Spatial variation in hyperthermia emergency department visits among those with employer-based insurance in the United States – a case-crossover analysis View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-12

AUTHORS

Shubhayu Saha, John W Brock, Ambarish Vaidyanathan, David R Easterling, George Luber

ABSTRACT

BACKGROUND: Predictions of intense heat waves across the United States will lead to localized health impacts, most of which are preventable. There is a need to better understand the spatial variation in the morbidity impacts associated with extreme heat across the country to prevent such adverse health outcomes. METHODS: Hyperthermia-related emergency department (ED) visits were obtained from the Truven Health MarketScan(®) Research dataset for 2000-2010. Three measures of daily ambient heat were constructed using meteorological observations from the National Climatic Data Center (maximum temperature, heat index) and the Spatial Synoptic Classification. Using a time-stratified case crossover approach, odds ratio of hyperthermia-related ED visit were estimated for the three different heat measures. Random effects meta-analysis was used to combine the odds ratios for 94 Metropolitan Statistical Areas (MSA) to examine the spatial variation by eight latitude categories and nine U.S. climate regions. RESULTS: Examination of lags for all three temperature measures showed that the odds ratio of ED visit was statistically significant and highest on the day of the ED visit. For heat waves lasting two or more days, additional statistically significant association was observed when heat index and synoptic classification was used as the temperature measure. These results were insensitive to the inclusion of air pollution measures. On average, the maximum temperature on the day of an ED visit was 93.4°F in 'South' and 81.9°F in the 'Northwest' climatic regions of United States. The meta-analysis showed higher odds ratios of hyperthermia ED visit in the central and the northern parts of the country compared to the south and southwest. CONCLUSION: The results showed spatial variation in average temperature on days of ED visit and odds ratio for hyperthermia ED visits associated with extreme heat across United States. This suggests that heat response plans need to be customized for different regions and the potential role of hyperthermia ED visits in syndromic surveillance for extreme heat. More... »

PAGES

20

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12940-015-0005-z

DOI

http://dx.doi.org/10.1186/s12940-015-0005-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1037914815

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/25888865


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1117", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Public Health and Health Services", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Air Pollutants", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Cross-Over Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Emergency Service, Hospital", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Extreme Heat", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Fever", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Health Benefit Plans, Employee", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Odds Ratio", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Ozone", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Particulate Matter", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Risk Factors", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Seasons", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Time Factors", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "United States", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "National Center for Environmental Health", 
          "id": "https://www.grid.ac/institutes/grid.416778.b", 
          "name": [
            "Climate and Health Program, Division of Environmental Hazards and Health Effects, National Center for Environmental Health, Centers for Disease Control and Prevention, 30341, Atlanta, GA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Saha", 
        "givenName": "Shubhayu", 
        "id": "sg:person.0752563176.96", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752563176.96"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Warren Wilson College", 
          "id": "https://www.grid.ac/institutes/grid.439071.8", 
          "name": [
            "Departments of Chemistry and Environmental Studies, Warren Wilson College, CPO 6066, PO Box 9000, 28815, Asheville, NC, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Brock", 
        "givenName": "John W", 
        "id": "sg:person.0753100162.03", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0753100162.03"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Center for Environmental Health", 
          "id": "https://www.grid.ac/institutes/grid.416778.b", 
          "name": [
            "Environmental Health Tracking Branch, Division of Environmental Hazards and Health Effects, National Center for Environmental Health, Centers for Disease Control and Prevention, 30341, Atlanta, GA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Vaidyanathan", 
        "givenName": "Ambarish", 
        "id": "sg:person.01324216460.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01324216460.27"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Centers for Environmental Information", 
          "id": "https://www.grid.ac/institutes/grid.454206.1", 
          "name": [
            "National Climatic Data Center, 28801, Asheville, NC, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Easterling", 
        "givenName": "David R", 
        "id": "sg:person.010026231077.65", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010026231077.65"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Center for Environmental Health", 
          "id": "https://www.grid.ac/institutes/grid.416778.b", 
          "name": [
            "Climate and Health Program, Division of Environmental Hazards and Health Effects, National Center for Environmental Health, Centers for Disease Control and Prevention, 30341, Atlanta, GA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Luber", 
        "givenName": "George", 
        "id": "sg:person.0636334576.11", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0636334576.11"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s00484-012-0593-z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001590110", 
          "https://doi.org/10.1007/s00484-012-0593-z"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1289/ehp.1104728", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001594361"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/01.ede.0000239688.70829.63", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004912688"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/01.ede.0000239688.70829.63", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004912688"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/bams-d-11-00197.1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006056205"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0011984", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006612909"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11069-008-9327-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007879270", 
          "https://doi.org/10.1007/s11069-008-9327-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1289/ehp.11594", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008537846"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.maturitas.2011.03.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009800337"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/sim.5963", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010172683"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/ijerph110606433", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011633000"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1476-072x-12-12", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013068664", 
          "https://doi.org/10.1186/1476-072x-12-12"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1289/ehp.1003198", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013245726"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1289/ehp.0901485", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014671102"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1164/rccm.201211-1969oc", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015146557"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/aje/kwr417", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019802208"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amepre.2008.08.021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023312556"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1476-072x-12-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024716297", 
          "https://doi.org/10.1186/1476-072x-12-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/bmj.e8050", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025572376"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0450(2001)040<0762:otdoah>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027049520"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/ede.0b013e31828ac01b", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027162832"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/ede.0b013e31828ac01b", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027162832"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2009gl040736", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029206876"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2009gl040736", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029206876"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/ede.0b013e3181ad5522", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029694948"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/ede.0b013e3181ad5522", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029694948"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/ede.0b013e3181ad5522", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029694948"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/ede.0b013e31826b7f97", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030274236"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/ede.0b013e31826b7f97", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030274236"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/01.ede.0000181315.18836.9d", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030611865"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/01.ede.0000181315.18836.9d", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030611865"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/01.ede.0000181315.18836.9d", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030611865"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amepre.2012.09.058", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032319434"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amepre.2008.08.020", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036226752"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/ede.0000000000000123", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036274003"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/ede.0000000000000123", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036274003"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1289/ehp.1307392", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038419766"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00484-014-0848-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038458352", 
          "https://doi.org/10.1007/s00484-014-0848-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.envres.2010.05.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040447486"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmra011089", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040520339"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0477(1998)079<0231:stopaf>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043883168"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/sim.1186", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047418980"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1289/ehp.1002313", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051759046"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1289/ehp.1306796", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052912896"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/1403494810377685", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064001799"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/1403494810377685", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064001799"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1289/ehp.6336", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064741793"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2105/ajph.2009.169748", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068844639"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2105/ajph.94.9.1520", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068879730"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3354/cr024255", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071159559"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1078429161", 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2015-12", 
    "datePublishedReg": "2015-12-01", 
    "description": "BACKGROUND: Predictions of intense heat waves across the United States will lead to localized health impacts, most of which are preventable. There is a need to better understand the spatial variation in the morbidity impacts associated with extreme heat across the country to prevent such adverse health outcomes.\nMETHODS: Hyperthermia-related emergency department (ED) visits were obtained from the Truven Health MarketScan(\u00ae) Research dataset for 2000-2010. Three measures of daily ambient heat were constructed using meteorological observations from the National Climatic Data Center (maximum temperature, heat index) and the Spatial Synoptic Classification. Using a time-stratified case crossover approach, odds ratio of hyperthermia-related ED visit were estimated for the three different heat measures. Random effects meta-analysis was used to combine the odds ratios for 94 Metropolitan Statistical Areas (MSA) to examine the spatial variation by eight latitude categories and nine U.S. climate regions.\nRESULTS: Examination of lags for all three temperature measures showed that the odds ratio of ED visit was statistically significant and highest on the day of the ED visit. For heat waves lasting two or more days, additional statistically significant association was observed when heat index and synoptic classification was used as the temperature measure. These results were insensitive to the inclusion of air pollution measures. On average, the maximum temperature on the day of an ED visit was 93.4\u00b0F in 'South' and 81.9\u00b0F in the 'Northwest' climatic regions of United States. The meta-analysis showed higher odds ratios of hyperthermia ED visit in the central and the northern parts of the country compared to the south and southwest.\nCONCLUSION: The results showed spatial variation in average temperature on days of ED visit and odds ratio for hyperthermia ED visits associated with extreme heat across United States. This suggests that heat response plans need to be customized for different regions and the potential role of hyperthermia ED visits in syndromic surveillance for extreme heat.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s12940-015-0005-z", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1327425", 
        "issn": [
          "1476-069X"
        ], 
        "name": "Environmental Health", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "14"
      }
    ], 
    "name": "Spatial variation in hyperthermia emergency department visits among those with employer-based insurance in the United States \u2013 a case-crossover analysis", 
    "pagination": "20", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "b49d0517f547d79a8625d5e1225d040f4ad69eec59cd9288d201a6caaa7bf631"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "25888865"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101147645"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s12940-015-0005-z"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1037914815"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s12940-015-0005-z", 
      "https://app.dimensions.ai/details/publication/pub.1037914815"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T13:10", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000367_0000000367/records_88247_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1186%2Fs12940-015-0005-z"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s12940-015-0005-z'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12940-015-0005-z'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12940-015-0005-z'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12940-015-0005-z'


 

This table displays all metadata directly associated to this object as RDF triples.

282 TRIPLES      21 PREDICATES      83 URIs      34 LITERALS      22 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s12940-015-0005-z schema:about N149ed1cf58bc40f19fe45aea6525b34c
2 N3985262d9a9745bfaa934ae5c6ea82b8
3 N482926f9bc324650bf4c1cc9ddeded51
4 N6dc28965e4fa4e3381520f81403e3452
5 N71a13d4320d147d480655fe04daea55b
6 N7523940102624fceb13d7128de99d72d
7 N7f9c43e152584b3b8d6b958aa85e53b7
8 N8e73606e5f2c46e7a979bd6c24074713
9 N9248644727eb46a0bceb54fb52b204ec
10 Nbb1ab6a708934845a7b39a37adf77217
11 Nbb3d236ffd1041b88f64afde3040a5cd
12 Nbc4f0bd7b81241c19ca97106e4e995b3
13 Nd167cf6b8cba4f88a565d459950f81f7
14 anzsrc-for:11
15 anzsrc-for:1117
16 schema:author N6b4c513d1a6a436d88c898c47fd28a18
17 schema:citation sg:pub.10.1007/s00484-012-0593-z
18 sg:pub.10.1007/s00484-014-0848-y
19 sg:pub.10.1007/s11069-008-9327-2
20 sg:pub.10.1186/1476-072x-12-1
21 sg:pub.10.1186/1476-072x-12-12
22 https://app.dimensions.ai/details/publication/pub.1078429161
23 https://doi.org/10.1002/sim.1186
24 https://doi.org/10.1002/sim.5963
25 https://doi.org/10.1016/j.amepre.2008.08.020
26 https://doi.org/10.1016/j.amepre.2008.08.021
27 https://doi.org/10.1016/j.amepre.2012.09.058
28 https://doi.org/10.1016/j.envres.2010.05.006
29 https://doi.org/10.1016/j.maturitas.2011.03.008
30 https://doi.org/10.1029/2009gl040736
31 https://doi.org/10.1056/nejmra011089
32 https://doi.org/10.1093/aje/kwr417
33 https://doi.org/10.1097/01.ede.0000181315.18836.9d
34 https://doi.org/10.1097/01.ede.0000239688.70829.63
35 https://doi.org/10.1097/ede.0000000000000123
36 https://doi.org/10.1097/ede.0b013e3181ad5522
37 https://doi.org/10.1097/ede.0b013e31826b7f97
38 https://doi.org/10.1097/ede.0b013e31828ac01b
39 https://doi.org/10.1136/bmj.e8050
40 https://doi.org/10.1164/rccm.201211-1969oc
41 https://doi.org/10.1175/1520-0450(2001)040<0762:otdoah>2.0.co;2
42 https://doi.org/10.1175/1520-0477(1998)079<0231:stopaf>2.0.co;2
43 https://doi.org/10.1175/bams-d-11-00197.1
44 https://doi.org/10.1177/1403494810377685
45 https://doi.org/10.1289/ehp.0901485
46 https://doi.org/10.1289/ehp.1002313
47 https://doi.org/10.1289/ehp.1003198
48 https://doi.org/10.1289/ehp.1104728
49 https://doi.org/10.1289/ehp.11594
50 https://doi.org/10.1289/ehp.1306796
51 https://doi.org/10.1289/ehp.1307392
52 https://doi.org/10.1289/ehp.6336
53 https://doi.org/10.1371/journal.pone.0011984
54 https://doi.org/10.2105/ajph.2009.169748
55 https://doi.org/10.2105/ajph.94.9.1520
56 https://doi.org/10.3354/cr024255
57 https://doi.org/10.3390/ijerph110606433
58 schema:datePublished 2015-12
59 schema:datePublishedReg 2015-12-01
60 schema:description BACKGROUND: Predictions of intense heat waves across the United States will lead to localized health impacts, most of which are preventable. There is a need to better understand the spatial variation in the morbidity impacts associated with extreme heat across the country to prevent such adverse health outcomes. METHODS: Hyperthermia-related emergency department (ED) visits were obtained from the Truven Health MarketScan(®) Research dataset for 2000-2010. Three measures of daily ambient heat were constructed using meteorological observations from the National Climatic Data Center (maximum temperature, heat index) and the Spatial Synoptic Classification. Using a time-stratified case crossover approach, odds ratio of hyperthermia-related ED visit were estimated for the three different heat measures. Random effects meta-analysis was used to combine the odds ratios for 94 Metropolitan Statistical Areas (MSA) to examine the spatial variation by eight latitude categories and nine U.S. climate regions. RESULTS: Examination of lags for all three temperature measures showed that the odds ratio of ED visit was statistically significant and highest on the day of the ED visit. For heat waves lasting two or more days, additional statistically significant association was observed when heat index and synoptic classification was used as the temperature measure. These results were insensitive to the inclusion of air pollution measures. On average, the maximum temperature on the day of an ED visit was 93.4°F in 'South' and 81.9°F in the 'Northwest' climatic regions of United States. The meta-analysis showed higher odds ratios of hyperthermia ED visit in the central and the northern parts of the country compared to the south and southwest. CONCLUSION: The results showed spatial variation in average temperature on days of ED visit and odds ratio for hyperthermia ED visits associated with extreme heat across United States. This suggests that heat response plans need to be customized for different regions and the potential role of hyperthermia ED visits in syndromic surveillance for extreme heat.
61 schema:genre research_article
62 schema:inLanguage en
63 schema:isAccessibleForFree true
64 schema:isPartOf N46fb1cdea31b4bdf871264e9884af046
65 N987d7b5f240444e1be65fb16f90d4468
66 sg:journal.1327425
67 schema:name Spatial variation in hyperthermia emergency department visits among those with employer-based insurance in the United States – a case-crossover analysis
68 schema:pagination 20
69 schema:productId N0474a6f661d2442c9cb272f5f67fa4ce
70 N1b294d2e610844788fb2c7ab1e933c10
71 N4559732dcae14e57a68e28963a45bade
72 N60ec95752ba54bc4a9a81a73bddb5f90
73 N69aedf5703ad4532866d3cb227cb7589
74 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037914815
75 https://doi.org/10.1186/s12940-015-0005-z
76 schema:sdDatePublished 2019-04-11T13:10
77 schema:sdLicense https://scigraph.springernature.com/explorer/license/
78 schema:sdPublisher N94e2578b9be8419d811c53f1e72c6eef
79 schema:url http://link.springer.com/10.1186%2Fs12940-015-0005-z
80 sgo:license sg:explorer/license/
81 sgo:sdDataset articles
82 rdf:type schema:ScholarlyArticle
83 N02ca3033973843bcb03a2625a45af600 rdf:first sg:person.0753100162.03
84 rdf:rest N6e55e7f4fdc94d25beb19a24d0577f0f
85 N0474a6f661d2442c9cb272f5f67fa4ce schema:name nlm_unique_id
86 schema:value 101147645
87 rdf:type schema:PropertyValue
88 N149ed1cf58bc40f19fe45aea6525b34c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
89 schema:name Particulate Matter
90 rdf:type schema:DefinedTerm
91 N1b294d2e610844788fb2c7ab1e933c10 schema:name pubmed_id
92 schema:value 25888865
93 rdf:type schema:PropertyValue
94 N3985262d9a9745bfaa934ae5c6ea82b8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
95 schema:name Cross-Over Studies
96 rdf:type schema:DefinedTerm
97 N4559732dcae14e57a68e28963a45bade schema:name doi
98 schema:value 10.1186/s12940-015-0005-z
99 rdf:type schema:PropertyValue
100 N46fb1cdea31b4bdf871264e9884af046 schema:issueNumber 1
101 rdf:type schema:PublicationIssue
102 N482926f9bc324650bf4c1cc9ddeded51 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
103 schema:name Risk Factors
104 rdf:type schema:DefinedTerm
105 N55d434a34329495fad4b846a09610403 rdf:first sg:person.010026231077.65
106 rdf:rest Nf6c88837a63743c2a8f62196ecc187aa
107 N60ec95752ba54bc4a9a81a73bddb5f90 schema:name dimensions_id
108 schema:value pub.1037914815
109 rdf:type schema:PropertyValue
110 N69aedf5703ad4532866d3cb227cb7589 schema:name readcube_id
111 schema:value b49d0517f547d79a8625d5e1225d040f4ad69eec59cd9288d201a6caaa7bf631
112 rdf:type schema:PropertyValue
113 N6b4c513d1a6a436d88c898c47fd28a18 rdf:first sg:person.0752563176.96
114 rdf:rest N02ca3033973843bcb03a2625a45af600
115 N6dc28965e4fa4e3381520f81403e3452 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
116 schema:name Air Pollutants
117 rdf:type schema:DefinedTerm
118 N6e55e7f4fdc94d25beb19a24d0577f0f rdf:first sg:person.01324216460.27
119 rdf:rest N55d434a34329495fad4b846a09610403
120 N71a13d4320d147d480655fe04daea55b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
121 schema:name Health Benefit Plans, Employee
122 rdf:type schema:DefinedTerm
123 N7523940102624fceb13d7128de99d72d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
124 schema:name Seasons
125 rdf:type schema:DefinedTerm
126 N7f9c43e152584b3b8d6b958aa85e53b7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
127 schema:name Extreme Heat
128 rdf:type schema:DefinedTerm
129 N8e73606e5f2c46e7a979bd6c24074713 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
130 schema:name Ozone
131 rdf:type schema:DefinedTerm
132 N9248644727eb46a0bceb54fb52b204ec schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
133 schema:name Fever
134 rdf:type schema:DefinedTerm
135 N94e2578b9be8419d811c53f1e72c6eef schema:name Springer Nature - SN SciGraph project
136 rdf:type schema:Organization
137 N987d7b5f240444e1be65fb16f90d4468 schema:volumeNumber 14
138 rdf:type schema:PublicationVolume
139 Nbb1ab6a708934845a7b39a37adf77217 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
140 schema:name United States
141 rdf:type schema:DefinedTerm
142 Nbb3d236ffd1041b88f64afde3040a5cd schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
143 schema:name Emergency Service, Hospital
144 rdf:type schema:DefinedTerm
145 Nbc4f0bd7b81241c19ca97106e4e995b3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
146 schema:name Odds Ratio
147 rdf:type schema:DefinedTerm
148 Nd167cf6b8cba4f88a565d459950f81f7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
149 schema:name Time Factors
150 rdf:type schema:DefinedTerm
151 Nf6c88837a63743c2a8f62196ecc187aa rdf:first sg:person.0636334576.11
152 rdf:rest rdf:nil
153 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
154 schema:name Medical and Health Sciences
155 rdf:type schema:DefinedTerm
156 anzsrc-for:1117 schema:inDefinedTermSet anzsrc-for:
157 schema:name Public Health and Health Services
158 rdf:type schema:DefinedTerm
159 sg:journal.1327425 schema:issn 1476-069X
160 schema:name Environmental Health
161 rdf:type schema:Periodical
162 sg:person.010026231077.65 schema:affiliation https://www.grid.ac/institutes/grid.454206.1
163 schema:familyName Easterling
164 schema:givenName David R
165 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010026231077.65
166 rdf:type schema:Person
167 sg:person.01324216460.27 schema:affiliation https://www.grid.ac/institutes/grid.416778.b
168 schema:familyName Vaidyanathan
169 schema:givenName Ambarish
170 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01324216460.27
171 rdf:type schema:Person
172 sg:person.0636334576.11 schema:affiliation https://www.grid.ac/institutes/grid.416778.b
173 schema:familyName Luber
174 schema:givenName George
175 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0636334576.11
176 rdf:type schema:Person
177 sg:person.0752563176.96 schema:affiliation https://www.grid.ac/institutes/grid.416778.b
178 schema:familyName Saha
179 schema:givenName Shubhayu
180 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752563176.96
181 rdf:type schema:Person
182 sg:person.0753100162.03 schema:affiliation https://www.grid.ac/institutes/grid.439071.8
183 schema:familyName Brock
184 schema:givenName John W
185 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0753100162.03
186 rdf:type schema:Person
187 sg:pub.10.1007/s00484-012-0593-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1001590110
188 https://doi.org/10.1007/s00484-012-0593-z
189 rdf:type schema:CreativeWork
190 sg:pub.10.1007/s00484-014-0848-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1038458352
191 https://doi.org/10.1007/s00484-014-0848-y
192 rdf:type schema:CreativeWork
193 sg:pub.10.1007/s11069-008-9327-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007879270
194 https://doi.org/10.1007/s11069-008-9327-2
195 rdf:type schema:CreativeWork
196 sg:pub.10.1186/1476-072x-12-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024716297
197 https://doi.org/10.1186/1476-072x-12-1
198 rdf:type schema:CreativeWork
199 sg:pub.10.1186/1476-072x-12-12 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013068664
200 https://doi.org/10.1186/1476-072x-12-12
201 rdf:type schema:CreativeWork
202 https://app.dimensions.ai/details/publication/pub.1078429161 schema:CreativeWork
203 https://doi.org/10.1002/sim.1186 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047418980
204 rdf:type schema:CreativeWork
205 https://doi.org/10.1002/sim.5963 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010172683
206 rdf:type schema:CreativeWork
207 https://doi.org/10.1016/j.amepre.2008.08.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036226752
208 rdf:type schema:CreativeWork
209 https://doi.org/10.1016/j.amepre.2008.08.021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023312556
210 rdf:type schema:CreativeWork
211 https://doi.org/10.1016/j.amepre.2012.09.058 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032319434
212 rdf:type schema:CreativeWork
213 https://doi.org/10.1016/j.envres.2010.05.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040447486
214 rdf:type schema:CreativeWork
215 https://doi.org/10.1016/j.maturitas.2011.03.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009800337
216 rdf:type schema:CreativeWork
217 https://doi.org/10.1029/2009gl040736 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029206876
218 rdf:type schema:CreativeWork
219 https://doi.org/10.1056/nejmra011089 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040520339
220 rdf:type schema:CreativeWork
221 https://doi.org/10.1093/aje/kwr417 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019802208
222 rdf:type schema:CreativeWork
223 https://doi.org/10.1097/01.ede.0000181315.18836.9d schema:sameAs https://app.dimensions.ai/details/publication/pub.1030611865
224 rdf:type schema:CreativeWork
225 https://doi.org/10.1097/01.ede.0000239688.70829.63 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004912688
226 rdf:type schema:CreativeWork
227 https://doi.org/10.1097/ede.0000000000000123 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036274003
228 rdf:type schema:CreativeWork
229 https://doi.org/10.1097/ede.0b013e3181ad5522 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029694948
230 rdf:type schema:CreativeWork
231 https://doi.org/10.1097/ede.0b013e31826b7f97 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030274236
232 rdf:type schema:CreativeWork
233 https://doi.org/10.1097/ede.0b013e31828ac01b schema:sameAs https://app.dimensions.ai/details/publication/pub.1027162832
234 rdf:type schema:CreativeWork
235 https://doi.org/10.1136/bmj.e8050 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025572376
236 rdf:type schema:CreativeWork
237 https://doi.org/10.1164/rccm.201211-1969oc schema:sameAs https://app.dimensions.ai/details/publication/pub.1015146557
238 rdf:type schema:CreativeWork
239 https://doi.org/10.1175/1520-0450(2001)040<0762:otdoah>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027049520
240 rdf:type schema:CreativeWork
241 https://doi.org/10.1175/1520-0477(1998)079<0231:stopaf>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043883168
242 rdf:type schema:CreativeWork
243 https://doi.org/10.1175/bams-d-11-00197.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006056205
244 rdf:type schema:CreativeWork
245 https://doi.org/10.1177/1403494810377685 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064001799
246 rdf:type schema:CreativeWork
247 https://doi.org/10.1289/ehp.0901485 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014671102
248 rdf:type schema:CreativeWork
249 https://doi.org/10.1289/ehp.1002313 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051759046
250 rdf:type schema:CreativeWork
251 https://doi.org/10.1289/ehp.1003198 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013245726
252 rdf:type schema:CreativeWork
253 https://doi.org/10.1289/ehp.1104728 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001594361
254 rdf:type schema:CreativeWork
255 https://doi.org/10.1289/ehp.11594 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008537846
256 rdf:type schema:CreativeWork
257 https://doi.org/10.1289/ehp.1306796 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052912896
258 rdf:type schema:CreativeWork
259 https://doi.org/10.1289/ehp.1307392 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038419766
260 rdf:type schema:CreativeWork
261 https://doi.org/10.1289/ehp.6336 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064741793
262 rdf:type schema:CreativeWork
263 https://doi.org/10.1371/journal.pone.0011984 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006612909
264 rdf:type schema:CreativeWork
265 https://doi.org/10.2105/ajph.2009.169748 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068844639
266 rdf:type schema:CreativeWork
267 https://doi.org/10.2105/ajph.94.9.1520 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068879730
268 rdf:type schema:CreativeWork
269 https://doi.org/10.3354/cr024255 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071159559
270 rdf:type schema:CreativeWork
271 https://doi.org/10.3390/ijerph110606433 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011633000
272 rdf:type schema:CreativeWork
273 https://www.grid.ac/institutes/grid.416778.b schema:alternateName National Center for Environmental Health
274 schema:name Climate and Health Program, Division of Environmental Hazards and Health Effects, National Center for Environmental Health, Centers for Disease Control and Prevention, 30341, Atlanta, GA, USA
275 Environmental Health Tracking Branch, Division of Environmental Hazards and Health Effects, National Center for Environmental Health, Centers for Disease Control and Prevention, 30341, Atlanta, GA, USA
276 rdf:type schema:Organization
277 https://www.grid.ac/institutes/grid.439071.8 schema:alternateName Warren Wilson College
278 schema:name Departments of Chemistry and Environmental Studies, Warren Wilson College, CPO 6066, PO Box 9000, 28815, Asheville, NC, USA
279 rdf:type schema:Organization
280 https://www.grid.ac/institutes/grid.454206.1 schema:alternateName National Centers for Environmental Information
281 schema:name National Climatic Data Center, 28801, Asheville, NC, USA
282 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...