Evidence map›Paper›PMID 22650800›Full record

ArticleDiabetology & metabolic syndrome2012

Metabolic syndrome among Sri Lankan adults: prevalence, patterns and correlates.

Prasad Katulanda, Priyanga Ranasinghe, Ranil Jayawardana, Rezvi Sheriff, David R Matthews

Abstract read
In one paragraph

Article in Diabetology & metabolic syndrome, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

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3 · Its place in the literature

Who cites it

54 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

5 authors.

Prasad KatulandaDiabetes Research Unit, Department of Clinical Medicine, Faculty of Medicine, University of Colombo, Colombo, Sri Lanka. pkatulanda@yahoo.com.
Priyanga Ranasinghe
Ranil Jayawardana
Rezvi Sheriff
David R Matthews

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolic Syndrome (MS) increases the risk for Coronary Artery Disease, stroke and diabetes. MS is twice more common amongst South Asian immigrants in US compared to native Caucasians. There are no nationally representative studies on prevalence of MS from any of the South Asian countries. The present study aims to evaluate the prevalence of MS among Sri Lankan adults and investigates its relationships with socio-demographic, clinical and biochemical parameters. Data on MS and its associated details were obtained from a population-based cross-sectional study conducted between years 2005-2006. MS was defined according to the International Diabetes Federation criteria. A binary logistic regression analysis was performed using the dichotomous variable MS (0 = absent, 1 = present). The independent co-variants were: gender, age category, area of residence, ethnicity, level of education, income and physical activity. Sample size was 4,485 (Response rate-89.7%), 39.5% were males and mean age was 46.1 ± 15.1 years. The crude prevalence of MS was 27.1% (95% CI: 25.8-28.5), and age-adjusted prevalence was 24.3% (95% CI: 23.0-25.6). Prevalence in males and females were 18.4% (95% CI: 16.5-20.3) and 28.3% (95% CI: 26.6-30.0) respectively (p < 0.001). Urban adults (34.8% [95% CI: 31.8-37.9]) had a significantly higher prevalence than rural adults (21.6% [95% CI: 20.2-23.0]). Among ethnic groups, the highest prevalence of MS was observed in Sri Lankan Moors (43.0% [95% CI: 37.2-48.9]). In all adults, MS was observed in those with the highest level of education and monthly household income. Prevalence of MS in the different physical activity categories of the IPAQ were; 'inactive'-38.8% (95% CI 34.5-43.2), 'moderately active'-33.5% (95% CI 30.9-36.1) and 'active'-21.1% (95% CI 19.6-22.7). The results of the binary logistic regression analysis indicates that female gender (OR:1.7), increasing age, urban living (OR:1.7), Moor ethnicity (OR:2.6), secondary (OR:1.5) and tertiary levels of education (OR:2.3), monthly household income LKR 7,000-24,999 (OR:1.5) and >50,000 (OR:2.1), and physical inactivity (OR:1.6), all significantly increased risk of developing MS. MS is common among Sri Lankan adults affecting nearly one-fourth of the population. Female gender, increasing age, urban living, higher socio-economical status and physical inactivity were important associated factors.

Identifiers

PMID22650800
PMCPMC3407762

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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.