Evidence map›Paper›PMID 38104949›Full record

ArticleThe Journal of allergy and clinical immunology2024

Trajectory analysis of rhinitis in a birth cohort from lower-income New York City neighborhoods.

Nina M Flores, Stephanie Lovinsky-Desir, Adnan Divjan, Lori A Hoepner, Jungang Zou, Rachel L Miller, Julie B Herbstman, Frederica P Perera, Matthew S Perzanowski, Qixuan Chen

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of allergy and clinical immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 25% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Observational
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

Nina M FloresDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY. Electronic address: nf2497@cumc.columbia.edu.
Stephanie Lovinsky-DesirDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY; Division of Pulmonary Medicine, Department of Pediatrics, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY.
Adnan DivjanDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY.
Lori A HoepnerData Coordinating Center, Columbia University, New York, NY.
Jungang ZouDepartment of Biostatistics, Mailman School of Public Health, New York, NY.
Rachel L MillerDivision of Clinical Immunology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY.
Julie B HerbstmanDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY.
Frederica P PereraDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY.
Matthew S PerzanowskiDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY.
Qixuan ChenDepartment of Biostatistics, Mailman School of Public Health, New York, NY.
Columbia University · USColumbia University Irving Medical Center · USIcahn School of Medicine at Mount Sinai · USThe Coordinating Center · US

Funding

True Metal fac coreP30ES009089 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MATTHEW S PERZANOWSKI · 1998 to 2026
$44.7M
HEALTH EFFECTS OF PAH &ETS IN MINORITY WOMEN &NEWBORNSR01ES008977 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PERERA, FREDERICA P · 1997 to 2011
$12.9M
Supplemental Training in Making Data FAIR and AI/ML ReadyT32ES007322 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Pam R Factor-Litvak, Allison Kupsco · 2000 to 2026
$12.1M
The Columbia Center for Children's Environmental HealthP01ES009600 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI ANDREWS, HOWARD F. · 1999 to 2014
$11.2M
Windows of Susceptibility to PAH/DEP Exposure and AsthmaP50ES015905 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PERERA, FREDERICA P · 2007 to 2011
$10.3M
Urban Diesel Exposure and Inner City AsthmaR01ES013163 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MILLER, RACHEL L · 2005 to 2016
$6.5M
Environmental bisphenol exposure, infant brain and behavior: Human and animal modelsR01ES030950 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI VEENSTRA-VANDERWEELE, JEREMY · 2020 to 2023
$2.6M
Prenatal Exposure to Environmental Tobacco Smoke, COVID-19- Related Psychosocial Stress, and Neurodevelopment.K23ES026239 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MARGOLIS, AMY · 2016 to 2021
$767k
Bayesian exposure-response analysis for immunoassays data with measurement errorsR21ES029668 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI CHEN, QIXUAN · 2019 to 2020
$417k
NIEHS NIH HHS K23 ES026239NIEHS NIH HHS P01 ES009600NIEHS NIH HHS P30 ES009089NIEHS NIH HHS P50 ES015905NIEHS NIH HHS R01 ES008977NIEHS NIH HHS R01 ES013163NIEHS NIH HHS R01 ES030950NIEHS NIH HHS R21 ES029668NIEHS NIH HHS T32 ES007322
6 · The paper itself

Abstract

backgroundRhinitis is a prevalent, chronic nasal condition associated with asthma. However, its developmental trajectories remain poorly characterized.

objectiveWe sought to describe the course of rhinitis from infancy to adolescence and the association between identified phenotypes, asthma-related symptoms, and physician-diagnosed asthma.

methodsWe collected rhinitis data from questionnaires repeated across 22 time points among 688 children from infancy to age 11 years and used latent class mixed modeling (LCMM) to identify phenotypes. Once children were between ages 5 and 12, a study physician determined asthma diagnosis. We collected information on the following asthma symptoms: any wheeze, exercise-induced wheeze, nighttime coughing, and emergency department visits. For each, we used LCMM to identify symptom phenotypes. Using logistic regression, we described the association between rhinitis phenotype and asthma diagnosis and each symptom overall and stratified by atopic predisposition and sex.

resultsLCMM identified 5 rhinitis trajectory groups: never/infrequent; transient; late onset, infrequent; late onset, frequent; and persistent. LCMM identified 2 trajectories for each symptom, classified as frequent and never/infrequent. Participants with persistent and late onset, frequent phenotypes were more likely to be diagnosed with asthma and to have the frequent phenotype for all symptoms (P < .01). We identified interaction between seroatopy and rhinitis phenotype for physician-diagnosed asthma (P = .04) and exercise-induced wheeze (P = .08). Severe seroatopy was more common among children with late onset, frequent and persistent rhinitis, with nearly 25% of these 2 groups exhibiting sensitivity to 4 or 5 of the 5 allergens tested.

conclusionsIn this prospective, population-based birth cohort, persistent and late onset, frequent rhinitis phenotypes were associated with increased risk of asthma diagnosis and symptoms during adolescence.

Indexed as

AsthmaRhinitisBirth CohortChildChild, PreschoolFemaleHumansInfantMaleNew York CityPhenotypePovertyResidence CharacteristicsSurveys and QuestionnairesasthmaRhinitisseroatopy

Identifiers

PMID38104949
PMCPMC11180217
OpenAlexW4389805898

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.