Evidence map›Paper›PMID 35957840›Full record

ArticleFrontiers in endocrinology2022

Osteoporosis and Related Health Status Among the Elderly Urban Residents in Elderly-Care Inns in Beijing, a Multicenter DXA Survey.

XinChao Lin, HongTao Guo, YiGang Lian, Jiajing Kou, GuangLei Wang, YiYun Chen, Juan Wang, Xu Han, Miao Jiang, QiaoHui Yang

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

5 citing papers in PubMed, 15 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

10 authors at 3 institutions in 1 country.

XinChao LinDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
HongTao GuoThe First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China.
YiGang LianDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Jiajing KouDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
GuangLei WangDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
YiYun ChenDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Juan WangInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Xu HanInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Miao JiangInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
QiaoHui YangDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNFirst Affiliated Hospital of Henan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Identification of the high risk population for osteoporosis and timely prevention are the best strategies at present. Detailed epidemiological investigation in a well-defined population is necessary to explore the population-based characteristics and risk factors of osteoporosis, thus to facilitate better prevention programs. Method: In this prospective cross-sectional study, 1423 questionnaires were given out to the urban residents (female ≥ 40 years of age, male ≥50 years) who lived in the 27 Elderly-Care Inns interspersed among the seven central urban areas of Beijing. All participants were voluntary and underwent routine physical examination and spine and hip BMD measurements using the DXA instrument. The study protocols were approved by the Medical Ethics Committee of Dongzhimen Hospital, Beijing University of Chinese Medicine (JDZX2015079). Results: Altogether 1407 participants fulfilled the survey. Among 359 men, the prevalence of osteoporosis, osteopenia, and normal BMD were 18.1%, 56.6%, and 25.3%, respectively; among 1048 women, the corresponding figures were 40.3%, 42.8%, and 16.9%, respectively. After adjustment of age and BMI, both hands grip strength, height loss over 3 cm, serum levels of β-CTx, PINP, and OST were the independent risk factors for osteoporosis in both men and women; besides, familial Alzheimer's disease history in men; and history of steatohepatitis and fracture, serum levels of PTH and ALT, age of menarche, age of menopause, and duration of menstruation in women were also risk factors of osteoporosis. In both genders, the cost-effective method, which adopted both hands grip strength, height loss over 3 cm, and medical history, indicated a good predictive ability to evaluate the risk of osteoporosis (in men AUC=0.730, 95%CI=0.642~0.817; in women AUC=0.769, 95%CI=0.724~0.813). Conclusions: In the population of elderly Beijing urban residents in Elderly-Care Inns, the prevalence of osteoporosis in women is higher than that in men and increases with aging more rapidly; the prevalence of osteopenia in men is higher than in women. The cost-effective method, including both hands grip strength, height loss over 3 cm, and familial Alzheimer's disease history in men; fracture and steatohepatitis history as well as menstrual history in women is recommended in identifying the high-risk subjects for osteoporosis.

Indexed as

Alzheimer DiseaseBone Diseases, MetabolicFatty LiverFractures, BoneOsteoporosisAbsorptiometry, PhotonAgedBone DensityCross-Sectional StudiesFemaleHealth StatusHumansMaleMiddle AgedProspective StudiesSurveys and QuestionnairesDXAosteopeniaosteoporosisrisk factorsurveyurban area in Beijing

Identifiers

PMID35957840
PMCPMC9359074
OpenAlexW4286559924

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.