Evidence map›Paper›PMID 33102414›Full record

ArticleFrontiers in public health2020

A Syndemic Perspective on the Management of Non-communicable Diseases Amid the COVID-19 Pandemic in Low- and Middle-Income Countries.

Uday Narayan Yadav, Binod Rayamajhee, Sabuj Kanti Mistry, Shradha S Parsekar, Shyam Kumar Mishra

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
88citing papers in PubMed, 2 pooled it
30.9field-weighted citation impact, top 1% 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

88 citing papers in PubMed, 2 syntheses or guidelines pooled it, 169 citations in OpenAlex.

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28 more citing papers are in PubMed but not listed here.

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

5 authors at 4 institutions in 5 countries.

Uday Narayan YadavCentre for Primary Health Care and Equity, University of New South Wales (UNSW), Sydney, NSW, Australia.
Binod RayamajheeSchool of Optometry and Vision Science, Faculty of Science, University of New South Wales, Sydney, NSW, Australia.
Sabuj Kanti MistryCentre for Primary Health Care and Equity, University of New South Wales (UNSW), Sydney, NSW, Australia.
Shradha S ParsekarPublic Health Evidence South Asia, Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal, India.
Shyam Kumar MishraSchool of Optometry and Vision Science, Faculty of Science, University of New South Wales, Sydney, NSW, Australia.
UNSW Sydney · AUBRAC University · BDGlobal Forum for Health Research · CHManipal Academy of Higher Education · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global coronavirus disease (COVID-19) pandemic has greatly affected the lives of people living with non-communicable diseases (PLWNCDs). The health of PLWNCDs worsens when synergistic epidemics or "syndemics" occur due to the interaction between socioecological and biological factors, resulting in adverse outcomes. These interactions can affect the physical, emotional, and social well-being of PLWNCDs. In this paper, we discuss the effects of the COVID-19 syndemic on PLWNCDs, particularly how it has exposed them to NCD risk factors and disrupted essential public health services. We conclude by reflecting on strategies and policies that deal with the COVID-19 syndemic among PLWNCDs in low- and middle-income countries.

Indexed as

COVID-19Noncommunicable DiseasesDeveloping CountriesHumansPandemicsSARS-CoV-2SyndemicCOVID-19LMICsNCDSSARS-CoV-2syndemic framework

Identifiers

PMID33102414
PMCPMC7545493
OpenAlexW3080661472

What OpenQuestion holds

Textmetadata
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.