ArticleJournal of cardiovascular disease research2010
Factor analysis of risk variables associated with metabolic syndrome in adult Asian Indians.
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.
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.
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.
Who cites it
5 citing papers in PubMed, 10 citations in OpenAlex.
- ACE2 and TMPRSS2 polymorphisms in various diseases with special reference to its impact on COVID-19 disease.Microbial pathogenesis · 2021Review
- Assessing clustering of metabolic syndrome components available at primary care for Bantu Africans using factor analysis in the general population.BMC research notes · 2013Article
- Cluster analysis reveals important determinants of cardiometabolic risk patterns in Filipino women.Asia Pacific journal of clinical nutrition · 2012Article
- Ethnic differences in the prevalence of metabolic syndrome: results from a multi-ethnic population-based survey in Malaysia.PloS one · 2012Article
- Association of metabolic syndrome with obesity measures, metabolic profiles, and intake of dietary fatty acids in people of Asian Indian origin.Journal of cardiovascular disease research · 2010Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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
Identifiers
What OpenQuestion holds
Registered trials
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.