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Record W4387950342 · doi:10.2196/50114

Burden of and Trends in Urticaria Globally, Regionally, and Nationally from 1990 to 2019: Systematic Analysis

2023· article· en· W4387950342 on OpenAlexvenueno aff
Xiaoli Liu, Yuan Cao, Wenhui Wang

Bibliographic record

VenueJMIR Public Health and Surveillance · 2023
Typearticle
Languageen
FieldMedicine
TopicUrticaria and Related Conditions
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePublic healthGlobal healthEnvironmental healthIncidence (geometry)PopulationDisease burdenDemographyEpidemiologyBurden of diseasePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Urticaria presents a significant global health challenge due to its sudden onset and potential for severe allergic reactions. Past data on worldwide prevalence and incidence is inconsistent due to differing study methodologies, regional differences, and evolving diagnostic criteria. Past studies have often provided broad ranges instead of specific figures, underscoring the necessity for a cohesive global perspective to inform public health strategies. OBJECTIVE: We aimed to assess the global burden of urticaria using the 2019 Global Burden of Disease (GBD) study data and systematically analyze urticaria prevalence, incidence, and disability-adjusted life years (DALYs) at global, regional, and national levels, thereby informing more effective prevention and treatment strategies. METHODS: We analyzed the global, regional, and national burden of urticaria from 1990 to 2019 using the 2019 GBD study coordinated by the Institute for Health Metrics and Evaluation. Estimations of urticaria prevalence, incidence, and DALYs were derived using DisMod-MR 2.1, a Bayesian meta-regression tool. The Socio-demographic Index (SDI) was used to correlate development status with health outcomes. The GBD's division of the world into 21 regions and 204 countries and territories facilitated a comprehensive assessment. Age-standardized estimated annual percentage changes were generated for urticaria metrics to quantify temporal trends, with age standardization adjusting for potential confounding from age structure. RESULTS: From 1990 to 2019, the global age-standardized prevalence, incidence, and DALY rates of urticaria showed marginal changes. In 2019, 65.14 million individuals were affected, with a prevalence rate of 841.88 per 100,000 population. The DALY rate was 50.39 per 100,000 population. Compared to 1990, the global age-standardized prevalence, incidence, and DALY rates saw increases of 2.92, 4.84, and 0.31 per 100,000 population, respectively. Women persistently had higher rates than men. At a regional level in 2019, low-middle SDI regions exhibited the highest age-standardized metrics, whereas high SDI regions reported the lowest. Central Europe showed the highest rates, contrasting with Western Europe's lowest rates. Nationally, urticaria prevalence in 2019 varied dramatically, from a low of 27.1 per 100,000 population in Portugal to a high of 92.0 per 100,000 population in Nepal. India reported the most DALYs at 749,495.9, followed by China, Pakistan, and the United States. Agewise data showed higher rates in younger age groups, which diminished with age and then experienced a slight resurgence in the oldest populations. This pattern was pronounced in women and younger populations, with the largest rises seen in those aged less than 40 years and the smallest in those aged more than 70 years. CONCLUSIONS: Urticaria remains a significant global health issue, with considerable variation across regions, countries, and territories. The increased burden among women, the rising burden in younger populations, and the regional differences in disease burden call for tailored interventions and policies to tackle this emerging public health issue.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.318
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations30
Published2023
Admission routes1
Has abstractyes

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