Cardiovascular risk factors are really linked in the metabolic syndrome: This phenomenon suggests clustering rather than coincidence

Combinação de fatores de risco relacionados à síndrome metabólica em militares da Marinha do Brasil

“…Of the 16 possibilities of combination, including at least three risk factors, seven showed higher prevalence than expected, and abdominal obesity was a common condition to all. In a similar study with a large Japanese population over the age of 40 years (41,819 men and 77,593 women), Aizawa et al 8 have reported that almost all combinations with at least three of the five components of the MS diagnosis occurred at a frequency over the one expected, indicating, similarly to this study, that a combination of risk factors occurred, and that such combination does not seem to be casual.…”

“…Although risk factors, in isolation, have a specific impact on health, they are often found in combination in individuals. The combination pattern of those risk factors has been investigated [5][6][7][8][9] . Studies can provide information about the pathophysiological mechanisms involved in cardiovascular disease, in addition to identifying a specific phenotype for the occurrence of a certain clinical condition in a population 8,9 .…”

Prevalence and Lifestyle Characteristics of Hypertensive Patients with Metabolic Syndrome Followed at an Outpatient Clinic in Fukuoka, Japan

“…Epidemiological studies have shown that MS occurs in a wide variety of ethnic groups (12,(15)(16)(17)(18). Data extracted from the third National Health and Nutrition Examination Survey (12) have shown that the age-adjusted prevalence of MS is 24% as defined by the NCEP-ATP III definition of MS.…”

Clustering of risk factors for cardiometabolic diseases in low-income, female adolescents

“…Expected prevalence of an specific risk factor clustering pattern was calculated based on the individual probability of each risk factor according to its occurrence in the sample. For example, expected prevalence of the clustering between central obesity (OC), high BP, dyslipidemia (DISL), absence of altered blood glucose (GL) and excess weight (EP) was calculated as follows: pOC x pPA x pDISL x (1 -pGL) x (1 -pEP), where p is the probability (prevalence/100) of the factor in the studied sample (5,22). Therefore, it was possible to investigate which combinations were higher or lower than expected values, assuming that risk factors occur independently in the studied population.…”

“…Although isolated risk factors have a specific impact on health, they are more frequently clustered in individuals (5). The clustering pattern of these risk factors have been investigated, including in adolescents (6)(7)(8)(9)(10), and this kind of analysis may subsidize the identification of risk factor clustering phenotypes in given populations (5,11), making clinical management easier by the use of specific preventive or therapeutic approaches.…”