would make low income look like a problem.", "isRemoved"=>false, "created"=>"2009-03-31T00:25:20Z", "lastModified"=>"2009-03-31T00:25:20Z", "creator"=>{"userId"=>"172479"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pmed.0050066", "state"=>"published", "journals"=>{"PLoSMedicine"=>{"journalKey"=>"PLoSMedicine", "eIssn"=>"1549-1676", "title"=>"PLOS Medicine"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2009-03-31T00:25:20Z", "replies"=>[]}
• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/3a948933-65f8-4388-b0bd-1be3ecb4378b", "title"=>"Men cheated", "body"=>"Author: Richard Brett\nPosition: registered nurse\nE-mail: richardbrettjr@yahoo.com\nSubmitted Date: April 23, 2008\nPublished Date: April 24, 2008\nThis comment was originally posted as a “Reader Response” on the publication date indicated above. All Reader Responses are now available as comments.\n\nWomen fall behind 1.6 years in life and now we must do something about it! What about the men who still are 6 years behind the women. There are no groups, pink ribbons or walkathons for men diseases.\n\nThat being said the number 1 reason I see with women in the clinical setting is their obesity. I would say 80% of my bariatric cllients are women.", "isRemoved"=>false, "created"=>"2009-03-31T00:25:24Z", "lastModified"=>"2009-03-31T00:25:24Z", "creator"=>{"userId"=>"172479"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pmed.0050066", "state"=>"published", "journals"=>{"PLoSMedicine"=>{"journalKey"=>"PLoSMedicine", "eIssn"=>"1549-1676", "title"=>"PLOS Medicine"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2009-03-31T00:25:24Z", "replies"=>[]}
• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/2469b25f-e785-45dd-a814-62553cb3aa2f", "title"=>"A coordinated attack on the Obesity Epidemic", "body"=>"Author: Andrea DeSantis\nPosition: DO\nInstitution: Carolinas Medical Center North Park Clinic\nE-mail: jbarkley2@carolina.rr.com\nSubmitted Date: April 24, 2008\nPublished Date: April 25, 2008\nThis comment was originally posted as a “Reader Response” on the publication date indicated above. All Reader Responses are now available as comments.\n\nI have practiced family medicine in a low income clinic for the past 10 years. I have I seen many woman and men die prematurely of cardiovascular disease related to obesity. My impression is that the combination of tobacco, poor diet and the genetic predisposition to obesity and diabetes are at play. Loosing weight by changing a lifetime of unhealthy eating and exercise habits seems to be as difficult as quitting smoking. Health behaviors become entrenched at a very early age. The solution must be done through the individual but also through reform of our public policy. Our Food Stamp program needs to look more like the WIC program. Our schools have to start serving more appealing fruits and vegetable type lunches that are free of trans-fats and lower in sugar. Our towns and cities need to be planned to encourage public, pedestrian, and bicycle transportation. Smoking cessation drugs and programs need to be more affordable. The food industry needs to do their part as well.", "isRemoved"=>false, "created"=>"2009-03-31T00:25:28Z", "lastModified"=>"2009-03-31T00:25:28Z", "creator"=>{"userId"=>"172479"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pmed.0050066", "state"=>"published", "journals"=>{"PLoSMedicine"=>{"journalKey"=>"PLoSMedicine", "eIssn"=>"1549-1676", "title"=>"PLOS Medicine"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2009-03-31T00:25:28Z", "replies"=>[]}
• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/4caefb19-1f00-476e-bea3-291698efce8b", "title"=>"Dataset S2", "body"=>"Author: Andrew Hyde\nPosition: Publications Manager\nInstitution: Public Library of Science\nE-mail: ahyde@plos.org\nSubmitted Date: April 28, 2008\nPublished Date: April 28, 2008\nThis comment was originally posted as a “Reader Response” on the publication date indicated above. All Reader Responses are now available as comments.\n\nIt has been brought to our attention that some readers are having difficulty opening Dataset S2 in Internet Explorer.\n\nThe dataset does open without any problems in Mozilla Firefox.\n\nIf you continue to have difficulty with the link to this piece of supporting information, please try the preview link of the same file that was sent out with the press release for the paper. By copying this into any browser - including Internet Explorer and Firefox - you should be able to open the dataset:\n\nhttp://www.plos.org/press/plme-05-04-ezzati-dataset-S2.xls\n\nPlease contact PLoSMedicine@plos.org if you continue to have difficulties.", "isRemoved"=>false, "created"=>"2009-03-31T00:25:32Z", "lastModified"=>"2009-03-31T00:25:32Z", "creator"=>{"userId"=>"172479"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pmed.0050066", "state"=>"published", "journals"=>{"PLoSMedicine"=>{"journalKey"=>"PLoSMedicine", "eIssn"=>"1549-1676", "title"=>"PLOS Medicine"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2009-03-31T00:25:32Z", "replies"=>[]}
• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/8cf62b2a-1af3-4e72-8279-20cc4d345a1d", "title"=>"Valley of Death", "body"=>"Author: Kenneth Thompson\nPosition: Associate Professor of Psychiatry and Public Health\nInstitution: University of Pittsburgh\nE-mail: visiblehands@mac.com\nSubmitted Date: April 27, 2008\nPublished Date: April 29, 2008\nThis comment was originally posted as a “Reader Response” on the publication date indicated above. All Reader Responses are now available as comments.\n\nIts an interesting phenomena that an article about the geography of mortality pays no attention to what that geography might mean. But its not surprising, given that the perspective from which the article is written, that our health care system is failing (in some places?), is really a non-geographic, non-social argument.\nThe question that might be asked, but apparently wasn't, is \"why is there a geography to mortality? and why this geography?\". The authors note that the rates of stagnant and worsening mortality follow the drainages of Ohio and Mississippi River Valley. There is a suggestion that health care in these regions must be at fault. Nothing is said- not even in the form of speculation- about the dramatic socioeconomic disruptions that have occurred in industry and agriculture in these regions. The last thirty years have seen the economic collapse of industries that once offered mass employment along the rivers and their tributaries. Meanwhile, the small family farm has also seen its demise.\nThe absence of any significant social safety net has certainly contributed to the casualties generated by these dramatic, heart breaking, community busting events. Yet their impact on health is hardly ever charted- and when it is, the contribution to illness and death made by our stubborn adherence to the vagaries of the invisible hand of the market and our apparent desire not to do much to help our country people is rarely acknowledged. I am willing to wager this is much more then about improving access to care and changing the quality of care provided- its about how we organize ourselves as a society.\n\nAnother piece of research, then- lets look at unemployment rates, job loss, plant closures, and farm sales by county over the last 30 years and plot them against the mortality data...", "isRemoved"=>false, "created"=>"2009-03-31T00:25:40Z", "lastModified"=>"2009-03-31T00:25:40Z", "creator"=>{"userId"=>"172479"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pmed.0050066", "state"=>"published", "journals"=>{"PLoSMedicine"=>{"journalKey"=>"PLoSMedicine", "eIssn"=>"1549-1676", "title"=>"PLOS Medicine"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2009-03-31T00:25:40Z", "replies"=>[]}
• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/66ea7f6d-fc18-4873-9cf1-cbd7c448acda", "title"=>"RE: Reversal of fortunes: Trends in county mortality and cross-county mortality disparities in the United States", "body"=>"Author: Adamson Muula\nPosition: Dr\nInstitution: University of Malawi and University of North Carolina at Chapel Hill\nE-mail: muula@email.unc.edu\nSubmitted Date: May 07, 2008\nPublished Date: May 8, 2008\nThis comment was originally posted as a “Reader Response” on the publication date indicated above. All Reader Responses are now available as comments.\n\nEzzati et al (1) must be commended for their contribution to the literature on mortality disparities in the United States studied using data across several decades. These types of papers have potential to stimulate remedial action for factors that are amenable to change. Even for immutable variables such as sex and race, an attempt should be made to understand why a particular sex or race experiences significant adverse health outcomes compared to the other i.e. the mechanisms how disadvantage by sex or race is mediated. The ultimate goal of course should be to encourage even better health outcomes in the “better offs” while also promoting a reduction in the gap with the “worse offs”. While Ezzati et al (1) did not intend to describe the mechanisms behind the disparities, it is equally important that the reasons behind the mortality and morbidity outcomes are explored. For instance, why reduced life expectancy in the particular geographical areas and racial groups? Why is this race or sex smoking more than the other? How does it happen that the risk of death increases if one leaves in a county with an x proportion of this race-ethnicity group? More importantly perhaps, how do we ensure that premature mortality and disability is prevented in counties with an x proportion of this race-ethnicity group? Was there any “risk clustering” observed i.e. high proportion of race x being associated with low education associated with low income?\nEzzati et al’s paper also begs other questions. In the methods section, the author reported that their used country-level social demographic characteristics of proportion of the population by education and per-capita income, among other county-level attributes. However, the education level categories used were not specified in the paper. Research who categorize education level as = high school versus > high school may potentially reach different conclusions to those who may have = high school, some college, college graduate and professional or graduate degree. Or was education level used a continuous variable of years of education completed among adults in the county? The authors also referred to per-capita income and not household income. This certainly raises the question as to how the authors dealt with households with dependents not earning an income of their own.\n\n.\n\nReference\n\nEzzati M, Friedman AB, Kulkarni SC, Murray CJL. Reversal of fortunes: Trends in county mortality and cross-county mortality disparities in the United States. PLos Med 2008; 5(4): e66", "isRemoved"=>false, "created"=>"2009-03-31T00:25:56Z", "lastModified"=>"2009-03-31T00:25:56Z", "creator"=>{"userId"=>"172479"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>true, "body"=>"I declare that I have no competing interests"}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pmed.0050066", "state"=>"published", "journals"=>{"PLoSMedicine"=>{"journalKey"=>"PLoSMedicine", "eIssn"=>"1549-1676", "title"=>"PLOS Medicine"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2009-03-31T00:25:56Z", "replies"=>[]}
• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/3d29490b-22fc-45f1-b729-1104ccc1fa88", "title"=>"Author's response to Thompson (\"Valley of Death \")", "body"=>"Author: Majid Ezzati\nPosition: Associate Professor of International Health\nInstitution: Harvard School of Public Health, Department of Population and International Health\nE-mail: majid_ezzati@harvard.edu\nAdditional Authors: Ari B Friedman, Sandeep C Kulkarni, Christopher JL Murray\nSubmitted Date: May 12, 2008\nPublished Date: May 12, 2008\nThis comment was originally posted as a “Reader Response” on the publication date indicated above. All Reader Responses are now available as comments.\n\nWe agree with Thompson that mortality and mortality trends are rooted in socioeconomic factors that are related to, and affect, many other aspects of welfare. We also believe that empirical research should investigate such influences. We however find it peculiar that one would consider not having answered what is a distinct research question a shortcoming of an empirical result. Thompson seems to have a different paper in mind and not the current study.\n\nBeyond this, we believe that the importance of socioeconomic factors, including on how health systems function, does not rule out the possibility and the responsibility of targeted interventions that can successfully reduce health disparities. Many experiences in low-income countries - such as those related to insecticide-treated bednets, ARVs, and interventions for child mortality – demonstrate that public health and health care can reduce mortality and mortality disparities parallel to, or in advance of, fundamental social and economic policies. Not to hold the health system in the US to the same standards seems like a low bar. As we strive for better social conditions, which we ought to, we should also keep the public health system accountable for delivering proven effective personal and population level interventions for risk factors such as high blood pressure and tobacco smoking (1-3) to the communities who most need them.\n\n1) Murray CJ, Lauer JA, Hutubessy RC et al. Effectiveness and costs of interventions to lower systolic blood pressure and cholesterol: a global and regional analysis on reduction of cardiovascular-disease risk. Lancet 2003; 361(9359):717-725.\n\n2) Asaria P, Chisholm D, Mathers C, Ezzati M, Beaglehole R. Chronic disease prevention: health effects and financial costs of strategies to reduce salt intake and control tobacco use. Lancet 2007.\n\n3) Lim SS, Gaziano TA, Gakidou E et al. Prevention of cardiovascular disease in high-risk individuals in low-income and middle-income countries: health effects and costs. Lancet 2007.", "isRemoved"=>false, "created"=>"2009-03-31T00:26:13Z", "lastModified"=>"2009-03-31T00:26:13Z", "creator"=>{"userId"=>"172479"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>true, "body"=>"We are the authors of this paper."}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pmed.0050066", "state"=>"published", "journals"=>{"PLoSMedicine"=>{"journalKey"=>"PLoSMedicine", "eIssn"=>"1549-1676", "title"=>"PLOS Medicine"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2009-03-31T00:26:13Z", "replies"=>[]}

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• {"id"=>"381264372578140160", "text"=>"MT @TomVargheseJr income ineq http://t.co/Hw1HcjTVqg and e0 http://t.co/J56Q9TREiD http://t.co/H2YPHcURDz", "created_at"=>"2013-09-21T03:51:24Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://abs.twimg.com/sticky/default_profile_images/default_profile_2_normal.png"}
• {"id"=>"386167192414216192", "text"=>"@charlesornstein Amazing how much better #dataviz is now. Same project's videos from my time at @IHME_UW : http://t.co/e9XYTBQ8dB", "created_at"=>"2013-10-04T16:33:27Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://a0.twimg.com/profile_images/378800000506419090/7334033f4b84df6547c6b38121f77636_normal.png"}
• {"id"=>"418920552921710592", "text"=>"@ProvPlan @kleachkemon @IHME_UW Older study (http://t.co/swJgMLHxzj) goes back to 1961: http://t.co/eZj0Oq0Yfq and http://t.co/lPEF5oXuVz", "created_at"=>"2014-01-03T01:43:37Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000506419090/7334033f4b84df6547c6b38121f77636_normal.png"}
• {"id"=>"418920720823885824", "text"=>"@ProvPlan @kleachkemon @IHME_UW #opendata on county life expectancy available: http://t.co/T24HBW5LHn", "created_at"=>"2014-01-03T01:44:17Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000506419090/7334033f4b84df6547c6b38121f77636_normal.png"}
• {"id"=>"419267961694605313", "text"=>"RT @AriBFriedman: @ProvPlan @kleachkemon @IHME_UW #opendata on county life expectancy available: http://t.co/T24HBW5LHn", "created_at"=>"2014-01-04T00:44:06Z", "user"=>"IHME_UW", "user_name"=>"IHME at UW", "user_profile_image"=>"http://pbs.twimg.com/profile_images/432414539/IHME_logo_normal.jpg"}
• {"id"=>"420017490085699585", "text"=>"Wasn't always so. http://t.co/swJgMLHxzj MT@katybkoz F mortality getting worse in much of US http://t.co/GBFIHxxSnA http://t.co/JYrTbHdMhX", "created_at"=>"2014-01-06T02:22:28Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000506419090/7334033f4b84df6547c6b38121f77636_normal.png"}
• {"id"=>"420584917626400768", "text"=>"RT @AriBFriedman: Wasn't always so. http://t.co/swJgMLHxzj MT@katybkoz F mortality getting worse in much of US http://t.co/GBFIHxxSnA http:…", "created_at"=>"2014-01-07T15:57:13Z", "user"=>"mcbridetd", "user_name"=>"Timothy McBride", "user_profile_image"=>"http://pbs.twimg.com/profile_images/2925901556/260885e90a85f5ac7bffbe445ee6186d_normal.jpeg"}
• {"id"=>"438731277433188352", "text"=>"@CarterCPrice Indeed. Incr ineq and lower income assoc with worse change in mortality 1983-99 http://t.co/EG21XcKeH1 http://t.co/wFaqDIwgym", "created_at"=>"2014-02-26T17:44:22Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000506419090/7334033f4b84df6547c6b38121f77636_normal.png"}
• {"id"=>"442603957954052097", "text"=>"Life expect. http://t.co/rt5efWLaWS CT @AriLamstein: recommend datasets at the county level that are not from the census? #rstats #dataviz", "created_at"=>"2014-03-09T10:13:01Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000506419090/7334033f4b84df6547c6b38121f77636_normal.png"}
• {"id"=>"442613612616507392", "text"=>"RT @AriBFriedman Life expect. http://t.co/DQgSqR8fVZ CT @AriLamstein: recommend datasets at the county level t... http://t.co/7Z0lI7kDVw", "created_at"=>"2014-03-09T10:51:23Z", "user"=>"rstats_bot", "user_name"=>"rstats_bot", "user_profile_image"=>"http://abs.twimg.com/sticky/default_profile_images/default_profile_4_normal.png"}
• {"id"=>"458197488059834368", "text"=>"@JHPPL @Reddy We saw same trend but by geo.Risk factors driving. Good it's confirmed but sad. http://t.co/rCusfUiyeM http://t.co/9aLM1k7c6u", "created_at"=>"2014-04-21T10:56:08Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000506419090/7334033f4b84df6547c6b38121f77636_normal.png"}
• {"id"=>"491215489017077760", "text"=>"@Goldfarb @porszag Geographic (county) life e0 trends similar--trend reversed in 80's. http://t.co/jql7TUd3Xr http://t.co/aK1JSHjLFI", "created_at"=>"2014-07-21T13:37:53Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000506419090/7334033f4b84df6547c6b38121f77636_normal.png"}
• {"id"=>"491215815967244288", "text"=>"RT @AriBFriedman: @Goldfarb @porszag Geographic (county) life e0 trends similar--trend reversed in 80's. http://t.co/jql7TUd3Xr http://t.co…", "created_at"=>"2014-07-21T13:39:11Z", "user"=>"Goldfarb", "user_name"=>"Zachary Goldfarb", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000678477820/dc309fe9a6b001125715fcc173f6960d_normal.jpeg"}
• {"id"=>"491216072742535168", "text"=>"RT @AriBFriedman: @Goldfarb @porszag Geographic (county) life e0 trends similar--trend reversed in 80's. http://t.co/jql7TUd3Xr http://t.co…", "created_at"=>"2014-07-21T13:40:12Z", "user"=>"porszag", "user_name"=>"Peter Orszag", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000854792536/2a1eca01c1a96d29098bae60dcfb5ba4_normal.jpeg"}
• {"id"=>"594547898215374848", "text"=>"Used to be diff. http://t.co/YOtCGnuCkz MT @ezraklein Few miles=9yr gap http://t.co/s7erXjw7TD http://t.co/NMCfBdRuET http://t.co/S47jXiDLrr", "created_at"=>"2015-05-02T17:03:59Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000506419090/7334033f4b84df6547c6b38121f77636_normal.png"}
• {"id"=>"661742380538695681", "text"=>".@afrakt @kng229 Not 1st sustained drop for many in US c.f. https://t.co/7A1QTANURh based on https://t.co/YOtCGnuCkz https://t.co/w9JbDlhaGP", "created_at"=>"2015-11-04T03:10:52Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000506419090/7334033f4b84df6547c6b38121f77636_normal.png"}
• {"id"=>"661742502475468801", "text"=>".@afrakt @kng229 Not 1st sustained drop for many in US c.f. https://t.co/7A1QTANURh based on https://t.co/YOtCGnuCkz https://t.co/feYBiP1f87", "created_at"=>"2015-11-04T03:11:21Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000506419090/7334033f4b84df6547c6b38121f77636_normal.png"}
• {"id"=>"661753120351997953", "text"=>"RT @AriBFriedman: .@afrakt @kng229 Not 1st sustained drop for many in US c.f. https://t.co/7A1QTANURh based on https://t.co/YOtCGnuCkz http…", "created_at"=>"2015-11-04T03:53:33Z", "user"=>"astokes", "user_name"=>"Andrew Stokes", "user_profile_image"=>"http://pbs.twimg.com/profile_images/502163010828242945/F2UVy78T_normal.jpeg"}
• {"id"=>"663381457398812674", "text"=>"@statesdj @charlesornstein @UpshotNYT Changes aren't uniform either. Nor changes of changes. https://t.co/YOtCGnMdJ9 https://t.co/ZAbfAob5f5", "created_at"=>"2015-11-08T15:43:59Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000506419090/7334033f4b84df6547c6b38121f77636_normal.png"}
• {"id"=>"663383349248049153", "text"=>"RT @AriBFriedman: @statesdj @charlesornstein @UpshotNYT Changes aren't uniform either. Nor changes of changes. https://t.co/YOtCGnMdJ9 http…", "created_at"=>"2015-11-08T15:51:30Z", "user"=>"ken_crichlow", "user_name"=>"ken crichlow", "user_profile_image"=>"http://pbs.twimg.com/profile_images/488414420415291392/q0a4xe49_normal.jpeg"}
• {"id"=>"663386283109019648", "text"=>"Red & orange: Decrease in life expectancy, 1983–1999. https://t.co/h2bHytGeEC https://t.co/TluFvwjyYF", "created_at"=>"2015-11-08T16:03:09Z", "user"=>"asymptosis", "user_name"=>"Steve Roth", "user_profile_image"=>"http://pbs.twimg.com/profile_images/581816537486467072/Pfuk6LMQ_normal.jpg"}
• {"id"=>"663386383428493312", "text"=>"RT @asymptosis: Red & orange: Decrease in life expectancy, 1983–1999. https://t.co/h2bHytGeEC https://t.co/TluFvwjyYF", "created_at"=>"2015-11-08T16:03:33Z", "user"=>"ryanlcooper", "user_name"=>"ryan cooper", "user_profile_image"=>"http://pbs.twimg.com/profile_images/582894932882370560/UtcsVs7y_normal.jpg"}
• {"id"=>"663386756331544577", "text"=>"RT @asymptosis: Red & orange: Decrease in life expectancy, 1983–1999. https://t.co/h2bHytGeEC https://t.co/TluFvwjyYF", "created_at"=>"2015-11-08T16:05:02Z", "user"=>"mattmgardner", "user_name"=>"Matt", "user_profile_image"=>"http://pbs.twimg.com/profile_images/580130182163402752/lJQJb7OP_normal.jpg"}
• {"id"=>"663395792410042369", "text"=>"RT @asymptosis: Red & orange: Decrease in life expectancy, 1983–1999. https://t.co/h2bHytGeEC https://t.co/TluFvwjyYF", "created_at"=>"2015-11-08T16:40:56Z", "user"=>"hilzoy", "user_name"=>"hilzoy", "user_profile_image"=>"http://pbs.twimg.com/profile_images/637867170953736192/YM49BHsl_normal.jpg"}
• {"id"=>"663400079030554624", "text"=>"RT @asymptosis: Red & orange: Decrease in life expectancy, 1983–1999. https://t.co/h2bHytGeEC https://t.co/TluFvwjyYF", "created_at"=>"2015-11-08T16:57:58Z", "user"=>"thunder_struck", "user_name"=>"Mo Johnson", "user_profile_image"=>"http://pbs.twimg.com/profile_images/510929645697388544/Hw6oXVV4_normal.jpeg"}
• {"id"=>"663414872131174400", "text"=>"RT @asymptosis: Red & orange: Decrease in life expectancy, 1983–1999. https://t.co/h2bHytGeEC https://t.co/TluFvwjyYF", "created_at"=>"2015-11-08T17:56:45Z", "user"=>"Peter_Turchin", "user_name"=>"Peter Turchin", "user_profile_image"=>"http://pbs.twimg.com/profile_images/3340551109/54dc1c1ea73e36808001608e113cbb17_normal.jpeg"}
• {"id"=>"663500818008506368", "text"=>"RT @asymptosis: Red & orange: Decrease in life expectancy, 1983–1999. https://t.co/h2bHytGeEC https://t.co/TluFvwjyYF", "created_at"=>"2015-11-08T23:38:16Z", "user"=>"WaltFrench", "user_name"=>"Walt French", "user_profile_image"=>"http://pbs.twimg.com/profile_images/662667754542010369/f8flVAE3_normal.jpg"}
• {"id"=>"663789821102551041", "text"=>"RT @asymptosis: Red & orange: Decrease in life expectancy, 1983–1999. https://t.co/h2bHytGeEC https://t.co/TluFvwjyYF", "created_at"=>"2015-11-09T18:46:40Z", "user"=>"TJ_Kelleher", "user_name"=>"T.J. Kelleher", "user_profile_image"=>"http://pbs.twimg.com/profile_images/570682144809164800/vzsQ6XGQ_normal.png"}
• {"id"=>"698157138498220032", "text"=>"Debate about life expectancy in #demdebate https://t.co/yI6sbycQQl Our early work here: https://t.co/R9FlDMUuN7 @PLOSMedicine @IHME_UW", "created_at"=>"2016-02-12T14:50:07Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000506419090/7334033f4b84df6547c6b38121f77636_normal.png"}
• {"id"=>"698157957779976192", "text"=>"RT @AriBFriedman: Debate about life expectancy in #demdebate https://t.co/yI6sbycQQl Our early work here: https://t.co/R9FlDMUuN7 @PLOSMedi…", "created_at"=>"2016-02-12T14:53:22Z", "user"=>"thehevez", "user_name"=>"HEVEZ", "user_profile_image"=>"http://pbs.twimg.com/profile_images/682934852153249796/lPMhd-BV_normal.png"}
• {"id"=>"698159915798437889", "text"=>"RT @AriBFriedman: Debate about life expectancy in #demdebate https://t.co/yI6sbycQQl Our early work here: https://t.co/R9FlDMUuN7 @PLOSMedi…", "created_at"=>"2016-02-12T15:01:09Z", "user"=>"sharry_insa", "user_name"=>"sharry insa", "user_profile_image"=>"http://pbs.twimg.com/profile_images/696507489882284033/FBRS8yGe_normal.jpg"}
• {"id"=>"698169088569245696", "text"=>"RT @AriBFriedman: Debate about life expectancy in #demdebate https://t.co/yI6sbycQQl Our early work here: https://t.co/R9FlDMUuN7 @PLOSMedi…", "created_at"=>"2016-02-12T15:37:36Z", "user"=>"PennLDI", "user_name"=>"PennLDI", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000457672631/5416e834428fe37b6161e0e0764ce5df_normal.jpeg"}
• {"id"=>"698176121649684480", "text"=>".@HillaryClinton & @BernieSanders debate life exp inequalities and geography. Our 2008 paper https://t.co/s16XLxfEbt https://t.co/R8YwIcLp3V", "created_at"=>"2016-02-12T16:05:33Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000506419090/7334033f4b84df6547c6b38121f77636_normal.png"}
• {"id"=>"698178526428712961", "text"=>"RT @AriBFriedman: .@HillaryClinton & @BernieSanders debate life exp inequalities and geography. Our 2008 paper https://t.co/s16XLxfEbt http…", "created_at"=>"2016-02-12T16:15:06Z", "user"=>"pickettjessica", "user_name"=>"Jessica Pickett", "user_profile_image"=>"http://pbs.twimg.com/profile_images/579501882445451264/zere7q5i_normal.jpg"}
• {"id"=>"698200247927971840", "text"=>"Trend of increased county life exp has been since 80s. https://t.co/YOtCGnMdJ9 https://t.co/ZAVAqyKDV4", "created_at"=>"2016-02-12T17:41:25Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000506419090/7334033f4b84df6547c6b38121f77636_normal.png"}
• {"id"=>"698200332598448128", "text"=>". @matthew608b @nytimes https://t.co/YOtCGnMdJ9 https://t.co/KQs3h9Eqii", "created_at"=>"2016-02-12T17:41:45Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000506419090/7334033f4b84df6547c6b38121f77636_normal.png"}
• {"id"=>"698200604405960704", "text"=>"RT @AriBFriedman: Trend of increased county life exp has been since 80s. https://t.co/YOtCGnMdJ9 https://t.co/ZAVAqyKDV4", "created_at"=>"2016-02-12T17:42:50Z", "user"=>"matthew608b", "user_name"=>"Matthew Zuckerman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/540520376971698176/VQWdo__6_normal.jpeg"}
• {"id"=>"698218349700845568", "text"=>"RT @AriBFriedman: Debate about life expectancy in #demdebate https://t.co/yI6sbycQQl Our early work here: https://t.co/R9FlDMUuN7 @PLOSMedi…", "created_at"=>"2016-02-12T18:53:21Z", "user"=>"IHME_UW", "user_name"=>"IHME at UW", "user_profile_image"=>"http://pbs.twimg.com/profile_images/509474832983920640/ijAkDalA_normal.png"}
• {"id"=>"698243654847074304", "text"=>"RT @AriBFriedman: Debate about life expectancy in #demdebate https://t.co/yI6sbycQQl Our early work here: https://t.co/R9FlDMUuN7 @PLOSMedi…", "created_at"=>"2016-02-12T20:33:54Z", "user"=>"wheisel", "user_name"=>"William Heisel", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000345723123/3b45ea94279fe6c0321596c70f1207e1_normal.jpeg"}
• {"id"=>"718451318994706432", "text"=>"@lindsleininger https://t.co/swJgMLZ8XT Trend has been ongoing. The TIE analysis is a really sharp look at why it might continue.", "created_at"=>"2016-04-08T14:51:57Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/710086002832973824/fzMWDmdh_normal.jpg"}
• {"id"=>"719514815140642816", "text"=>"Chetty and Cutler paper today https://t.co/49SRGDXSFr may resolve decade-old puzzles https://t.co/YOtCGnMdJ9. Looking forward to digging in.", "created_at"=>"2016-04-11T13:17:54Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/710086002832973824/fzMWDmdh_normal.jpg"}
• {"id"=>"719517242698940417", "text"=>"Seconded. And here's 1961-1999 data for comparison: https://t.co/nkYPIlj34o https://t.co/efkor8OJV1", "created_at"=>"2016-04-11T13:27:33Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/710086002832973824/fzMWDmdh_normal.jpg"}
• {"id"=>"719541284289912832", "text"=>"RT @AriBFriedman: Chetty and Cutler paper today https://t.co/49SRGDXSFr may resolve decade-old puzzles https://t.co/YOtCGnMdJ9. Looking for…", "created_at"=>"2016-04-11T15:03:05Z", "user"=>"SwensonTami", "user_name"=>"Tami Swenson", "user_profile_image"=>"http://pbs.twimg.com/profile_images/1823413206/profilePhoto_normal.jpg"}
• {"id"=>"719542850053152769", "text"=>"RT @AriBFriedman: Chetty and Cutler paper today https://t.co/49SRGDXSFr may resolve decade-old puzzles https://t.co/YOtCGnMdJ9. Looking for…", "created_at"=>"2016-04-11T15:09:18Z", "user"=>"iarroyo48", "user_name"=>"Israel Arroyo", "user_profile_image"=>"http://pbs.twimg.com/profile_images/658939191443722240/HWuwEujW_normal.jpg"}
• {"id"=>"785832412827705344", "text"=>"@chowkydar @jmhockenberry Not sure. IANAME* but we 1983 was the minimum county life expectancy inequality https://t.co/YOtCGnuCkz", "created_at"=>"2016-10-11T13:20:21Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/710086002832973824/fzMWDmdh_normal.jpg"}
• {"id"=>"787828139879698432", "text"=>"@RAdamsDudleyMD From https://t.co/CHbxND0wK3", "created_at"=>"2016-10-17T01:30:40Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/710086002832973824/fzMWDmdh_normal.jpg"}
• {"id"=>"806866825980051456", "text"=>"Our brief 2008 review of national mortality declines https://t.co/YOtCGnMdJ9. cc @voxdotcom https://t.co/s6R68qHG7q", "created_at"=>"2016-12-08T14:23:36Z", "user"=>"AriBFriedman", "user_name"=>"Ari Friedman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/710086002832973824/fzMWDmdh_normal.jpg"}

Wikipedia | Further Information

• {"title"=>"Health care in the United States", "url"=>"http://en.wikipedia.org/wiki/Health_care_in_the_United_States", "timestamp"=>"2019-03-13T08:23:59Z"}
• {"title"=>"File:The-Reversal-of-Fortunes-Trends-in-County-Mortality-and-Cross-County-Mortality-Disparities-in-the-pmed.0050066.sv002.ogv", "url"=>"http://commons.wikimedia.org/wiki/File:The-Reversal-of-Fortunes-Trends-in-County-Mortality-and-Cross-County-Mortality-Disparities-in-the-pmed.0050066.sv002.ogv", "timestamp"=>"2017-02-07T03:23:22Z"}
• {"title"=>"File:The-Reversal-of-Fortunes-Trends-in-County-Mortality-and-Cross-County-Mortality-Disparities-in-the-pmed.0050066.sv001.ogv", "url"=>"http://commons.wikimedia.org/wiki/File:The-Reversal-of-Fortunes-Trends-in-County-Mortality-and-Cross-County-Mortality-Disparities-in-the-pmed.0050066.sv001.ogv", "timestamp"=>"2017-02-07T03:23:22Z"}

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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/933285"], "description"=>"<div><p>Counties are categorized into six groups on the basis of how their life expectancy changed in relation to national sex-specific change in life expectancy (4.1 y for men and 4.8 y for women in 1961–1983; 3.1 y for men and 1.3 y for women in 1983–1999). Actual life expectancies are shown in <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.0050066#pmed-0050066-sg001\" target=\"_blank\">Figure S1</a>, and absolute changes in life expectancy are shown in <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.0050066#pmed-0050066-sg002\" target=\"_blank\">Figure S2</a>.</p>\n <p>Group 1, life expectancy increased at a level significantly higher than the national sex-specific mean; group 2, life expectancy increased at a level significantly higher than zero but not significantly distinguishable from the national sex-specific mean; group 3, life expectancy increased at a level significantly higher than zero but significantly less than the national sex-specific mean; group 4, life expectancy change was statistically indistinguishable from zero and from the national sex-specific mean; group 5, life expectancy change was statistically indistinguishable from zero and was significantly less than the national sex-specific mean; group 6, life expectancy had a statistically significant decline. All statistical significance was assessed at 90%.</p></div>", "links"=>[], "tags"=>["expectancy"], "article_id"=>603736, "categories"=>["Biotechnology"], "users"=>["Majid Ezzati", "Ari B Friedman", "Sandeep C Kulkarni", "Christopher J. L Murray"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.0050066.g003", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Change_in_County_Life_Expectancy_in_1961_8211_1983_and_1983_8211_1999_/603736", "title"=>"Change in County Life Expectancy in 1961–1983 and 1983–1999", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-04-22 01:02:16"}
• {"files"=>["https://ndownloader.figshare.com/files/933400"], "description"=>"<div><p>The total height of each column shows the change in the probability of dying (from all causes) in the age range shown, divided into the probability of dying from specific diseases and injuries. The change is calculated as the probability of death in the end year minus that of the initial year. Therefore, a positive number indicates an increase in mortality, and a negative number indicates a decline in mortality (disease-specific or all-cause for the net effects of all diseases). Group 6 for females in 1983–1999 is shown on a different scale to increase resolution for all other groups.</p>\n <p>Notes: Results are not shown for 5–14 y because there are few deaths in these ages in the United States. Groups with less than 0.2% of the country's population (groups 4 and 6 for both sexes in 1961–1983, and group 4 for males in 1983–1999) have not been shown because the results are based on too few deaths. COPD and lung cancer are presented together and changed in the same direction for all age and county group. The other noncommunicable disease group includes diabetes, for which the direction of change in probability of death is identical to other noncommunicable diseases exclusive of diabetes.</p></div>", "links"=>[], "tags"=>["probability", "ranges", "1961", "1983", "counties", "grouped", "expectancy"], "article_id"=>603844, "categories"=>["Biotechnology"], "users"=>["Majid Ezzati", "Ari B Friedman", "Sandeep C Kulkarni", "Christopher J. L Murray"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.0050066.g004", "stats"=>{"downloads"=>3, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Change_in_Probability_of_Dying_in_Specific_Age_Ranges_between_1961_and_1983_and_between_1983_and_1999_with_Counties_Grouped_on_the_Basis_of_the_Level_of_Change_in_Life_Expectancy_as_in_Figure_3_/603844", "title"=>"Change in Probability of Dying in Specific Age Ranges between 1961 and 1983 and between 1983 and 1999, with Counties Grouped on the Basis of the Level of Change in Life Expectancy as in Figure 3", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-04-22 01:04:04"}
• {"files"=>["https://ndownloader.figshare.com/files/933128"], "description"=>"<div><p>(A) Life expectancy for counties that make up the 2.5% of the US population with the highest and lowest county life expectancies in each year.</p>\n <p>(B) Difference between highest and lowest life expectancies in (A). Data for each year show the combined life expectancy for counties that make up 2.5% of the US population and have the highest/lowest life expectancy for that year. The mean number of years that each county was in the highest/lowest life expectancy group was 7.9/10.5 y for men and 8.6/8.6 y for women.</p>\n <p>The vertical lines show the 90% confidence interval (CI) for the estimated life expectancy or life expectancy difference. In each year, the 5% and 95% confidence limits correspond to the 5th and 95th percentiles of the distribution of life tables, calculated using the population-weighted average of death rates of constituent counties in 100 independent draws (see <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.0050066#s2\" target=\"_blank\">Methods</a>).</p></div>", "links"=>[], "tags"=>["expectancy", "disparity", "counties", "highest", "lowest"], "article_id"=>603573, "categories"=>["Biotechnology"], "users"=>["Majid Ezzati", "Ari B Friedman", "Sandeep C Kulkarni", "Christopher J. L Murray"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.0050066.g002", "stats"=>{"downloads"=>4, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Annual_Absolute_Life_Expectancy_Disparity_between_the_Counties_with_the_Highest_and_Lowest_Life_Expectancies_/603573", "title"=>"Annual Absolute Life Expectancy Disparity between the Counties with the Highest and Lowest Life Expectancies", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-04-22 00:59:33"}
• {"files"=>["https://ndownloader.figshare.com/files/476057", "https://ndownloader.figshare.com/files/476067", "https://ndownloader.figshare.com/files/476085", "https://ndownloader.figshare.com/files/476145", "https://ndownloader.figshare.com/files/476178", "https://ndownloader.figshare.com/files/476240"], "description"=>"<div><h3>Background</h3><p>Counties are the smallest unit for which mortality data are routinely available, allowing consistent and comparable long-term analysis of trends in health disparities. Average life expectancy has steadily increased in the United States but there is limited information on long-term mortality trends in the US counties This study aimed to investigate trends in county mortality and cross-county mortality disparities, including the contributions of specific diseases to county level mortality trends.</p> <h3>Methods and Findings</h3><p>We used mortality statistics (from the National Center for Health Statistics [NCHS]) and population (from the US Census) to estimate sex-specific life expectancy for US counties for every year between 1961 and 1999. Data for analyses in subsequent years were not provided to us by the NCHS. We calculated different metrics of cross-county mortality disparity, and also grouped counties on the basis of whether their mortality changed favorably or unfavorably relative to the national average. We estimated the probability of death from specific diseases for counties with above- or below-average mortality performance. We simulated the effect of cross-county migration on each county's life expectancy using a time-based simulation model. Between 1961 and 1999, the standard deviation (SD) of life expectancy across US counties was at its lowest in 1983, at 1.9 and 1.4 y for men and women, respectively. Cross-county life expectancy SD increased to 2.3 and 1.7 y in 1999. Between 1961 and 1983 no counties had a statistically significant increase in mortality; the major cause of mortality decline for both sexes was reduction in cardiovascular mortality. From 1983 to 1999, life expectancy declined significantly in 11 counties for men (by 1.3 y) and in 180 counties for women (by 1.3 y); another 48 (men) and 783 (women) counties had nonsignificant life expectancy decline. Life expectancy decline in both sexes was caused by increased mortality from lung cancer, chronic obstructive pulmonary disease (COPD), diabetes, and a range of other noncommunicable diseases, which were no longer compensated for by the decline in cardiovascular mortality. Higher HIV/AIDS and homicide deaths also contributed substantially to life expectancy decline for men, but not for women. Alternative specifications of the effects of migration showed that the rise in cross-county life expectancy SD was unlikely to be caused by migration.</p> <h3>Conclusions</h3><p>There was a steady increase in mortality inequality across the US counties between 1983 and 1999, resulting from stagnation or increase in mortality among the worst-off segment of the population. Female mortality increased in a large number of counties, primarily because of chronic diseases related to smoking, overweight and obesity, and high blood pressure.</p> </div>", "links"=>[], "tags"=>["reversal", "trends", "cross-county", "disparities", "united", "states"], "article_id"=>153766, "categories"=>["Biotechnology"], "users"=>["Majid Ezzati", "Ari B Friedman", "Sandeep C Kulkarni", "Christopher J. L Murray"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.0050066.sd001", "https://dx.doi.org/10.1371/journal.pmed.0050066.sd002", "https://dx.doi.org/10.1371/journal.pmed.0050066.sg001", "https://dx.doi.org/10.1371/journal.pmed.0050066.sg002", "https://dx.doi.org/10.1371/journal.pmed.0050066.sv001", "https://dx.doi.org/10.1371/journal.pmed.0050066.sv002"], "stats"=>{"downloads"=>7, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/The_Reversal_of_Fortunes_Trends_in_County_Mortality_and_Cross_County_Mortality_Disparities_in_the_United_States_/153766", "title"=>"The Reversal of Fortunes: Trends in County Mortality and Cross-County Mortality Disparities in the United States", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2008-04-22 01:02:46"}
• {"files"=>["https://ndownloader.figshare.com/files/932965"], "description"=>"<p>Inequality in family income (e.g., as measured by the Gini coefficient) declined in the United States between the 1920s and 1970s, and has increased after that period [<a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.0050066#pmed-0050066-b049\" target=\"_blank\">49</a>,<a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.0050066#pmed-0050066-b050\" target=\"_blank\">50</a>].</p>", "links"=>[], "tags"=>["expectancies", "units", "united", "states"], "article_id"=>603407, "categories"=>["Biotechnology"], "users"=>["Majid Ezzati", "Ari B Friedman", "Sandeep C Kulkarni", "Christopher J. L Murray"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.0050066.g001", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_SD_of_Life_Expectancies_of_the_2_068_County_Units_in_the_United_States_by_Sex_/603407", "title"=>"SD of Life Expectancies of the 2,068 County Units in the United States by Sex", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-04-22 00:56:47"}

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Relative Metric

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F1000Prime | Further Information

• {"year"=>2014, "month"=>5, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2014-05-26T08:31:15Z"}
• {"year"=>2014, "month"=>6, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2014-06-30T08:31:14Z"}
• {"year"=>2014, "month"=>7, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2014-07-28T08:31:20Z"}
• {"year"=>2014, "month"=>8, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2014-08-25T08:31:18Z"}
• {"year"=>2014, "month"=>9, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2014-09-29T08:31:19Z"}
• {"year"=>2014, "month"=>10, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2014-10-27T08:31:13Z"}
• {"year"=>2014, "month"=>11, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2014-11-24T09:30:49Z"}
• {"year"=>2014, "month"=>12, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2014-12-29T09:40:46Z"}
• {"year"=>2015, "month"=>1, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2015-01-26T09:40:22Z"}
• {"year"=>2015, "month"=>2, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2015-02-23T09:40:21Z"}
• {"year"=>2015, "month"=>3, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2015-03-23T08:40:24Z"}
• {"year"=>2015, "month"=>4, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2015-04-27T08:40:23Z"}
• {"year"=>2015, "month"=>5, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2015-05-25T08:40:19Z"}
• {"year"=>2015, "month"=>6, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2015-06-29T08:40:25Z"}
• {"year"=>2015, "month"=>7, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2015-07-27T08:40:19Z"}
• {"year"=>2015, "month"=>8, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2015-08-31T08:40:23Z"}
• {"year"=>2015, "month"=>9, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2015-09-28T08:40:22Z"}
• {"year"=>2015, "month"=>10, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2015-10-26T08:40:25Z"}
• {"year"=>2015, "month"=>11, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2015-11-30T09:40:24Z"}
• {"year"=>2015, "month"=>12, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2015-12-28T09:40:25Z"}
• {"year"=>2016, "month"=>1, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2016-01-25T09:40:26Z"}
• {"year"=>2016, "month"=>2, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2016-02-29T09:40:17Z"}
• {"year"=>2016, "month"=>3, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2016-03-28T08:40:18Z"}
• {"year"=>2016, "month"=>4, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2016-04-25T08:40:18Z"}
• {"year"=>2016, "month"=>5, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2016-05-16T08:40:19Z"}
• {"year"=>2016, "month"=>6, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2016-06-27T08:40:19Z"}
• {"year"=>2016, "month"=>7, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2016-07-25T08:40:21Z"}
• {"year"=>2016, "month"=>8, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2016-08-29T08:40:17Z"}
• {"year"=>2016, "month"=>9, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2016-09-26T08:40:22Z"}
• {"year"=>2016, "month"=>10, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2016-10-31T08:40:18Z"}
• {"year"=>2016, "month"=>11, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2016-11-28T09:40:20Z"}
• {"year"=>2016, "month"=>12, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2016-12-26T09:40:22Z"}
• {"year"=>2017, "month"=>1, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2017-01-30T09:40:19Z"}
• {"year"=>2017, "month"=>2, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2017-02-27T09:40:20Z"}
• {"year"=>2017, "month"=>3, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2017-03-27T08:40:16Z"}
• {"year"=>2017, "month"=>4, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2017-04-24T08:40:14Z"}
• {"year"=>2017, "month"=>5, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2017-05-29T08:40:32Z"}
• {"year"=>2017, "month"=>6, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"http://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2017-06-26T08:40:13Z"}
• {"year"=>2017, "month"=>7, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2017-07-31T08:40:29Z"}
• {"year"=>2017, "month"=>8, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2017-08-28T08:40:34Z"}
• {"year"=>2017, "month"=>9, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2017-09-25T08:40:16Z"}
• {"year"=>2017, "month"=>10, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2017-10-30T08:40:32Z"}
• {"year"=>2017, "month"=>11, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2017-11-27T09:40:40Z"}
• {"year"=>2017, "month"=>12, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2017-12-25T09:40:13Z"}
• {"year"=>2018, "month"=>1, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2018-01-29T09:40:14Z"}
• {"year"=>2018, "month"=>2, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2018-02-26T09:40:14Z"}
• {"year"=>2018, "month"=>3, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2018-03-26T08:40:15Z"}
• {"year"=>2018, "month"=>4, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2018-04-30T08:40:14Z"}
• {"year"=>2018, "month"=>5, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2018-05-28T08:40:16Z"}
• {"year"=>2018, "month"=>6, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2018-06-25T08:40:15Z"}
• {"year"=>2018, "month"=>7, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2018-07-30T08:40:17Z"}
• {"year"=>2018, "month"=>8, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2018-08-27T08:40:15Z"}
• {"year"=>2018, "month"=>9, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2018-09-24T08:40:15Z"}
• {"year"=>2018, "month"=>10, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2018-10-29T08:40:22Z"}
• {"year"=>2018, "month"=>11, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2018-11-26T09:40:17Z"}
• {"year"=>2018, "month"=>12, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2018-12-31T09:40:33Z"}
• {"year"=>2019, "month"=>1, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2019-01-28T09:40:17Z"}
• {"year"=>2019, "month"=>2, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2019-02-25T09:40:20Z"}
• {"year"=>2019, "month"=>3, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2019-03-25T08:40:15Z"}
• {"year"=>2019, "month"=>4, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2019-04-29T08:40:18Z"}
• {"year"=>2019, "month"=>5, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2019-05-27T08:40:26Z"}
• {"year"=>2019, "month"=>6, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2019-06-24T08:40:18Z"}
• {"year"=>2019, "month"=>7, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2019-07-29T08:40:17Z"}
• {"year"=>2019, "month"=>8, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2019-08-26T08:40:20Z"}
• {"year"=>2019, "month"=>9, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2019-09-30T08:40:18Z"}
• {"year"=>2019, "month"=>10, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2019-10-28T08:40:19Z"}
• {"year"=>2019, "month"=>11, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2019-11-25T09:40:23Z"}
• {"year"=>2019, "month"=>12, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2019-12-30T09:40:19Z"}
• {"year"=>2020, "month"=>1, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2020-01-27T09:40:18Z"}
• {"year"=>2020, "month"=>2, "doi"=>"10.1371/journal.pmed.0050066", "f1000_id"=>"1108234", "url"=>"https://f1000.com/prime/1108234", "score"=>3, "classifications"=>["confirmation", "new_finding"], "updated_at"=>"2020-02-17T09:40:16Z"}