The associations between daily spring pollen counts, over-the-counter allergy medication sales, and asthma syndrome emergency department visits in New York City, 2002-2012.
Identifieur interne : 001B10 ( Main/Exploration ); précédent : 001B09; suivant : 001B11The associations between daily spring pollen counts, over-the-counter allergy medication sales, and asthma syndrome emergency department visits in New York City, 2002-2012.
Auteurs : Kazuhiko Ito [États-Unis] ; Kate R. Weinberger [États-Unis] ; Guy S. Robinson [États-Unis] ; Perry E. Sheffield [États-Unis] ; Ramona Lall [États-Unis] ; Robert Mathes [États-Unis] ; Zev Ross [États-Unis] ; Patrick L. Kinney [États-Unis] ; Thomas D. Matte [États-Unis]Source :
- Environmental health : a global access science source [ 1476-069X ] ; 2015.
Descripteurs français
- KwdFr :
- Adolescent (MeSH), Adulte (MeSH), Adulte d'âge moyen (MeSH), Allergènes (effets indésirables), Asthme (épidémiologie), Asthme (étiologie), Enfant (MeSH), Enfant d'âge préscolaire (MeSH), Femelle (MeSH), Humains (MeSH), Hypersensibilité (épidémiologie), Hypersensibilité (étiologie), Jeune adulte (MeSH), Mâle (MeSH), Médicaments multi-ingrédients contre le rhume, la grippe et l'allergie (économie), Médicaments sans ordonnance (économie), New York (ville) (épidémiologie), Nourrisson (MeSH), Nouveau-né (MeSH), Pollen (effets indésirables), Service hospitalier d'urgences (statistiques et données numériques), Sujet âgé (MeSH), Sujet âgé de 80 ans ou plus (MeSH).
- MESH :
- effets indésirables : Allergènes, Pollen.
- statistiques et données numériques : Service hospitalier d'urgences.
- économie : Médicaments multi-ingrédients contre le rhume, la grippe et l'allergie, Médicaments sans ordonnance.
- épidémiologie : Asthme, Hypersensibilité, New York (ville).
- étiologie : Asthme, Hypersensibilité.
- Adolescent, Adulte, Adulte d'âge moyen, Enfant, Enfant d'âge préscolaire, Femelle, Humains, Jeune adulte, Mâle, Nourrisson, Nouveau-né, Sujet âgé, Sujet âgé de 80 ans ou plus.
English descriptors
- KwdEn :
- Adolescent (MeSH), Adult (MeSH), Aged (MeSH), Aged, 80 and over (MeSH), Allergens (adverse effects), Asthma (epidemiology), Asthma (etiology), Child (MeSH), Child, Preschool (MeSH), Emergency Service, Hospital (statistics & numerical data), Female (MeSH), Humans (MeSH), Hypersensitivity (epidemiology), Hypersensitivity (etiology), Infant (MeSH), Infant, Newborn (MeSH), Male (MeSH), Middle Aged (MeSH), Multi-Ingredient Cold, Flu, and Allergy Medications (economics), New York City (epidemiology), Nonprescription Drugs (economics), Pollen (adverse effects), Young Adult (MeSH).
- MESH :
- chemical , adverse effects : Allergens.
- chemical , economics : Multi-Ingredient Cold, Flu, and Allergy Medications, Nonprescription Drugs.
- adverse effects : Pollen.
- epidemiology : Asthma, Hypersensitivity, New York City.
- etiology : Asthma, Hypersensitivity.
- statistics & numerical data : Emergency Service, Hospital.
- Adolescent, Adult, Aged, Aged, 80 and over, Child, Child, Preschool, Female, Humans, Infant, Infant, Newborn, Male, Middle Aged, Young Adult.
Abstract
BACKGROUND
Many types of tree pollen trigger seasonal allergic illness, but their population-level impacts on allergy and asthma morbidity are not well established, likely due to the paucity of long records of daily pollen data that allow analysis of multi-day effects. Our objective in this study was therefore to determine the impacts of individual spring tree pollen types on over-the-counter allergy medication sales and asthma emergency department (ED) visits.
METHODS
Nine clinically-relevant spring tree pollen genera (elm, poplar, maple, birch, beech, ash, sycamore/London planetree, oak, and hickory) measured in Armonk, NY, were analyzed for their associations with over-the-counter allergy medication sales and daily asthma syndrome ED visits from patients' chief complaints or diagnosis codes in New York City during March 1st through June 10th, 2002-2012. Multi-day impacts of pollen on the outcomes (0-3 days and 0-7 days for the medication sales and ED visits, respectively) were estimated using a distributed lag Poisson time-series model adjusting for temporal trends, day-of-week, weather, and air pollution. For asthma syndrome ED visits, age groups were also analyzed. Year-to-year variation in the average peak dates and the 10th-to-90th percentile duration between pollen and the outcomes were also examined with Spearman's rank correlation.
RESULTS
Mid-spring pollen types (maple, birch, beech, ash, oak, and sycamore/London planetree) showed the strongest significant associations with both outcomes, with cumulative rate ratios up to 2.0 per 0-to-98th percentile pollen increase (e.g., 1.9 [95% CI: 1.7, 2.1] and 1.7 [95% CI: 1.5, 1.9] for the medication sales and ED visits, respectively, for ash). Lagged associations were longer for asthma syndrome ED visits than for the medication sales. Associations were strongest in children (ages 5-17; e.g., a cumulative rate ratio of 2.6 [95% CI: 2.1, 3.1] per 0-to-98th percentile increase in ash). The average peak dates and durations of some of these mid-spring pollen types were also associated with those of the outcomes.
CONCLUSIONS
Tree pollen peaking in mid-spring exhibit substantive impacts on allergy, and asthma exacerbations, particularly in children. Given the narrow time window of these pollen peak occurrences, public health and clinical approaches to anticipate and reduce allergy/asthma exacerbation should be developed.
DOI: 10.1186/s12940-015-0057-0
PubMed: 26310854
PubMed Central: PMC4549916
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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Kinney</name><affiliation wicri:level="4"><nlm:affiliation>Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, 10032-3727, USA. plk3@cumc.columbia.edu.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, 10032-3727</wicri:regionArea><orgName type="university">Université Columbia</orgName><placeName><settlement type="city">New York</settlement><region type="state">État de New York</region></placeName></affiliation></author><author><name sortKey="Matte, Thomas D" sort="Matte, Thomas D" uniqKey="Matte T" first="Thomas D" last="Matte">Thomas D. 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Weinberger</name><affiliation wicri:level="4"><nlm:affiliation>Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, 10032-3727, USA. krw2114@cumc.columbia.edu.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, 10032-3727</wicri:regionArea><orgName type="university">Université Columbia</orgName><placeName><settlement type="city">New York</settlement><region type="state">État de New York</region></placeName></affiliation></author><author><name sortKey="Robinson, Guy S" sort="Robinson, Guy S" uniqKey="Robinson G" first="Guy S" last="Robinson">Guy S. Robinson</name><affiliation wicri:level="1"><nlm:affiliation>Louis Calder Center, Biological Field Station, Fordham University, Armonk, New York, NY, 10504-1104, USA. grobinson@fordham.edu.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Louis Calder Center, Biological Field Station, Fordham University, Armonk, New York, NY, 10504-1104</wicri:regionArea><wicri:noRegion>10504-1104</wicri:noRegion></affiliation><affiliation wicri:level="1"><nlm:affiliation>Department of Natural Sciences, Fordham College at Lincoln Center, 113 West 60th Street, New York, NY, 10023, USA. grobinson@fordham.edu.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Natural Sciences, Fordham College at Lincoln Center, 113 West 60th Street, New York, NY, 10023</wicri:regionArea><wicri:noRegion>10023</wicri:noRegion></affiliation></author><author><name sortKey="Sheffield, Perry E" sort="Sheffield, Perry E" uniqKey="Sheffield P" first="Perry E" last="Sheffield">Perry E. Sheffield</name><affiliation wicri:level="1"><nlm:affiliation>Departments of Pediatrics and Preventive Medicine, Mount Sinai School of Medicine, 1 Gustave L. Levy Pl., Box 1512, New York, NY, 10029, USA. perry.sheffield@mssm.edu.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Departments of Pediatrics and Preventive Medicine, Mount Sinai School of Medicine, 1 Gustave L. Levy Pl., Box 1512, New York, NY, 10029</wicri:regionArea><wicri:noRegion>10029</wicri:noRegion></affiliation></author><author><name sortKey="Lall, Ramona" sort="Lall, Ramona" uniqKey="Lall R" first="Ramona" last="Lall">Ramona Lall</name><affiliation wicri:level="1"><nlm:affiliation>New York City Department of Health and Mental Hygiene, Bureau of Communicable Disease, Queens, NY, 11101, USA. rlall@health.nyc.gov.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>New York City Department of Health and Mental Hygiene, Bureau of Communicable Disease, Queens, NY, 11101</wicri:regionArea><wicri:noRegion>11101</wicri:noRegion></affiliation></author><author><name sortKey="Mathes, Robert" sort="Mathes, Robert" uniqKey="Mathes R" first="Robert" last="Mathes">Robert Mathes</name><affiliation wicri:level="1"><nlm:affiliation>New York City Department of Health and Mental Hygiene, Bureau of Communicable Disease, Queens, NY, 11101, USA. rmathes@health.nyc.gov.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>New York City Department of Health and Mental Hygiene, Bureau of Communicable Disease, Queens, NY, 11101</wicri:regionArea><wicri:noRegion>11101</wicri:noRegion></affiliation></author><author><name sortKey="Ross, Zev" sort="Ross, Zev" uniqKey="Ross Z" first="Zev" last="Ross">Zev Ross</name><affiliation wicri:level="1"><nlm:affiliation>ZevRoss Spatial Analysis, Ithaca, NY, 14850, USA. zev@zevross.com.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>ZevRoss Spatial Analysis, Ithaca, NY, 14850</wicri:regionArea><wicri:noRegion>14850</wicri:noRegion></affiliation></author><author><name sortKey="Kinney, Patrick L" sort="Kinney, Patrick L" uniqKey="Kinney P" first="Patrick L" last="Kinney">Patrick L. Kinney</name><affiliation wicri:level="4"><nlm:affiliation>Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, 10032-3727, USA. plk3@cumc.columbia.edu.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, 10032-3727</wicri:regionArea><orgName type="university">Université Columbia</orgName><placeName><settlement type="city">New York</settlement><region type="state">État de New York</region></placeName></affiliation></author><author><name sortKey="Matte, Thomas D" sort="Matte, Thomas D" uniqKey="Matte T" first="Thomas D" last="Matte">Thomas D. Matte</name><affiliation wicri:level="1"><nlm:affiliation>New York City Department of Health and Mental Hygiene, Bureau of Environmental Surveillance and Policy, New York, NY, 10013, USA. tmatte@health.nyc.gov.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>New York City Department of Health and Mental Hygiene, Bureau of Environmental Surveillance and Policy, New York, NY, 10013</wicri:regionArea><wicri:noRegion>10013</wicri:noRegion></affiliation></author></analytic><series><title level="j">Environmental health : a global access science source</title><idno type="eISSN">1476-069X</idno><imprint><date when="2015" type="published">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adolescent (MeSH)</term><term>Adult (MeSH)</term><term>Aged (MeSH)</term><term>Aged, 80 and over (MeSH)</term><term>Allergens (adverse effects)</term><term>Asthma (epidemiology)</term><term>Asthma (etiology)</term><term>Child (MeSH)</term><term>Child, Preschool (MeSH)</term><term>Emergency Service, Hospital (statistics & numerical data)</term><term>Female (MeSH)</term><term>Humans (MeSH)</term><term>Hypersensitivity (epidemiology)</term><term>Hypersensitivity (etiology)</term><term>Infant (MeSH)</term><term>Infant, Newborn (MeSH)</term><term>Male (MeSH)</term><term>Middle Aged (MeSH)</term><term>Multi-Ingredient Cold, Flu, and Allergy Medications (economics)</term><term>New York City (epidemiology)</term><term>Nonprescription Drugs (economics)</term><term>Pollen (adverse effects)</term><term>Young Adult (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Adolescent (MeSH)</term><term>Adulte (MeSH)</term><term>Adulte d'âge moyen (MeSH)</term><term>Allergènes (effets indésirables)</term><term>Asthme (épidémiologie)</term><term>Asthme (étiologie)</term><term>Enfant (MeSH)</term><term>Enfant d'âge préscolaire (MeSH)</term><term>Femelle (MeSH)</term><term>Humains (MeSH)</term><term>Hypersensibilité (épidémiologie)</term><term>Hypersensibilité (étiologie)</term><term>Jeune adulte (MeSH)</term><term>Mâle (MeSH)</term><term>Médicaments multi-ingrédients contre le rhume, la grippe et l'allergie (économie)</term><term>Médicaments sans ordonnance (économie)</term><term>New York (ville) (épidémiologie)</term><term>Nourrisson (MeSH)</term><term>Nouveau-né (MeSH)</term><term>Pollen (effets indésirables)</term><term>Service hospitalier d'urgences (statistiques et données numériques)</term><term>Sujet âgé (MeSH)</term><term>Sujet âgé de 80 ans ou plus (MeSH)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="adverse effects" xml:lang="en"><term>Allergens</term></keywords><keywords scheme="MESH" type="chemical" qualifier="economics" xml:lang="en"><term>Multi-Ingredient Cold, Flu, and Allergy Medications</term><term>Nonprescription Drugs</term></keywords><keywords scheme="MESH" qualifier="adverse effects" xml:lang="en"><term>Pollen</term></keywords><keywords scheme="MESH" qualifier="effets indésirables" xml:lang="fr"><term>Allergènes</term><term>Pollen</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Asthma</term><term>Hypersensitivity</term><term>New York City</term></keywords><keywords scheme="MESH" qualifier="etiology" xml:lang="en"><term>Asthma</term><term>Hypersensitivity</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Emergency Service, Hospital</term></keywords><keywords scheme="MESH" qualifier="statistiques et données numériques" xml:lang="fr"><term>Service hospitalier d'urgences</term></keywords><keywords scheme="MESH" qualifier="économie" xml:lang="fr"><term>Médicaments multi-ingrédients contre le rhume, la grippe et l'allergie</term><term>Médicaments sans ordonnance</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Asthme</term><term>Hypersensibilité</term><term>New York (ville)</term></keywords><keywords scheme="MESH" qualifier="étiologie" xml:lang="fr"><term>Asthme</term><term>Hypersensibilité</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adolescent</term><term>Adult</term><term>Aged</term><term>Aged, 80 and over</term><term>Child</term><term>Child, Preschool</term><term>Female</term><term>Humans</term><term>Infant</term><term>Infant, Newborn</term><term>Male</term><term>Middle Aged</term><term>Young Adult</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Adolescent</term><term>Adulte</term><term>Adulte d'âge moyen</term><term>Enfant</term><term>Enfant d'âge préscolaire</term><term>Femelle</term><term>Humains</term><term>Jeune adulte</term><term>Mâle</term><term>Nourrisson</term><term>Nouveau-né</term><term>Sujet âgé</term><term>Sujet âgé de 80 ans ou plus</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b></p><p>Many types of tree pollen trigger seasonal allergic illness, but their population-level impacts on allergy and asthma morbidity are not well established, likely due to the paucity of long records of daily pollen data that allow analysis of multi-day effects. Our objective in this study was therefore to determine the impacts of individual spring tree pollen types on over-the-counter allergy medication sales and asthma emergency department (ED) visits.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>Nine clinically-relevant spring tree pollen genera (elm, poplar, maple, birch, beech, ash, sycamore/London planetree, oak, and hickory) measured in Armonk, NY, were analyzed for their associations with over-the-counter allergy medication sales and daily asthma syndrome ED visits from patients' chief complaints or diagnosis codes in New York City during March 1st through June 10th, 2002-2012. Multi-day impacts of pollen on the outcomes (0-3 days and 0-7 days for the medication sales and ED visits, respectively) were estimated using a distributed lag Poisson time-series model adjusting for temporal trends, day-of-week, weather, and air pollution. For asthma syndrome ED visits, age groups were also analyzed. Year-to-year variation in the average peak dates and the 10th-to-90th percentile duration between pollen and the outcomes were also examined with Spearman's rank correlation.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>Mid-spring pollen types (maple, birch, beech, ash, oak, and sycamore/London planetree) showed the strongest significant associations with both outcomes, with cumulative rate ratios up to 2.0 per 0-to-98th percentile pollen increase (e.g., 1.9 [95% CI: 1.7, 2.1] and 1.7 [95% CI: 1.5, 1.9] for the medication sales and ED visits, respectively, for ash). Lagged associations were longer for asthma syndrome ED visits than for the medication sales. Associations were strongest in children (ages 5-17; e.g., a cumulative rate ratio of 2.6 [95% CI: 2.1, 3.1] per 0-to-98th percentile increase in ash). The average peak dates and durations of some of these mid-spring pollen types were also associated with those of the outcomes.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b></p><p>Tree pollen peaking in mid-spring exhibit substantive impacts on allergy, and asthma exacerbations, particularly in children. Given the narrow time window of these pollen peak occurrences, public health and clinical approaches to anticipate and reduce allergy/asthma exacerbation should be developed.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">26310854</PMID><DateCompleted><Year>2016</Year><Month>05</Month><Day>11</Day></DateCompleted><DateRevised><Year>2018</Year><Month>12</Month><Day>02</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1476-069X</ISSN><JournalIssue CitedMedium="Internet"><Volume>14</Volume><PubDate><Year>2015</Year><Month>Aug</Month><Day>27</Day></PubDate></JournalIssue><Title>Environmental health : a global access science source</Title><ISOAbbreviation>Environ Health</ISOAbbreviation></Journal><ArticleTitle>The associations between daily spring pollen counts, over-the-counter allergy medication sales, and asthma syndrome emergency department visits in New York City, 2002-2012.</ArticleTitle><Pagination><MedlinePgn>71</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/s12940-015-0057-0</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Many types of tree pollen trigger seasonal allergic illness, but their population-level impacts on allergy and asthma morbidity are not well established, likely due to the paucity of long records of daily pollen data that allow analysis of multi-day effects. Our objective in this study was therefore to determine the impacts of individual spring tree pollen types on over-the-counter allergy medication sales and asthma emergency department (ED) visits.</AbstractText><AbstractText Label="METHODS" NlmCategory="METHODS">Nine clinically-relevant spring tree pollen genera (elm, poplar, maple, birch, beech, ash, sycamore/London planetree, oak, and hickory) measured in Armonk, NY, were analyzed for their associations with over-the-counter allergy medication sales and daily asthma syndrome ED visits from patients' chief complaints or diagnosis codes in New York City during March 1st through June 10th, 2002-2012. Multi-day impacts of pollen on the outcomes (0-3 days and 0-7 days for the medication sales and ED visits, respectively) were estimated using a distributed lag Poisson time-series model adjusting for temporal trends, day-of-week, weather, and air pollution. For asthma syndrome ED visits, age groups were also analyzed. Year-to-year variation in the average peak dates and the 10th-to-90th percentile duration between pollen and the outcomes were also examined with Spearman's rank correlation.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">Mid-spring pollen types (maple, birch, beech, ash, oak, and sycamore/London planetree) showed the strongest significant associations with both outcomes, with cumulative rate ratios up to 2.0 per 0-to-98th percentile pollen increase (e.g., 1.9 [95% CI: 1.7, 2.1] and 1.7 [95% CI: 1.5, 1.9] for the medication sales and ED visits, respectively, for ash). Lagged associations were longer for asthma syndrome ED visits than for the medication sales. Associations were strongest in children (ages 5-17; e.g., a cumulative rate ratio of 2.6 [95% CI: 2.1, 3.1] per 0-to-98th percentile increase in ash). The average peak dates and durations of some of these mid-spring pollen types were also associated with those of the outcomes.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">Tree pollen peaking in mid-spring exhibit substantive impacts on allergy, and asthma exacerbations, particularly in children. Given the narrow time window of these pollen peak occurrences, public health and clinical approaches to anticipate and reduce allergy/asthma exacerbation should be developed.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Ito</LastName><ForeName>Kazuhiko</ForeName><Initials>K</Initials><AffiliationInfo><Affiliation>New York City Department of Health and Mental Hygiene, Bureau of Environmental Surveillance and Policy, New York, NY, 10013, USA. kito1@health.nyc.gov.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Weinberger</LastName><ForeName>Kate R</ForeName><Initials>KR</Initials><AffiliationInfo><Affiliation>Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, 10032-3727, USA. krw2114@cumc.columbia.edu.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Robinson</LastName><ForeName>Guy S</ForeName><Initials>GS</Initials><AffiliationInfo><Affiliation>Louis Calder Center, Biological Field Station, Fordham University, Armonk, New York, NY, 10504-1104, USA. grobinson@fordham.edu.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Natural Sciences, Fordham College at Lincoln Center, 113 West 60th Street, New York, NY, 10023, USA. grobinson@fordham.edu.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Sheffield</LastName><ForeName>Perry E</ForeName><Initials>PE</Initials><AffiliationInfo><Affiliation>Departments of Pediatrics and Preventive Medicine, Mount Sinai School of Medicine, 1 Gustave L. Levy Pl., Box 1512, New York, NY, 10029, USA. perry.sheffield@mssm.edu.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lall</LastName><ForeName>Ramona</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>New York City Department of Health and Mental Hygiene, Bureau of Communicable Disease, Queens, NY, 11101, USA. rlall@health.nyc.gov.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Mathes</LastName><ForeName>Robert</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>New York City Department of Health and Mental Hygiene, Bureau of Communicable Disease, Queens, NY, 11101, USA. rmathes@health.nyc.gov.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ross</LastName><ForeName>Zev</ForeName><Initials>Z</Initials><AffiliationInfo><Affiliation>ZevRoss Spatial Analysis, Ithaca, NY, 14850, USA. zev@zevross.com.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kinney</LastName><ForeName>Patrick L</ForeName><Initials>PL</Initials><AffiliationInfo><Affiliation>Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, 10032-3727, USA. plk3@cumc.columbia.edu.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Matte</LastName><ForeName>Thomas D</ForeName><Initials>TD</Initials><AffiliationInfo><Affiliation>New York City Department of Health and Mental Hygiene, Bureau of Environmental Surveillance and Policy, New York, NY, 10013, USA. tmatte@health.nyc.gov.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>K23ES024127</GrantID><Acronym>ES</Acronym><Agency>NIEHS NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>T32ES007322</GrantID><Acronym>ES</Acronym><Agency>NIEHS NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>P30 ES000260</GrantID><Acronym>ES</Acronym><Agency>NIEHS NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>T32HD049311</GrantID><Acronym>HD</Acronym><Agency>NICHD NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>P30 ES023515</GrantID><Acronym>ES</Acronym><Agency>NIEHS NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>P30-ES00260</GrantID><Acronym>ES</Acronym><Agency>NIEHS NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>T32 HD049311</GrantID><Acronym>HD</Acronym><Agency>NICHD NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>T32 ES007322</GrantID><Acronym>ES</Acronym><Agency>NIEHS NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>K23 ES024127</GrantID><Acronym>ES</Acronym><Agency>NIEHS NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>200-2009-31909-003</GrantID><Agency>PHS HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>T32 ES023770</GrantID><Acronym>ES</Acronym><Agency>NIEHS NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>P30 ES009089</GrantID><Acronym>ES</Acronym><Agency>NIEHS NIH HHS</Agency><Country>United States</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D052061">Research Support, N.I.H., Extramural</PublicationType><PublicationType UI="D013487">Research Support, U.S. Gov't, P.H.S.</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2015</Year><Month>08</Month><Day>27</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Environ Health</MedlineTA><NlmUniqueID>101147645</NlmUniqueID><ISSNLinking>1476-069X</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D000485">Allergens</NameOfSubstance></Chemical><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D057985">Multi-Ingredient Cold, Flu, and Allergy Medications</NameOfSubstance></Chemical><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D004366">Nonprescription Drugs</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000369" MajorTopicYN="N">Aged, 80 and over</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000485" MajorTopicYN="N">Allergens</DescriptorName><QualifierName UI="Q000009" MajorTopicYN="Y">adverse effects</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D001249" MajorTopicYN="N">Asthma</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName><QualifierName UI="Q000209" MajorTopicYN="N">etiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D002648" MajorTopicYN="N">Child</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D002675" MajorTopicYN="N">Child, Preschool</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D004636" MajorTopicYN="N">Emergency Service, Hospital</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006967" MajorTopicYN="N">Hypersensitivity</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName><QualifierName UI="Q000209" MajorTopicYN="N">etiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D007223" MajorTopicYN="N">Infant</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007231" MajorTopicYN="N">Infant, Newborn</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D057985" MajorTopicYN="N">Multi-Ingredient Cold, Flu, and Allergy Medications</DescriptorName><QualifierName UI="Q000191" MajorTopicYN="Y">economics</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D009519" MajorTopicYN="N">New York City</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D004366" MajorTopicYN="N">Nonprescription Drugs</DescriptorName><QualifierName UI="Q000191" 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Kinney</name><name sortKey="Lall, Ramona" sort="Lall, Ramona" uniqKey="Lall R" first="Ramona" last="Lall">Ramona Lall</name><name sortKey="Mathes, Robert" sort="Mathes, Robert" uniqKey="Mathes R" first="Robert" last="Mathes">Robert Mathes</name><name sortKey="Matte, Thomas D" sort="Matte, Thomas D" uniqKey="Matte T" first="Thomas D" last="Matte">Thomas D. Matte</name><name sortKey="Robinson, Guy S" sort="Robinson, Guy S" uniqKey="Robinson G" first="Guy S" last="Robinson">Guy S. Robinson</name><name sortKey="Robinson, Guy S" sort="Robinson, Guy S" uniqKey="Robinson G" first="Guy S" last="Robinson">Guy S. Robinson</name><name sortKey="Ross, Zev" sort="Ross, Zev" uniqKey="Ross Z" first="Zev" last="Ross">Zev Ross</name><name sortKey="Sheffield, Perry E" sort="Sheffield, Perry E" uniqKey="Sheffield P" first="Perry E" last="Sheffield">Perry E. Sheffield</name><name sortKey="Weinberger, Kate R" sort="Weinberger, Kate R" uniqKey="Weinberger K" first="Kate R" last="Weinberger">Kate R. 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