Evidence map›Paper›PMID 20877692›Full record

ArticleJournal of cardiovascular disease research2010

Factor analysis of risk variables associated with metabolic syndrome in adult Asian Indians.

Mithun Das, Susil Pal, Arnab Ghosh

Open access · greenAbstract read
In one paragraph

Article in Journal of cardiovascular disease research, 2010. 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
0.9field-weighted citation impact, top 24% 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, 10 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

3 authors at 2 institutions in 1 country.

Mithun DasPost Graduate Department of Anthropology, Sree Chaitanya College, Habra, West Bengal, India.
Susil Pal
Arnab Ghosh
Centre For Human Genetics · INVisva-Bharati University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSeveral studies hinted about the clustering of risk variables of the metabolic syndrome (MS) and suggested that the underlying genetic polymorphisms could be responsible for the increasing incidence of coronary heart disease (CHD) in people of Indian origin. Therefore, identification of the components of the MS along with the genetic factors could be one of the aspects to make an attempt to prevent the increasing incidence of CHD. MATERIALS AND

methodsPrincipal component factor analysis (PCFA) was undertaken to identify the components or factors of the MS among the adult (≥30 years) Asian Indians living in and around Calcutta, India. The study comprised 350 adult Asian Indians. Anthropometric measurements were taken, and lipid profiles, blood pressure and fasting blood glucose were measured for each participant. Two genetic polymorphisms, namely, angiotensin converting enzyme (ACE) gene polymorphism (insertion/deletion [I/D]) or ACE (I/D) and apolipoproteinE (Hha I) were also studied.

resultsPCFA revealed 3 factors that cumulatively explained 65.39% of the observed variance of the MS by measured variables. The 3 factors identified were lipids and lipoprotein (Factor 1), centripetal fat and blood pressure (Factor 2), and ACE (I/D) polymorphism with blood pressure (Factor 3). Moreover, the first 2 factors, that is, lipids, lipoprotein, centripetal fat, and blood pressures cumulatively explained ~46% (45.94%) of the observed variance of MS in this population.

conclusionsSince more than 1 factor was identified for the MS phenotype, more than 1 physiogenetic mechanism could be accounted for MS in the Asian Indian population.

Indexed as

Asian Indiansfactorsgene polymorphismmetabolic syndromeobesity

Identifiers

PMID20877692
PMCPMC2945203
OpenAlexW2079977501

What OpenQuestion holds

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LicenceCC BY-NC-SA
Read underepoch 390

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.