Acute and Chronic Effects of Particles on Hospital Admissions in New-England
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{"title"=>"Acute and chronic effects of particles on hospital admissions in New-England", "type"=>"journal", "authors"=>[{"first_name"=>"Itai", "last_name"=>"Kloog", "scopus_author_id"=>"23667564700"}, {"first_name"=>"Brent A.", "last_name"=>"Coull", "scopus_author_id"=>"7005844847"}, {"first_name"=>"Antonella", "last_name"=>"Zanobetti", "scopus_author_id"=>"6701354130"}, {"first_name"=>"Petros", "last_name"=>"Koutrakis", "scopus_author_id"=>"7005322431"}, {"first_name"=>"Joel D.", "last_name"=>"Schwartz", "scopus_author_id"=>"55729331400"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84859822416", "sgr"=>"84859822416", "pui"=>"364638454", "isbn"=>"1932-6203", "pmid"=>"22529923", "doi"=>"10.1371/journal.pone.0034664"}, "id"=>"a8e390e6-8402-3557-9572-3e128b86092c", "abstract"=>"BACKGROUND: Many studies have reported significant associations between exposure to PM(2.5) and hospital admissions, but all have focused on the effects of short-term exposure. In addition all these studies have relied on a limited number of PM(2.5) monitors in their study regions, which introduces exposure error, and excludes rural and suburban populations from locations in which monitors are not available, reducing generalizability and potentially creating selection bias.\\n\\nMETHODS: Using our novel prediction models for exposure combining land use regression with physical measurements (satellite aerosol optical depth) we investigated both the long and short term effects of PM(2.5) exposures on hospital admissions across New-England for all residents aged 65 and older. We performed separate Poisson regression analysis for each admission type: all respiratory, cardiovascular disease (CVD), stroke and diabetes. Daily admission counts in each zip code were regressed against long and short-term PM(2.5) exposure, temperature, socio-economic data and a spline of time to control for seasonal trends in baseline risk.\\n\\nRESULTS: We observed associations between both short-term and long-term exposure to PM(2.5) and hospitalization for all of the outcomes examined. In example, for respiratory diseases, for every 10-µg/m(3) increase in short-term PM(2.5) exposure there is a 0.70 percent increase in admissions (CI = 0.35 to 0.52) while concurrently for every 10-µg/m(3) increase in long-term PM(2.5) exposure there is a 4.22 percent increase in admissions (CI = 1.06 to 4.75).\\n\\nCONCLUSIONS: As with mortality studies, chronic exposure to particles is associated with substantially larger increases in hospital admissions than acute exposure and both can be detected simultaneously using our exposure models.", "link"=>"http://www.mendeley.com/research/acute-chronic-effects-particles-hospital-admissions-newengland", "reader_count"=>81, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Professor > Associate Professor"=>1, "Librarian"=>3, "Researcher"=>28, "Student > Doctoral Student"=>2, "Student > Ph. D. 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Student"=>14, "Student > Postgraduate"=>3, "Student > Master"=>10, "Other"=>4, "Student > Bachelor"=>6, "Lecturer"=>1, "Professor"=>6}, "reader_count_by_subject_area"=>{"Unspecified"=>7, "Agricultural and Biological Sciences"=>9, "Arts and Humanities"=>1, "Business, Management and Accounting"=>1, "Chemistry"=>2, "Computer Science"=>2, "Earth and Planetary Sciences"=>3, "Economics, Econometrics and Finance"=>2, "Engineering"=>2, "Environmental Science"=>29, "Biochemistry, Genetics and Molecular Biology"=>1, "Mathematics"=>5, "Medicine and Dentistry"=>9, "Neuroscience"=>1, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Physics and Astronomy"=>1, "Social Sciences"=>5}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>9}, "Social Sciences"=>{"Social Sciences"=>5}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Mathematics"=>{"Mathematics"=>5}, "Unspecified"=>{"Unspecified"=>7}, "Environmental Science"=>{"Environmental Science"=>29}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Engineering"=>{"Engineering"=>2}, "Chemistry"=>{"Chemistry"=>2}, "Neuroscience"=>{"Neuroscience"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>3}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>9}, "Computer Science"=>{"Computer Science"=>2}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}}, "reader_count_by_country"=>{"Iran"=>1, "United States"=>7, "United Kingdom"=>1, "Italy"=>1, "Israel"=>1, "Portugal"=>1, "India"=>1}, "group_count"=>8}

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/651886"], "description"=>"<p>Descriptive statistics stratified by long term exposure: Hospital admissions by type of admission across New-England for the years 2000–2006.</p>", "links"=>[], "tags"=>["stratified", "admissions", "new-england", "years"], "article_id"=>322371, "categories"=>["Biological Sciences", "Medicine", "Biotechnology"], "users"=>["Itai Kloog", "Brent A. Coull", "Antonella Zanobetti", "Petros Koutrakis", "Joel D. Schwartz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0034664.t001", "stats"=>{"downloads"=>2, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Descriptive_statistics_stratified_by_long_term_exposure_Hospital_admissions_by_type_of_admission_across_New_England_for_the_years_2000_8211_2006_/322371", "title"=>"Descriptive statistics stratified by long term exposure: Hospital admissions by type of admission across New-England for the years 2000–2006.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-04-17 00:39:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/651779"], "description"=>"<p> Map of the study area showing the residential location of admission cases juxtaposed over a sample PM2.5 10×10 km pollution grid for 01/07/2001.</p>", "links"=>[], "tags"=>["cases", "juxtaposed", "km", "grid"], "article_id"=>322265, "categories"=>["Biological Sciences", "Medicine", "Biotechnology"], "users"=>["Itai Kloog", "Brent A. Coull", "Antonella Zanobetti", "Petros Koutrakis", "Joel D. Schwartz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0034664.g001", "stats"=>{"downloads"=>0, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Map_of_the_study_area_showing_the_residential_location_of_admission_cases_juxtaposed_over_a_sample_PM2_5_10_215_10_km_pollution_grid_for_01_07_2001_/322265", "title"=>"Map of the study area showing the residential location of admission cases juxtaposed over a sample PM2.5 10×10 km pollution grid for 01/07/2001.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-04-17 00:37:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/336126", "https://ndownloader.figshare.com/files/336200"], "description"=>"<div><h3>Background</h3><p>Many studies have reported significant associations between exposure to PM<sub>2.5</sub> and hospital admissions, but all have focused on the effects of short-term exposure. In addition all these studies have relied on a limited number of PM<sub>2.5</sub> monitors in their study regions, which introduces exposure error, and excludes rural and suburban populations from locations in which monitors are not available, reducing generalizability and potentially creating selection bias.</p> <h3>Methods</h3><p>Using our novel prediction models for exposure combining land use regression with physical measurements (satellite aerosol optical depth) we investigated both the long and short term effects of PM<sub>2.5</sub> exposures on hospital admissions across New-England for all residents aged 65 and older. We performed separate Poisson regression analysis for each admission type: all respiratory, cardiovascular disease (CVD), stroke and diabetes. Daily admission counts in each zip code were regressed against long and short-term PM<sub>2.5</sub> exposure, temperature, socio-economic data and a spline of time to control for seasonal trends in baseline risk.</p> <h3>Results</h3><p>We observed associations between both short-term and long-term exposure to PM<sub>2.5</sub> and hospitalization for all of the outcomes examined. In example, for respiratory diseases, for every10-µg/m<sup>3</sup> increase in <em>short-term</em> PM<sub>2.5</sub> exposure there is a 0.70 percent increase in admissions (CI = 0.35 to 0.52) while concurrently for every10-µg/m<sup>3</sup> increase in <em>long-term</em> PM<sub>2.5</sub> exposure there is a 4.22 percent increase in admissions (CI = 1.06 to 4.75).</p> <h3>Conclusions</h3><p>As with mortality studies, chronic exposure to particles is associated with substantially larger increases in hospital admissions than acute exposure and both can be detected simultaneously using our exposure models.</p> </div>", "links"=>[], "tags"=>["acute", "effects", "particles", "admissions", "new-england"], "article_id"=>126424, "categories"=>["Biological Sciences", "Medicine", "Biotechnology"], "users"=>["Itai Kloog", "Brent A. Coull", "Antonella Zanobetti", "Petros Koutrakis", "Joel D. Schwartz"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0034664.s001", "https://dx.doi.org/10.1371/journal.pone.0034664.s002"], "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Acute_and_Chronic_Effects_of_Particles_on_Hospital_Admissions_in_New_England/126424", "title"=>"Acute and Chronic Effects of Particles on Hospital Admissions in New-England", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-04-17 01:47:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/651929"], "description"=>"<p>Note: <sup>a</sup>Values are percent.</p>", "links"=>[], "tags"=>["percent", "admissions", "10"], "article_id"=>322418, "categories"=>["Biological Sciences", "Medicine", "Biotechnology"], "users"=>["Itai Kloog", "Brent A. Coull", "Antonella Zanobetti", "Petros Koutrakis", "Joel D. Schwartz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0034664.t003", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Estimated_percent_increase_in_hospital_admissions_for_a_10_g_m_3_increase_for_both_short_term_and_long_term_PM_2_5_by_cause_of_admission_/322418", "title"=>"Estimated percent increase in hospital admissions for a 10 μg/m<sup>3</sup> increase for both short term and long term PM<sub>2.5</sub> by cause of admission.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-04-17 00:40:18"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"8", "full-text"=>"6", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"8"}
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Relative Metric

{"start_date"=>"2012-01-01T00:00:00Z", "end_date"=>"2012-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Medicine and health sciences/Health care", "average_usage"=>[335, 575, 699, 804, 900, 994, 1119, 1215, 1317, 1408, 1509, 1583, 1664, 1732, 1802, 1873, 1945, 2020, 2104, 2190, 2259, 2325, 2400, 2463, 2548]}, {"subject_area"=>"/Physical sciences", "average_usage"=>[304, 506, 616, 712, 799, 879, 968, 1052, 1134, 1212, 1284, 1357, 1427, 1494, 1557, 1621, 1689, 1756, 1823, 1883, 1944, 1997, 2056, 2118, 2171]}, {"subject_area"=>"/Physical sciences/Materials science", "average_usage"=>[314, 504, 614, 722, 798, 877, 957, 1055, 1131, 1207, 1278, 1350, 1430, 1503, 1570, 1640, 1694, 1774, 1844, 1915, 1971, 2046, 2104, 2175, 2251]}, {"subject_area"=>"/Social sciences/Human geography", "average_usage"=>[349, 511, 586, 696, 768, 841, 924, 1003, 1071, 1145, 1226, 1291, 1370, 1428, 1497, 1553, 1612, 1660, 1723, 1805, 1865, 1922, 1981, 2043, 2100]}]}
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