Evidence map›Paper›PMID 26830813›Full record

ArticleBMC public health2016

Prevalence and associated factors of knee osteoarthritis in a rural Chinese adult population: an epidemiological survey.

Yuan Liu, Haifeng Zhang, Ningxia Liang, Weimin Fan, Jun Li, Zuhu Huang, Zhijian Yin, Zhijun Wu, Jun Hu

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 4 pooled it
4.6field-weighted citation impact, top 5% 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

50 citing papers in PubMed, 4 syntheses or guidelines pooled it, 105 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Yuan LiuDepartment of Infectious Diseases, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
Haifeng ZhangDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
Ningxia LiangDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
Weimin FanDepartment of Orthopedics, The First Affiliated Hospital of Nanjing Medical University, Guang Zhou Road 300, Nanjing, 210029, China.
Jun LiDepartment of Infectious Diseases, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
Zuhu HuangDepartment of Infectious Diseases, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
Zhijian YinCentre Clinics of Baqiao, Gaoyou, 225642, China.
Zhijun WuCentre Clinics of Baqiao, Gaoyou, 225642, China.
Jun HuDepartment of Orthopedics, The First Affiliated Hospital of Nanjing Medical University, Guang Zhou Road 300, Nanjing, 210029, China. junhu89@vip.sina.com.
Nanjing Medical University · CNJiangsu Province Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe exact pathogenic mechanism of knee osteoarthritis (OA) is still unknown. With the exception of clinical treatment to alleviate symptoms, or total knee replacement, there is currently no effective treatment method. Consequently, an in-depth etiological and epidemiological study of knee OA can provide clues for diagnosis, treatment and scientific research, and will ultimately have a beneficial effect on public health.

methodsA cross-sectional community study in the rural village of Gaoyou was conducted in 3428 Chinese adults (aged ≥ 40 years). Subjects completed an interviewer-administered questionnaire, evaluating knee pain and associated disability, analgesia, use of health services, past medical history, walking, income, smoking, and use of oral contraceptives, and standardized weight-bearing knee radiographs were obtained. Patient demographic characteristics and biochemical parameters were recorded.

resultsSingle-factor regression analysis indicated that age, overweight, central adiposity, high low-density lipoprotein cholesterol (LDLC), high total cholesterol (TC), high triglycerides (TG), dyslipidemia, hypertension and low income were the associated factors for knee OA in females; age, high LDLC, hypertension, low income and frequent walking were the associated factors for knee OA in males. Interestingly, male heavy smokers were less likely to develop severe knee OA compared with non-smokers. Stepwise logistic regression analysis indicated that age and overweight were the associated factors for knee OA for all individuals. Although central adiposity, high LDLC, high TC, high TG, dyslipidemia, hypertension and low income appeared to be related to knee OA in females according to univariate analysis, these factors were not identified in stepwise logistic regression analysis. In addition although age, high LDLC, hypertension and frequent walking were also the associated factors for knee OA in males by stepwise logistic regression analysis, smoking as a protective factor was not identified in this analysis.

conclusionsIn this study, aging, obesity, frequent walking, low income and relevant multiple metabolic disorders were the associated factors for knee OA. Smoking might be associated with a lower prevalence of OA in male smokers according to univariate analysis. A retrospective association of smoking with OA may constitute an important etiologic clue, but further well-designed, large-scale prospective controlled trials are required to confirm these findings.

Indexed as

Health StatusAdultAgedAge DistributionComorbidityCross-Sectional StudiesDyslipidemiasFemaleHumansHypertensionMaleMiddle AgedObesityOsteoarthritis, KneePrevalenceRetrospective Studies

Identifiers

PMID26830813
PMCPMC4736305
OpenAlexW2252790379

What OpenQuestion holds

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LicenceCC BY
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.