Evidence map›Paper›PMID 32524174›Full record

ArticleOsteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA2020

Traumatic fractures in China from 2012 to 2014: a National Survey of 512,187 individuals.

H Lv, W Chen, T Zhang, Z Hou, G Yang, Y Zhu, H Wang, B Yin, J Guo, L Liu and 8 more

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Article in Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 6% 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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

  1. Efficacy of Platelet-Rich Plasma in the Treatment of Fractures: A Meta-Analysis.Computational and mathematical methods in medicine · 2022
    Pooled it
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  9. Application of collagen in bone regeneration.Journal of orthopaedic translation · 2025
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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

18 authors at 3 institutions in 1 country.

H LvDepartment of Orthopedic Surgery, the Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang, 050051, China.
W ChenDepartment of Orthopedic Surgery, the Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang, 050051, China.
T ZhangDepartment of Orthopedic Surgery, the Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang, 050051, China.
Z HouDepartment of Orthopedic Surgery, the Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang, 050051, China.
G YangDepartment of Orthopedic Surgery, the Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang, 050051, China.
Y ZhuDepartment of Orthopedic Surgery, the Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang, 050051, China.
H WangDepartment of Orthopedic Surgery, the Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang, 050051, China.
B YinDepartment of Orthopedic Surgery, the Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang, 050051, China.
J GuoDepartment of Orthopedic Surgery, the Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang, 050051, China.
L LiuDepartment of Orthopedic Surgery, the Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang, 050051, China.
P HuDepartment of Orthopedic Surgery, the Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang, 050051, China.
S LiuDepartment of Orthopedic Surgery, the Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang, 050051, China.
B LiuDepartment of Orthopedic Surgery, the Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang, 050051, China.
J SunDepartment of Orthopedic Surgery, the Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang, 050051, China.
S LiDepartment of Orthopedic Surgery, the Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang, 050051, China.
X ZhangDepartment of Epidemiology and Statistics, Hebei Medical University, Shijiazhuang, China.
Y LiFuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, Shenzhen, 518057, China.
Y ZhangDepartment of Orthopedic Surgery, the Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang, 050051, China. dryzzhang@126.com.
Hebei Medical University · CNThird Hospital of Hebei Medical University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

Hebei Province Medical Science Special Major Projects Research Fund 2015-03
6 · The paper itself

Abstract

The China National Fracture Study has been conducted to provide a national dataset of traumatic fractures across China. A national representative sample of 512,187 individuals was selected. The population-weighted incidence rates, distribution, injury mechanisms, and risk factors for traumatic fractures were identified for various groups of individuals.

introductionThe China National Fracture Study (CNFS) has been conducted to provide a comprehensive and up-to-date national dataset of traumatic fractures across China. This study aims to report the national incidences and distributions of traumatic fractures that occurred in 2012, 2013, and 2014 and to analyze the risk factors.

methodsA national representative sample of individuals was selected from 24 rural counties and 24 urban cities of 8 provinces using stratified random sampling and the probability proportional to size (PPS) methodology. Participants were interviewed to identify whether they sustained traumatic fractures of the trunk and/or four extremities that had occurred in 2012, 2013, and 2014. The main risk factors associated with traumatic fractures were analyzed by multiple logistic regression models.

resultsA total of 512,187 individuals, including 259,649 males and 252,538 females, participated in the CNFS. The population-weighted incidence rates of traumatic fractures in China were calculated to be 2.5 (95% CI, 2.2-2.8) per 1000 population in 2012, 2.8 (95% CI, 2.5-3.3) in 2013, and 3.2% (95% CI, 2.8-3.6) in 2014. The population-weighted incidence rates of fragility fractures among participants aged 65 years and older were calculated to be 27.4 (95% CI, 21.4-33.4) per 1000 population in 2012, 36.0 (95% CI, 28.6-43.5) in 2013, and 42.4 (95% CI, 34.9-49.9) in 2014. The most common cause of fracture was low-energy injuries, followed by traffic accidents. For all age groups, sleeping less than 7 h was a risk factor for traumatic fractures. Alcohol consumption and previous fracture history were identified as risk factors for adults aged 15 years and over. Cigarette smoking was found to be a risk factor for males aged 15-64 years old. For individuals aged 15-64 years old, underweight incurred a risk effect for males and overweight for females. Alcohol consumption, sleeping less than 7 h per day, living in the central and eastern regions, a body mass index less of than 18.5, and having a previous fracture history were identified as strong risk factors for fragility fractures.

conclusionThe national incidence, distribution, and injury mechanisms for traumatic fractures were revealed in the CNFS. Risk factors were identified for various groups of individuals.

Indexed as

Fractures, BoneAdolescentAdultAgedAlcohol DrinkingBody Mass IndexChinaFemaleHumansIncidenceMaleMiddle AgedRisk FactorsSleep DeprivationYoung AdultEpidemiologyFragility fractureIncidenceNational surveyRisk factorTraumatic fracture

Identifiers

PMID32524174
OpenAlexW3033330454

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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.