Evidence map›Paper›PMID 42051999›Full record

ArticleFrontiers in public health2026

Associated factors, nonlinear risk patterns and effect heterogeneity of severe injuries in recreational skiers and snowboarders.

Xiaoyu Ling, Lijun Long, Dongting Jiang, Xiaoyu Han, Xinping Song, Shuang Qin, Guole Jiang

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

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No citing paper in PubMed yet.

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.

Xiaoyu Ling *School of Physical Education, Southwest University, Chongqing, China.
Lijun Long *Sports Coaching College, Beijing Sport University, Beijing, China.
Dongting JiangSchool of Athletic Performance, Shanghai University of Sport, Shanghai, China.
Xiaoyu HanCollege of Nursing, Zhangjiakou University, Zhangjiakou City, China.
Xinping SongBasic Education College, National University of Defense Technology, Changsha, China.
Shuang QinSchool of Acupuncture-Moxibustion, Tuina and Rehabilitation, Hunan University of Chinese Medicine, Changsha, China.
Guole JiangBasic Education College, National University of Defense Technology, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Severe injuries in recreational alpine skiing and snowboarding impose disproportionate clinical and societal burden. Evidence on modifiable countermeasures beyond helmets remains fragmented and may vary across risk profiles and exposure conditions. This study aimed to identify factors associated with severe injuries among recreational skiers and snowboarders, and to examine nonlinear dose-response relationships and effect modification by preventive practices. Methods: We conducted a retrospective cross-sectional injury-severity study of injured adult skiers and snowboarders treated at resort medical clinics and emergency departments at two ski resorts in Zhangjiakou, China, across three winter seasons from 2021 to 2024. Severe injury was defined as an injury severity score (ISS) above 15. We modeled severe injury conditional on injury using Firth-penalized logistic regression. Restricted cubic splines were applied for age, body mass index, temperature, and snow depth to assess nonlinear associations. Prespecified interaction blocks were tested using joint Wald tests with false discovery rate control, and scenario-standardized impact metrics were estimated with bootstrap uncertainty. Results: Among 2,369 injured participants, 339 (14.3%) sustained severe injuries. In fully adjusted models, knee protector use (OR = 0.57, Conclusion: Severe outcomes among injured snow-sport participants reflect interacting exposure intensity, environment, and modifiable practices. Findings support risk-stratified prevention and condition-aware resort safety operations.

Indexed as

Athletic InjuriesSkiingAdultChinaCross-Sectional StudiesFemaleHumansInjury Severity ScoreMaleMiddle AgedRetrospective StudiesRisk FactorsYoung Adultinjury severityprotective equipmentrisk-taking behaviorsnow sportswarm-up

Identifiers

PMID42051999
PMCPMC13111118

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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.