Evidence map›Paper›PMID 36705225›Full record

ArticleJNMA; journal of the Nepal Medical Association2022

Hyperkyphosis among the Elderly in a Community: A Descriptive Cross-sectional Study.

Inosha Bimali, Sikha Pudasaini

Open access · diamondAbstract read
In one paragraph

Article in JNMA; journal of the Nepal Medical Association, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

3 citing papers in PubMed, 6 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

2 authors at 2 institutions in 1 country.

Inosha BimaliDepartment of Physiotherapy, Kathmandu University School of Medical Sciences, Dhulikhel, Kavre, Nepal.
Sikha PudasainiDepartment of Physiotherapy, Norvic International Hospital, Thapathali, Kathmandu, Nepal.
Grande International Hospital · NPKathmandu University · NP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Aging brings progressive changes in the physiology of the musculoskeletal system that leads to postural changes and degenerative diseases in elderly. The most common postural change is hyperkyphosis which decreases physical performance, ability to perform daily activities, overall quality of life, and increases the risk of falls in elderly. The aim of the study was to find out the prevalence of hyperkyphosis among the elderly in a community. Methods: A descriptive cross-sectional study was done in a local community from 26 May 2019 to 8 June 2019 after obtaining ethical approval from the Institutional Review Committee (Protocol approval number: 138/19). Participants above 60 years of age were included in the study. Convenience sampling was done. A bubble inclinometer was used to measure the degree of kyphosis. Point estimate and 95% Confidence Interval were calculated. Results: Among 144 elderly participants, hyperkyphosis was present in 90 (62.50%) (54.59-70.41, 95% Confidence Interval) with the mean hyperkyphosis being 47.07±4.83˚. The elderly in the age group of 70-75 years had a higher degree of hyperkyphosis with a mean value of 47.77±4.92˚. The mean hyperkyphosis was 48.18±5.30˚ and 45.31±3.36˚ in female and male participants respectively. Conclusions: The prevalence of hyperkyphosis was found to be higher in our study compared to other studies conducted in similar settings. Early identification and interventions of hyperkyphosis are thus warranted to prevent the detrimental consequences in the later stages of life. Keywords: aging; hyperkyphosis; posture.

Indexed as

KyphosisQuality of LifeAgedCross-Sectional StudiesFemaleHumansMaleRisk AssessmentRisk Factors

Identifiers

PMID36705225
PMCPMC9446495
OpenAlexW4289261787

What OpenQuestion holds

Textmetadata
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.