Cited by 1Diabetes, Cardiovascular Risks, and LipoproteinsAdipokines, Inflammation, and Metabolic DiseasesDiet, Metabolism, and Disease

Metabolic Syndrome: An Emerging Threat

Open access
Rahman, Quazi Audry Arafat, Razzak, Md Abdur, Wahab, Md Abdul·2020·Journal of Armed Forces Medical College, Bangladesh

Abstract

Metabolic syndrome (MetS) is a multifaceted syndrome, which occurs frequently in the general population. It represents a cluster of metabolic abnormalities that include hypertension, central obesity, insulin resistance, and atherogenic dyslipidemia, and is strongly associated with an increased risk for developing diabetes and atherosclerotic and nonatherosclerotic cardiovascular disease (CVD). The pathogenesis of MetS involves both genetic and acquired factors that contribute to the final pathway of inflammation that leads to CVD. MetS has gained significant importance recently due to the exponential increase in obesity worldwide. Early diagnosis is important in order to employ lifestyle and risk factor modification. Here, we review the epidemiology, diagnostic criteria, pathogenesis and disease associations of MetS, and summarize existing management modalities. Journal of Armed Forces Medical College Bangladesh Vol.14 (2) 2018: 203-208

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Registry

Crossref · 10.3329/jafmc.v14i2.45911

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48 of 48 references verified0 citation errors · 0 not checkable

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  • Age is related to metabolic changes.

    “Gender affects hormonal and metabolic functions, age is related to metabolic changes, height is associated with body proportions and health, and waist circumference (WC) indicates central obesity, a key part of MetS [12, 13].”

    From Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome (2025) · cites this paper as [12]

    The Diagnostic Criteria section (p. 1) lists advancing age among factors considered in assessing metabolic syndrome, supporting an association between age and metabolic health. It does not describe metabolic changes that occur with age, so the claim is broader than the passage supports. (LLM, conf=0.76)

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  • Waist circumference indicates central obesity, a key part of metabolic syndrome.

    “Gender affects hormonal and metabolic functions, age is related to metabolic changes, height is associated with body proportions and health, and waist circumference (WC) indicates central obesity, a key part of MetS [12, 13].”
  • Height is associated with body proportions and health.

    “Gender affects hormonal and metabolic functions, age is related to metabolic changes, height is associated with body proportions and health, and waist circumference (WC) indicates central obesity, a key part of MetS [12, 13].”

    From Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome (2025) · cites this paper as [12]

    The Introduction (p. 1) discusses body mass index and waist-to-hip ratio, and Systemic Effects (p. 3) discusses fat distribution around the waist. Neither addresses an association between height, body proportions, and health. Searches for height, stature, and related body-proportion terms found no passage supporting that claim. (LLM, conf=0.73)

    Experimental — accuracy not yet measured
  • Gender affects hormonal and metabolic functions.

    “Gender affects hormonal and metabolic functions, age is related to metabolic changes, height is associated with body proportions and health, and waist circumference (WC) indicates central obesity, a key part of MetS [12, 13].”

    From Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome (2025) · cites this paper as [12]

    The Introduction (p. 1) reports differences in metabolic-syndrome prevalence by sex, while Systemic Effects (p. 3) lists reproductive conditions associated with the syndrome. Neither passage says that gender affects hormonal and metabolic functions; searches for sex-related hormonal and metabolic differences found no passage making that claim. (LLM, conf=0.72)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 10

  1. [11]11. Palaniappan L, Carnethon MR, Wang Y et al. Predictors of the incident metabolic syndrome in adults: The Insulin Resistance Atherosclerosis Study. Diabetes Care 2004; 27(3):788-93.
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  7. [44]44. Grundy SM, Hansen B, Smith SC et al. American Heart Association; National Heart, Lung, and Blood Institute; American Diabetes Association. Clinical management of metabolic syndrome: report of the American Heart Association/National Heart, Lung, and Blood Institute/American Diabetes Association conference on scientific issues related to management. Circulation 2004; 109(4):551-6.
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Authors
Rahman, Q. A. A., Razzak, M. A., & Wahab, M. A.
Affiliations
Armed Forces Medical College (BD)
Venue
Journal of Armed Forces Medical College, Bangladesh
Published
2020-03-10
Volume
14
Issue
2
Pages
203-208
ISSN
1992-5743 (ISSN-L)
OpenAlex
W3046834602
Cited by
1
References
49
Citations by year
2025: 1
FWCI
0.00
Type
journal article
Language
en
Open access
Locations
Journal of Armed Forces Medical College Bangladesh (publishedVersion)
Topics
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
  • Health Sciences › Medicine › Epidemiology › Adipokines, Inflammation, and Metabolic Diseases
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diet, Metabolism, and Disease
Keywords
metabolic syndrome, hypertension, abdominal obesity, insulin resistance, dyslipidemia, cardiovascular disease, diabetes mellitus, inflammation, obesity, diagnostic criteria, pathogenesis, disease management

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