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Asthma as an outcome: Exploring multiple definitions of asthma across birth cohorts in the Environmental influences on Child Health Outcomes Children's Respiratory and Environmental Workgroup

2019; Elsevier BV; Volume: 144; Issue: 3 Linguagem: Inglês

10.1016/j.jaci.2019.05.025

1097-6825

Cynthia M. Visness, Tebeb Gebretsadik, Daniel J. Jackson, Jocelyn Biagini Myers, Suzanne Havstad, Robert F. Lemanske, Tina V. Hartert, Gurjit K. Khurana Hershey, Edward M. Zoratti, Lisa J. Martin, Rachel L. Miller, Diane R. Gold, Anne Wright, Debra A. Stern, James E. Gern, Christine Cole Johnson,

Air Quality and Health Impacts

Every birth cohort study investigating risk factors for the development of asthma relies on specific criteria for classifying children as asthmatic or not, but these criteria vary widely across studies because there is no gold standard set of diagnostic criteria or an objective test for asthma. Researchers make independent yet informed decisions about the data elements they need and are able to collect to achieve their research objectives given available resources. Cohorts with only questionnaire data available, such as the International Study of Asthma and Allergies in Childhood, rely on a parent-reported physician's diagnosis of asthma.1Bousquet J. Anto J. Sunyer J. Nieuwenhuijsen M. Vrijheid M. Keil T. et al.Pooling birth cohorts in allergy and asthma: European Union-funded initiatives—a MeDALL, CHICOS, ENRIECO, and GA(2)LEN joint paper.Int Arch Allergy Immunol. 2013; 161: 1-10Crossref PubMed Scopus (51) Google Scholar Some studies have used lung function and airway hyperresponsiveness in their asthma definition criteria, whereas others have used reports of wheezing symptoms, asthma medication use, and health care data. Often, studies use a combination of the above to identify children with asthma. A comprehensive review of birth cohort asthma definitions found 60 different asthma definitions among 122 studies.2Van Wonderen K.E. Van Der Mark L.B. Mohrs J. Bindels P.J. Van Aalderen W.M. Ter Riet G. Different definitions in childhood asthma: how dependable is the dependent variable?.Eur Respir J. 2010; 36: 48-56Crossref PubMed Scopus (73) Google Scholar In addition to the varying prevalence of asthma because of the definition used, identification of risk factors for asthma can also vary based on how the outcome is defined and the age at which it is applied, potentially leading to inconsistent findings across birth cohorts. The Children's Respiratory and Environment Workgroup (CREW) is a consortium of 12 US birth cohort studies3Gern JE, Jackson DJ, Lemanske RF Jr, Seroogy CM, Tachinardi U, Craven M, et al. The Children's Respiratory and Environmental Workgroup (CREW) Birth Cohort Consortium: design, methods, and study population. Respiratory Research 2019;20:115.Google Scholar that are part of the larger Environmental influences on Child Health Outcomes (ECHO) program of the National Institutes of Health (http://echochildren.org/). The combined study participants of the CREW consortium represent a diverse national sample of children recruited over the past 30 or more years into cohort studies specifically designed to study the role of early-life environmental risk factors on asthma development. Some of the cohorts recruited participants from the general population, whereas others selected participants based on parental histories of asthma or allergy or parental atopy. One of the goals of CREW is to combine and harmonize extant data across all of the cohorts. Understanding the extent of heterogeneity in asthma definitions is an essential early step in the process toward building a harmonized definition of asthma. We used data from 9 of the CREW cohorts to examine how the prevalence of asthma in middle childhood (age 5-10 years) varies by applying different outcome definitions, where possible. After examining all of the definitions used across all 9 cohorts (see Table E1 in this article's Online Repository at www.jacionline.org), 4 definitions of asthma were chosen for comparison across multiple cohorts:•Definition 1: Positive response to “Has a doctor or other health professional ever told you your child has asthma?” at any time up to the assessment age;•Definition 2: Parent-reported physician's diagnosis of asthma as above plus a parental report of 1 or more wheezing episodes in the past 12 months;•Definition 3: Parent-reported physician's diagnosis of asthma as above or report of asthma medication use (both controllers and rescue albuterol) in the past year; and•Definition 4: FEV1 reversibility of 12% or greater or bronchial hyperresponsiveness (methacholine PC20 ≤ 4 mg/mL). A single analyst (T.G.) pooled the data and applied the 4 asthma definitions to each cohort. The cohort analysis populations were restricted to those children who had data for all definitions possible for that cohort to ensure that observed differences were due to changes in definition and not to changing population sizes. If a cohort did not collect a given data element at all (eg, clinical pulmonary function measurements), that definition was not used for that cohort. Descriptive statistics were calculated as medians with interquartile ranges (25th to 75th) for continuous variables and frequencies and percentages for categorical variables. We used a Venn diagram to graphically display the overlap in children defined as asthmatic by using the different asthma definitions. All analyses were performed with R software, version 3.4.0 (http://www.R-project.org). Demographic characteristics of the cohorts are shown in Table I. Each cohort sent data for a particular time point, usually that for which a primary determination of asthma was previously done. Ages ranged from about 5 to 7 years, with the exception of the Wayne County Health Environment Allergy and Asthma Longitudinal Study, which provided data from a 10-year assessment.Table IDemographic characteristics of participating CREW birth cohortsCCCEH (n = 727)TCRS (n = 1246)IIS (n = 482)COAST (n = 259)URECA (n = 485)CCAAPS (n = 617)EHAAS (n = 438)WHEALS (n = 1258)CAS (n = 835)Race/ethnicity Hispanic65%26%26%3%20%1%6%7%0% Non-Hispanic white0%59%58%87%1%66%80%26%95% Non-Hispanic black35%2%2%4%72%16%7%63%2% Other/mixed0%13%14%6%7%16%8%5%4% SexMale48%49%48%57%51%55%54%50%49%Female52%51%52%43%49%45%46%50%51% Mean (SD) age (y) at asthma assessment7.0 (6.0-9.0)6.2 (5.8-6.5)5.1 (5.0-5.2)6.0 (6.0-6.0)7.0 (6.9-7.2)6.8 (6.7-7.0)7.0 (7.0-7.0)10.2 (9.5-10.8)6.7 (6.6-6.8) Type of eligibility∗Detailed eligibility criteria are shown in Table E1 in this article's Online Repository.GeneralGeneralGeneralFamily historyFamily historyFamily historyFamily historyGeneralGeneral Percentage with asthma in original cohort publication31%10%12%28%29%16%8%13%10%CAS, Childhood Allergy/Asthma Study; CCAAPS, Cincinnati Childhood Allergy and Air Pollution Study; CCCEH, Columbia Center for Children's Environmental Health; COAST, Childhood Origins of Asthma Study; EHAAS, Epidemiology of Home Allergens and Asthma Study; IIS, the Infant Immune Study; TCRS, Tucson Children's Respiratory Study; URECA, Urban Environment and Childhood Asthma; WHEALS, Wayne County Health Environment Allergy and Asthma Longitudinal Study.∗ Detailed eligibility criteria are shown in Table E1 in this article's Online Repository. Open table in a new tab CAS, Childhood Allergy/Asthma Study; CCAAPS, Cincinnati Childhood Allergy and Air Pollution Study; CCCEH, Columbia Center for Children's Environmental Health; COAST, Childhood Origins of Asthma Study; EHAAS, Epidemiology of Home Allergens and Asthma Study; IIS, the Infant Immune Study; TCRS, Tucson Children's Respiratory Study; URECA, Urban Environment and Childhood Asthma; WHEALS, Wayne County Health Environment Allergy and Asthma Longitudinal Study. Only 2 definitions could be applied to all 9 cohorts: physician's diagnosis (Definition 1) and physician's diagnosis plus wheeze (Definition 2). As expected, prevalence based on Definition 2 (“current” vs “ever” asthma) was lower across all the cohorts (range, 2-13 percentage points). A physician's diagnosis or asthma medication use (Definition 3) was applied to 6 of the 9 cohorts and always resulted in greater prevalence than Definition 1 (range, 1-6 percentage points). The definition based on tests of reversibility or hyperresponsiveness (Definition 4) could only be applied to 3 cohorts. Prevalence based on Definition 4 was the lowest of the 4 definitions for 1 cohort and the highest for 2 of the cohorts (Fig 1). Thus, in addition to varying in inclusivity, the different definitions identified distinct subsets of children as having asthma (see Fig E1 in this article's Online Repository at www.jacionline.org). Without an objective test or even a gold standard set of clinical diagnostic criteria for asthma, research studies are not consistent in operationalizing their definition of disease. In our application of 4 different asthma definitions to data from 9 of the CREW birth cohorts, we found substantial differences in asthma prevalence. Furthermore, the definitions identified distinct groups of children, such that certain definitions miss children that others pick up. In addition, because of the availability of data, only 2 of 4 of the definitions could be applied post hoc to all studies, making harmonization of outcome definitions challenging. As shown in the van Wonderen review article,2Van Wonderen K.E. Van Der Mark L.B. Mohrs J. Bindels P.J. Van Aalderen W.M. Ter Riet G. Different definitions in childhood asthma: how dependable is the dependent variable?.Eur Respir J. 2010; 36: 48-56Crossref PubMed Scopus (73) Google Scholar researchers often choose combinations of variables to determine asthma in their study populations because they strive to identify all asthmatic patients while simultaneously excluding the nonasthmatic subjects. In particular, the Urban Environment and Childhood Asthma cohort used a complex set of criteria to identify the children with asthma in their population at 7 years of age.4O'Connor G.T. Lynch S.V. Bloomberg G.R. Kattan M. Wood R.A. Gergen P.J. et al.Early-life home environment and risk of asthma among inner-city children.J Allergy Clin Immunol. 2018; 141: 1468-1475Abstract Full Text Full Text PDF PubMed Scopus (36) Google Scholar An approach like this (eg, creating standard “building blocks” that could be assembled depending on the research question) might hold promise but is next to impossible to apply post hoc to data sets from other studies that did not ask the same questions or include the same procedures. This work highlights the need to develop consensus guidelines for asthma definitions and to promote the use of standardized data collection elements to ensure the ability to compare studies and achieve reproducibility and rigor. CREW would like to acknowledge the following institutions, investigators, and staff whose efforts contributed to the work presented in this article (principal investigators are indicated by an asterisk): Columbia Center for Children's Environmental Health (CCCEH): Rachel Miller,* Howard Andrews, Julie Herbstman, Lori Hoepner, Frederica Perera, Matthew Perzanowski, Xinhua Liu, Judyth Ramirez, Janelle Rivera, Deliang Tang, Kylie Wheelock, Jaqueline Jezioro Tucson Children's Respiratory Study (TCRS): Anne L. Wright,* Fernando D. Martinez,* Wayne Morgan, Debra A. Stern, Dean Billheimer, Brian Hallmark, Paloma Beamer, Nathan Lothrop, Lydia De La Ossa, Silvia Lopez, Marilyn Halonen, Amber Spangenberg, David Spies Infant Immune Study (IIS): Anne L. Wright,* Fernando D. Martinez,* Wayne Morgan, Debra A. Stern, Dean Billheimer, Brian Hallmark, Paloma Beamer, Nathan Lothrop, Heidi Erickson, Marilyn Halonen, Amber Spangenberg, David Spies Childhood Origins of Asthma Study (COAST): Robert F. Lemanske, Jr,* Daniel J. Jackson,* James E. Gern, Carole Ober, Ronald E. Gangnon, Michael D. Evans, Victoria Rajamanickam, Christopher Tisler, Lisa Salazar, Susan Doyle, Yury Bochkov, Rebecca Brockman-Schneider, Rose Vrtis, Kristine Grindle, Tressa Pappas, Elizabeth Anderson, Kathy Roberg, Kirsten Carlson-Dakes, Mark DeVries, Douglas DaSilva, Ronald Sorkness, Lance Mikus, Julia Bach Urban Environment and Childhood Asthma Study (URECA): Johns Hopkins University, Baltimore, Maryland—R. Wood,* E. Matsui, H. Lederman, F. Witter, S. Leimenstoll, D. Scott, M. Cootauco, P. Jones; Boston University School of Medicine, Boston, Massachusetts—G. O'Connor,* W. Cruikshank, M. Sandel, A. Lee-Parritz, C. Jordan, E. Gjerasi, P. Price-Johnson, L. Gagalis, L. Wang, N. Gonzalez, M. Tuzova; Harvard Medical School, Boston, Massachusetts—D. Gold, R. Wright; Columbia University, New York, NY—M. Kattan,* C. Lamm, N. Whitney, P. Yaniv, M. Pierce, J. Jezioro; Mount Sinai School of Medicine, New York, NY—H. Sampson, R. Sperling, N. Rivers; Washington University School of Medicine, St Louis, Missouri: G. Bloomberg,* L. Bacharier,* Y. Sadovsky, E. Tesson, C. Koerkenmeier, R. Sharp, K. Ray, J. Durrange, I. Bauer, A. Freie, V. Morgan; Statistical and Clinical Coordinating Center, Rho, Chapel Hill, NC—C. Visness,* P. Zook, M. Yaeger, J. Martin, A. Calatroni, K. Jaffee, W. Taylor, R. Budrevich, H. Mitchell; Scientific Coordination and Administrative Center, University of Wisconsin, Madison, Wisconsin—W. Busse,* J. Gern,* P. Heinritz, C. Sorkness, K. Hernandez, Y. Bochkov, K. Grindle, A. Dresen, T. Pappas, M. Renneberg, B. Stoffel; National Institute of Allergy and Infectious Diseases, Bethesda, Maryland—P. Gergen, A. Togias, E. Smartt, K. Thompson Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS): Gurjit K. Khurana Hershey,* Patrick H. Ryan,* Jocelyn M. Biagini Myers,* Grace K. LeMasters,* Kristi Curtsinger, Liza Murrison,* Lisa J. Martin, Jeffrey W. Burkle, Christopher Wolfe, Zachary Flege, David Morgan, Kristina Keidel, Krista Tensing, Taylor Groeschen The Epidemiology of Home Allergens and Asthma Study (EHAAS): Diane R. Gold, Soma Datta, Sharon O'Toole, Conner Fleurat, Leanna Farnham Wayne County Health, Environment, Allergy and Asthma Longitudinal Study (WHEALS): Henry Ford Health System, Detroit, Michigan—C. C. Johnson,* G. Wegienka, S. Havstad, E. Zoratti, A. Cassidy-Bushrow, A. Levin, H. Kim, K. Woodcroft, A. Sitarik, C. Joseph, L. K. Williams, C. Barone, K. Bobbitt, S. Zhang, J. Campbell, K. Bourgeois, M. Aubuchon, J. Ezell, K. Jones; Augusta University, Augusta, Georgia—D. Ownby Childhood Allergy Study (CAS): D. Ownby,* C. C. Johnson, C. Joseph, E. Zoratti, G. Wegienka, S. Havstad, K. Woodcroft, E. Peterson, S. Hensley Alford, J. McCullough, C. Strauchman Boyer, S. Blocki, G. Birg, N. Akkerman, K. Wells, S. Zhang, C. Nicholas, A. Jones, G. Stouffer Table E1Definitions of asthma (age 5-10 years) for each CREW birth cohortCohortCohort nameInstitutionCityOriginal cohort asthma definitionKey eligibility criteriaCCCEHE1Whyatt R.M. Perzanowski M.S. Just A.C. Rundle A.G. Donohue K.M. Calafat A.M. et al.Asthma in inner-city children at 5-11 years of age and prenatal exposure to phthalates: the Columbia center for children's environmental health cohort.Environ Health Perspect. 2014; 122: 1141-1146Crossref PubMed Scopus (96) Google ScholarColumbia Center for Children's Environmental HealthColumbia University Medical CenterNew YorkParent-reported physician's diagnosis of asthma or report of wheeze or use of asthma medications in past yearWomen 18-35 years old who self-identified as African American or Dominican and had resided in northern Manhattan or the South Bronx for at least 1 year before pregnancy were included.Women were excluded from enrollment in the cohort if they reported active smoking; used other tobacco products or illicit drugs; had diabetes, hypertension, or known HIV; or had their first prenatal visit after 20 weeks of gestation.TCRSE2Halonen M. Stern D.A. Wright A.L. Taussig L.M. Martinez F.D. Alternaria as a major allergen for asthma in children raised in a desert environment.Am J Respir Crit Care Med. 1997; 155: 1356-1361Crossref PubMed Scopus (371) Google ScholarTucson Children's Respiratory StudyUniversity of ArizonaTucsonPhysician-diagnosed asthma with report of asthma attacks/episodes or wheezing in past yearNewborns whose parents were patients of Group Health Medical Associates in Tucson, Arizona, were included.IISE3Rothers J. Halonen M. Stern D.A. Lohman I.C. Mobley S. Spangenberg A. et al.Adaptive cytokine production in early life differentially predicts total IgE levels and asthma through age 5 years.J Allergy Clin Immunol. 2011; 128: 397-402.e2Abstract Full Text Full Text PDF PubMed Scopus (43) Google ScholarThe Infant Immune StudyUniversity of ArizonaTucsonPhysician-diagnosed asthma with report of asthma attacks/episodes, wheezing, or asthma medication use in past yearParticipants were healthy children born to women who planned to obtain care for their newborns from collaborating pediatricians.COASTE4Jackson D.J. Gangnon R.E. Evans M.D. Roberg K.A. Anderson E.L. Pappas T.E. et al.Wheezing rhinovirus illnesses in early life predict asthma development in high-risk children.Am J Respir Crit Care Med. 2008; 178: 667-672Crossref PubMed Scopus (986) Google ScholarChildhood Origins of Asthma StudyUniversity of WisconsinMadisonPhysician-diagnosed asthma, or use of albuterol for asthma attacks/episodes or wheezing, or asthma controller medication use or having a step-up plan or use of prednisone in past yearAt least 1 parent was required to have respiratory allergies (defined as ≥1 positive aeroallergen skin test response) and/or a history of physician-diagnosed asthma.Delivery occurred at ≥34 weeks of gestation.URECAE5O'Connor G.T. Lynch S.V. Bloomberg G.R. Kattan M. Wood R.A. Gergen P.J. et al.Early-life home environment and risk of asthma among inner-city children.J Allergy Clin Immunol. 2018; 141: 1468-1475Abstract Full Text Full Text PDF PubMed Scopus (123) Google ScholarUrban Environment and Childhood AsthmaJohn's Hopkins University School of MedicineBoston University School of MedicineColumbia University Medical CenterSt Louis Children's HospitalBaltimoreBostonNew YorkSt Louis(1) Parent-reported physician's diagnosis of asthma between age 4 and 7 years combined with asthma symptoms or use of asthma controller medication for 6 of the past 12 months; (2) methacholine PC20 ≤4 mg/mL or albuterol reversibility of FEV1 ≥ 10% combined with asthma symptoms or use of asthma controller medication for 6 of the past 12 months; or (3) report in the past 12 months of ≥2 wheezing episodes, ≥2 doctor's office visits for asthma/wheeze, ≥1 hospitalization for asthma/wheeze, or use of controller medications for 6 of the past 12 months.At least 1 parent was required to have had a previous physician's diagnosis of asthma, hay fever, or eczema (captured by maternal report).Delivery occurred at ≥34 weeks of gestation.Residence was in a census tract with ≥20% poverty at the time of birth.CCAAPSE6LeMasters G. Levin L. Bernstein D.I. Lockey S.D.t. Lockey J.E. Burkle J. et al.Secondhand smoke and traffic exhaust confer opposing risks for asthma in normal and overweight children.Obesity. 2015; 23: 32-36Crossref Scopus (11) Google ScholarCincinnati Childhood Allergy and Air Pollution StudyCincinnati Children's HospitalCincinnatiPhysician-diagnosed asthma with evidence of bronchoreactivity or reversibilityDelivery occurred at ≥35 weeks' gestation.At least 1 parent had to have current allergy symptoms and a positive SPT response to at least 1 aeroallergen.Subjects lived less than 400 meters or greater than 1500 meters from a major highway.EHAASE7Gold D.R. Burge H.A. Carey V. Milton D.K. Platts-Mills T. Weiss S.T. Predictors of repeated wheeze in the first year of life: the relative roles of cockroach, birth weight, acute lower respiratory illness, and maternal smoking.Am J Respir Crit Care Med. 1999; 160: 227-236Crossref PubMed Scopus (266) Google Scholar, E8Raby B.A. Celedon J.C. Litonjua A.A. Phipatanakul W. Sredl D. Oken E. et al.Low-normal gestational age as a predictor of asthma at 6 years of age.Pediatrics. 2004; 114: e327-e332Crossref PubMed Scopus (55) Google ScholarEpidemiology of Home Allergens and Asthma StudyHarvard UniversityCambridgePhysician-diagnosed asthma with report of asthma attacks/episodes or wheezing in past yearChildren with a history of asthma or allergy in at least 1 parent were included.WHEALSE9Havstad S. Johnson C.C. Kim H. Levin A.M. Zoratti E.M. Joseph C.L. et al.Atopic phenotypes identified with latent class analyses at age 2 years.J Allergy Clin Immunol. 2014; 134: 722-727.e2Abstract Full Text Full Text PDF PubMed Scopus (72) Google ScholarWayne County Health Environment Allergy and Asthma Longitudinal StudyHenry Ford Health SystemDetroitParental report of physician-diagnosed asthmaWomen were eligible for inclusion in the study if they were in their second or third trimester of pregnancy, were between 21 and 49 years of age, and lived in a predefined cluster of ZIP codes in Detroit and its surrounding suburbs and attended one of 5 obstetric clinics.CASE10Carter P.M. Peterson E.L. Ownby D.R. Zoratti E.M. Johnson C.C. Relationship of house-dust mite allergen exposure in children's bedrooms in infancy to bronchial hyperresponsiveness and asthma diagnosis by age 6 to 7.Ann Allergy Asthma Immunol. 2003; 90: 41-44Abstract Full Text PDF PubMed Scopus (39) Google Scholar, E11Johnson C.C. Ownby D.R. Havstad S.L. Peterson E.L. Family history, dust mite exposure in early childhood, and risk for pediatric atopy and asthma.J Allergy Clin Immunol. 2004; 114: 105-110Abstract Full Text Full Text PDF PubMed Scopus (81) Google ScholarChildhood Allergy/Asthma StudyHenry Ford Health SystemDetroitParental report of physician-diagnosed asthmaWomen 18 years and older having prenatal visits in a geographically circumscribed suburban Detroit health maintenance organization were included. Open table in a new tab