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Plasminogen Activator Inhibitor ‐ 1 and Diagnosis of the Metabolic Syndrome in a West African Population

View Article: PubMed Central - PubMed

ABSTRACT

Background: Metabolic syndrome (MetS) is diagnosed by the presence of at least 3 of the following: obesity, hypertension, hyperglycemia, hypertriglyceridemia, and low high‐density lipoprotein. Individuals with MetS also typically have elevated plasma levels of the antifibrinolytic factor, plasminogen activator inhibitor‐1 (PAI‐1), but the relationships between PAI‐1 and MetS diagnostic criteria are not clear. Understanding these relationships can elucidate the relevance of MetS to cardiovascular disease risk, because PAI‐1 is associated with ischemic events and directly involved in thrombosis.

Methods and results: In a cross‐sectional analysis of 2220 Ghanaian men and women from urban and rural locales, we found the age‐standardized prevalence of MetS to be as high as 21.4% (urban women). PAI‐1 level increased exponentially as the number of diagnostic criteria increased linearly (P<10−13), supporting the conclusion that MetS components have a joint effect that is stronger than their additive contributions. Body mass index, triglycerides, and fasting glucose were more strongly correlated with PAI‐1 than with canonical MetS criteria, and this pattern did not change when pair‐wise correlations were conditioned on all other risk factors, supporting an independent role for PAI‐1 in MetS. Finally, whereas the correlations between conventional risk factors did not vary significantly by sex or across urban and rural environments, correlations with PAI‐1 were generally stronger among urban participants.

Conclusions: MetS prevalence in the West African population we studied was comparable to that of the industrialized West. PAI‐1 may serve as a key link between MetS, as currently defined, and the endpoints with which it is associated. Whether this association is generalizable will require follow‐up.

No MeSH data available.


Related in: MedlinePlus

Relationship between the total number of risk factor diagnoses and mean PAI‐1 concentrations. Horizontal axis: 2220 participants from the Brong Ahafo region of Ghana were grouped by number of risk factor conditions (obesity, hypertension, hyperglycemia, hypertriglyceridemia, and low HDL); 22 participants had all 5; 573 had 4; 473 had 3; 376 had 2; 300 had 1; and 573 had none. Vertical axis: For each group, mean standardized ln‐PAI‐1 concentrations (adjusted for age, sex, and urban/rural residence) are depicted with 95% CIs. P values above horizontal brackets are for t tests comparing the means of adjacent groups. PAI‐1 was normally distributed within each group (Shapiro‐Wilk test; P>0.05). The quadratic fit to the means is also depicted (R2=0.996). HDL indicates high‐density lipoprotein cholesterol; MetS, metabolic syndrome; PAI‐1, plasminogen activator inhibitor 1.
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jah31797-fig-0001: Relationship between the total number of risk factor diagnoses and mean PAI‐1 concentrations. Horizontal axis: 2220 participants from the Brong Ahafo region of Ghana were grouped by number of risk factor conditions (obesity, hypertension, hyperglycemia, hypertriglyceridemia, and low HDL); 22 participants had all 5; 573 had 4; 473 had 3; 376 had 2; 300 had 1; and 573 had none. Vertical axis: For each group, mean standardized ln‐PAI‐1 concentrations (adjusted for age, sex, and urban/rural residence) are depicted with 95% CIs. P values above horizontal brackets are for t tests comparing the means of adjacent groups. PAI‐1 was normally distributed within each group (Shapiro‐Wilk test; P>0.05). The quadratic fit to the means is also depicted (R2=0.996). HDL indicates high‐density lipoprotein cholesterol; MetS, metabolic syndrome; PAI‐1, plasminogen activator inhibitor 1.

Mentions: Mean PAI‐1 (log‐normalized and adjusted for age, sex, and residence) rose exponentially as the number of MetS risk factors increased linearly. The quadratic fit to the means was virtually perfect (R2=0.996). Among participants who had at least 1 MetS risk factor, mean PAI‐1 increased significantly with each additional condition, with the most significant increase occurring when the number of conditions increased from 2 to 3, consistent with the NCEP ATP‐III definition (Figure 1). Ordinal polynomial regression was also used to model the number of MetS risk factors as a function of PAI‐1. The improvement of the quadratic fit over the linear fit was highly significant (P<10−13), confirming the strong exponential relationship between the logarithm of PAI‐1 level and number of MetS criteria.


Plasminogen Activator Inhibitor ‐ 1 and Diagnosis of the Metabolic Syndrome in a West African Population
Relationship between the total number of risk factor diagnoses and mean PAI‐1 concentrations. Horizontal axis: 2220 participants from the Brong Ahafo region of Ghana were grouped by number of risk factor conditions (obesity, hypertension, hyperglycemia, hypertriglyceridemia, and low HDL); 22 participants had all 5; 573 had 4; 473 had 3; 376 had 2; 300 had 1; and 573 had none. Vertical axis: For each group, mean standardized ln‐PAI‐1 concentrations (adjusted for age, sex, and urban/rural residence) are depicted with 95% CIs. P values above horizontal brackets are for t tests comparing the means of adjacent groups. PAI‐1 was normally distributed within each group (Shapiro‐Wilk test; P>0.05). The quadratic fit to the means is also depicted (R2=0.996). HDL indicates high‐density lipoprotein cholesterol; MetS, metabolic syndrome; PAI‐1, plasminogen activator inhibitor 1.
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jah31797-fig-0001: Relationship between the total number of risk factor diagnoses and mean PAI‐1 concentrations. Horizontal axis: 2220 participants from the Brong Ahafo region of Ghana were grouped by number of risk factor conditions (obesity, hypertension, hyperglycemia, hypertriglyceridemia, and low HDL); 22 participants had all 5; 573 had 4; 473 had 3; 376 had 2; 300 had 1; and 573 had none. Vertical axis: For each group, mean standardized ln‐PAI‐1 concentrations (adjusted for age, sex, and urban/rural residence) are depicted with 95% CIs. P values above horizontal brackets are for t tests comparing the means of adjacent groups. PAI‐1 was normally distributed within each group (Shapiro‐Wilk test; P>0.05). The quadratic fit to the means is also depicted (R2=0.996). HDL indicates high‐density lipoprotein cholesterol; MetS, metabolic syndrome; PAI‐1, plasminogen activator inhibitor 1.
Mentions: Mean PAI‐1 (log‐normalized and adjusted for age, sex, and residence) rose exponentially as the number of MetS risk factors increased linearly. The quadratic fit to the means was virtually perfect (R2=0.996). Among participants who had at least 1 MetS risk factor, mean PAI‐1 increased significantly with each additional condition, with the most significant increase occurring when the number of conditions increased from 2 to 3, consistent with the NCEP ATP‐III definition (Figure 1). Ordinal polynomial regression was also used to model the number of MetS risk factors as a function of PAI‐1. The improvement of the quadratic fit over the linear fit was highly significant (P<10−13), confirming the strong exponential relationship between the logarithm of PAI‐1 level and number of MetS criteria.

View Article: PubMed Central - PubMed

ABSTRACT

Background: Metabolic syndrome (MetS) is diagnosed by the presence of at least 3 of the following: obesity, hypertension, hyperglycemia, hypertriglyceridemia, and low high&#8208;density lipoprotein. Individuals with MetS also typically have elevated plasma levels of the antifibrinolytic factor, plasminogen activator inhibitor&#8208;1 (PAI&#8208;1), but the relationships between PAI&#8208;1 and MetS diagnostic criteria are not clear. Understanding these relationships can elucidate the relevance of MetS to cardiovascular disease risk, because PAI&#8208;1 is associated with ischemic events and directly involved in thrombosis.

Methods and results: In a cross&#8208;sectional analysis of 2220 Ghanaian men and women from urban and rural locales, we found the age&#8208;standardized prevalence of MetS to be as high as 21.4% (urban women). PAI&#8208;1 level increased exponentially as the number of diagnostic criteria increased linearly (P&lt;10&minus;13), supporting the conclusion that MetS components have a joint effect that is stronger than their additive contributions. Body mass index, triglycerides, and fasting glucose were more strongly correlated with PAI&#8208;1 than with canonical MetS criteria, and this pattern did not change when pair&#8208;wise correlations were conditioned on all other risk factors, supporting an independent role for PAI&#8208;1 in MetS. Finally, whereas the correlations between conventional risk factors did not vary significantly by sex or across urban and rural environments, correlations with PAI&#8208;1 were generally stronger among urban participants.

Conclusions: MetS prevalence in the West African population we studied was comparable to that of the industrialized West. PAI&#8208;1 may serve as a key link between MetS, as currently defined, and the endpoints with which it is associated. Whether this association is generalizable will require follow&#8208;up.

No MeSH data available.


Related in: MedlinePlus