Evidence map›Paper›PMID 41029276›Full record

ArticleBMC public health2025

Obesity as the predominant contributor to asthma burden: insights from GBD and NHANES analyses.

Wenxin Zheng, Xiaoxiao Fan, Jian Guan, Xiaozhen Zhang, Xinyi Li, Shuang Liu, Xiaolin Wu

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Article
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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

7 authors.

Wenxin Zheng *Basic Medical College, Jiamusi University, Jiamusi, 154007, China.
Xiaoxiao Fan *Basic Medical College, Jiamusi University, Jiamusi, 154007, China.
Jian GuanDepartment of Otolaryngology Head and Neck Surgery & Otolaryngology Institute of Shanghai Jiao Tong University, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China.
Xiaozhen ZhangHospital Infection Control Office, Shanghai Sixth People's Hospital, Shanghai, 200233, China.
Xinyi LiDepartment of Otolaryngology Head and Neck Surgery & Otolaryngology Institute of Shanghai Jiao Tong University, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China. lixinyilixinyi123@163.com.
Shuang LiuBasic Medical College, Jiamusi University, Jiamusi, 154007, China. lius@jmsu.edu.cn.
Xiaolin WuCentral Laboratory, Shanghai Eighth People's Hospital (Xuhui Branch of Shanghai sixth People's Hospital), Shanghai, 200235, China. wuxiaolin999@hotmail.com.

Funding

Cultivation project of Jiamusi University JMSUGPZR2211Shanghai "Rising Stars of Medical Talents" Youth Development Program SHWSRS (2025)_071Shanghai Sixth People's Hospital ynts202103, ZY (2021-2023)-0205 -04Shanghai Sixth People's Hospital Clinical Medical Technical Backbone Team Cultivation Project 20250206
6 · The paper itself

Abstract

objectiveThis study describes the global asthma burden trends from 1990 to 2021 and identifies key risk factors contributing to changes in asthma burden, focusing on the impact of obesity on asthma burden.

methodsWe extracted asthma incidence, mortality, and Disability-Adjusted Life Years (DALYs) from the Global Burden of Disease (GBD) database (1990-2021), stratifying by age, sex and Socio-demographic Index (SDI). Temporal trends were evaluated using Joinpoint regression. Decomposition analysis quantified contributions of population growth, aging, and age-specific rates to DALY changes. Frontier analysis evaluated SDI regions' effectiveness in reducing asthma burden. To evaluate the impact of obesity, we further analyzed risk-attributable DALYs and, using National Health and Nutrition Examination Survey (NHANES) data (2021-2023), performed multivariable logistic regression examining associations between body-mass index (BMI) and asthma outcomes.

resultsAlthough age-standardized incidence and mortality rates declined, asthma remained prevalent in 2021 with an estimated 37 million new cases and 21.4 million DALYs, disproportionately affecting children (0-14 years) and older adults (55-74 years). Decomposition analysis attributed most DALY increases to demographic changes, particularly population growth and aging. Frontier analysis showed that while high-SDI regions achieved notable reductions in burden, rising obesity rates expanded the at-risk population even in these areas. High BMI emerged as the leading global risk factor for asthma-related DALYs-ranking first in high-SDI regions and, since the late 2010s, in low-SDI regions as well. NHANES analyses confirmed that individuals with asthma exhibited significantly higher BMI (Non- Asthma: 29.4 ± 7.32, Asthma: 31.2 ± 8.48, P < 0.001) Adjusted regression demonstrated that obesity independently predicted asthma onset and progression across all age groups (BMI Adjusted Odds Ratio (aOR): 1.41; 95% confidence interval (CI): 1.17-1.68.)

conclusionDespite declines in standardized rates, asthma continues to impose a heavy global burden, concentrated in vulnerable age groups, especially among the young and elderly. Obesity has emerged as the foremost modifiable risk factor worldwide. Tailored public health strategies focusing on weight management are urgently needed to curb asthma incidence and severity.

Indexed as

AsthmaCost of IllnessGlobal Burden of DiseaseObesityAdolescentAdultAgedChildChild, PreschoolDisability-Adjusted Life YearsFemaleGlobal HealthHumansIncidenceInfantInfant, NewbornAsthma burdenGlobal burden of disease (GBD)National health and nutrition examination survey (NHANES)Obesity

Identifiers

PMID41029276
PMCPMC12486712

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LicenceCC BY-NC-ND
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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.