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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

Strengths of correlation between cardiovascular risk factors associated with metabolic syndrome and their differences by sex and urban/rural residence. A, Colors in the heat map reflect the magnitude of correlation between risk factors adjusted for age, sex, and residence. In (B), shading reflects the statistical significance of differences in correlation by sex (below diagonal, purple) and residence (above diagonal, green). BMI indicates body mass index; GLUC, glucose; HDL, high‐density lipoprotein cholesterol; MAP, mean arterial pressure; PAI‐1, plasminogen activator inhibitor 1; TG, triglycerides.
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jah31797-fig-0002: Strengths of correlation between cardiovascular risk factors associated with metabolic syndrome and their differences by sex and urban/rural residence. A, Colors in the heat map reflect the magnitude of correlation between risk factors adjusted for age, sex, and residence. In (B), shading reflects the statistical significance of differences in correlation by sex (below diagonal, purple) and residence (above diagonal, green). BMI indicates body mass index; GLUC, glucose; HDL, high‐density lipoprotein cholesterol; MAP, mean arterial pressure; PAI‐1, plasminogen activator inhibitor 1; TG, triglycerides.

Mentions: All pair‐wise correlations between risk factors adjusted for age, sex, and residence were statistically significant (P<0.0001), except for the correlation between MAP and HDL (Table 2 and Figure 2). Seven of 15 correlations were at least 0.20 in magnitude: BMI‐PAI‐1; BMI‐TG; BMI‐MAP; TG‐PAI‐1; TG‐HDL; MAP‐PAI‐1; and GLUC‐PAI‐1. The above analysis was repeated after stratifying participants by urban versus rural residence and adjusting for age and sex. Of the 5 pair‐wise correlations with PAI‐1, 3 were significantly stronger in the urban population: BMI (P=4.9×10−9); GLUC (P=9.9×10−4); and TG (P=2.1×10−3; Table 2 and Figure 2). Among pair‐wise correlations that did not include PAI‐1, only 2 of 10 pairs were significantly different: BMI‐HDL (P=0.047) and BMI‐TG (P=0.012), with both correlations again stronger in the urban population (Table 2 and Figure 2). When participants were stratified by sex, no P value for homogeneity of correlation was smaller than 0.01 (Table 3 and Figure 2). Of the 3 significant at the 0.05 level, the GLUC‐PAI‐1 correlation was higher in women than in men, and the correlations of both BMI and PAI‐1 with MAP were higher in men.


Plasminogen Activator Inhibitor ‐ 1 and Diagnosis of the Metabolic Syndrome in a West African Population
Strengths of correlation between cardiovascular risk factors associated with metabolic syndrome and their differences by sex and urban/rural residence. A, Colors in the heat map reflect the magnitude of correlation between risk factors adjusted for age, sex, and residence. In (B), shading reflects the statistical significance of differences in correlation by sex (below diagonal, purple) and residence (above diagonal, green). BMI indicates body mass index; GLUC, glucose; HDL, high‐density lipoprotein cholesterol; MAP, mean arterial pressure; PAI‐1, plasminogen activator inhibitor 1; TG, triglycerides.
© Copyright Policy - creativeCommonsBy-nc-nd
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5121488&req=5

jah31797-fig-0002: Strengths of correlation between cardiovascular risk factors associated with metabolic syndrome and their differences by sex and urban/rural residence. A, Colors in the heat map reflect the magnitude of correlation between risk factors adjusted for age, sex, and residence. In (B), shading reflects the statistical significance of differences in correlation by sex (below diagonal, purple) and residence (above diagonal, green). BMI indicates body mass index; GLUC, glucose; HDL, high‐density lipoprotein cholesterol; MAP, mean arterial pressure; PAI‐1, plasminogen activator inhibitor 1; TG, triglycerides.
Mentions: All pair‐wise correlations between risk factors adjusted for age, sex, and residence were statistically significant (P<0.0001), except for the correlation between MAP and HDL (Table 2 and Figure 2). Seven of 15 correlations were at least 0.20 in magnitude: BMI‐PAI‐1; BMI‐TG; BMI‐MAP; TG‐PAI‐1; TG‐HDL; MAP‐PAI‐1; and GLUC‐PAI‐1. The above analysis was repeated after stratifying participants by urban versus rural residence and adjusting for age and sex. Of the 5 pair‐wise correlations with PAI‐1, 3 were significantly stronger in the urban population: BMI (P=4.9×10−9); GLUC (P=9.9×10−4); and TG (P=2.1×10−3; Table 2 and Figure 2). Among pair‐wise correlations that did not include PAI‐1, only 2 of 10 pairs were significantly different: BMI‐HDL (P=0.047) and BMI‐TG (P=0.012), with both correlations again stronger in the urban population (Table 2 and Figure 2). When participants were stratified by sex, no P value for homogeneity of correlation was smaller than 0.01 (Table 3 and Figure 2). Of the 3 significant at the 0.05 level, the GLUC‐PAI‐1 correlation was higher in women than in men, and the correlations of both BMI and PAI‐1 with MAP were higher in men.

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