Integration of suboptimal health status and endothelial dysfunction as a new aspect for risk evaluation of cardiovascular disease


Changes in lipid affect the condition of vessel wall—the endothelium. Over the last
decade, there is accumulated evidence of the importance of determining the stiffness
of the arterial wall as an indicator on vascular remodeling. With photopletismography
arterial stiffness and endothelial dysfunction can be accessed. The higher the absolute
value of stiffness index, the lower the expression of index of endothelial function
(IEF) and a healthy vascular wall. Our study showed that in the group of participants
with risk factors value was 7.5?±?7.6 %, which was significantly lower (p??0.01) than those in healthy group, whose proportion was 18.4?±?7.7 %. The index
of endothelial function was found significantly correlated with the overall performance
of suboptimal health status (r?=??0.31, p??0.05), as well as with individual sub-scales of the questionnaire SHSQ-25: fatigue
(r?=??0.36, p??0.05), mental (r?=??0.29, p??0.05), and the cardiovascular system (r?=??0.36, p??0.05). Linear regression also showed association between SHS and IEF (Table 3).

Table 3. The results of the regression analysis (dependent variable SHSQ score)

Given the obvious correlations between indicators of endothelial dysfunction and the
values of the scales of the questionnaire SHSQ-25, we explored the integral relationship
between the values of SHS indicators of endothelial dysfunction and risk factors for
cardiovascular disease. In our study, a newly created instrument, SHSQ-25, was used
for measurement of SHS. The SHSQ-25 is a self-rated questionnaire of perceived health
complaints which is a brief and valid instrument for the assessment of SHS 3]. To do this, we used multivariate statistical analysis on the following parameters:
the values of profiles SHS-25 subscale (“fatigue,” “mental status,” “cardiovascular
system,” “digestive system,” “immune system,” and “the total amount of SHS-25”), the
index of the smoker, BMI, SBP, DBP and endothelial function parameters, vascular stiffness
index, the index of reflection pulse wave, blood glucose, and TCH.

Based on the cluster analysis on risk factors of cardiovascular system and indicators
of SHS, all the subjects were classified into five clusters (Fig. 1). The first cluster includes 99 young persons, with a low value of the total index
SHSQ-25, normal weight, blood pressure, lack of endothelial dysfunction, reduced levels
of glucose and cholesterol. These persons were estimated as the persons with the optimal
health status. The second cluster contains 121 cases. This cluster was characterized
by the young age of the participants, the mean value of the total index SHSQ-25, with
deviations in the mental sphere, and the immune system, normal weight, blood pressure,
lack of endothelial dysfunction, reduced levels of glucose, cholesterol. This cluster
was described as a cluster of SHS at low risk of disease states. The third cluster
(?=?91 cases) is different from the other two by high values of the cumulative index
SHSQ-25, especially on the scale of the mental sphere, digestive tract, and immune
system. This cluster was described by us as a cluster of SHS with a high risk of non-cardiac
pathologies profile. Faces of the fourth cluster (?=?94 cases) were aged over 35 years, with the average values of the total index SHSQ-25,
but with the presence of at least 1–2 risk factors for cardiovascular disease. This
is mainly overweight or long smoking history. We designated it as a cardiovascular
phenotype of SHS of low risk of cardiovascular disease. And finally, the fifth cluster
(?=?54 cases) differs in significant variations in the total index SHSQ-25, the scale
of cardiovascular disease, and the presence of risk factors for cardiovascular disease
and endothelial dysfunction. These patients were referred to our cardiovascular phenotype
of SHS with high risk of cardiovascular disease.

Fig. 1. Cluster analysis of integration of suboptimal health status, cardiovascular risk,
and endothelial dysfunction. The figure shows a graph obtained during cluster analysis,
allowing for classification into clusters after pre-processing the received data in
accordance with the average values in the whole population. *SumSHS: the total amount
of SHS score: 25. SI smoker index, BMI body mass index, SBP systolic blood pressures, DBP diastolic blood pressures, IEF index of endothelial function, IR index of reflection before the sample, IR2 index of reflection after the sample, IS stiffness index before the sample, IS2 stiffness index after the sample, TCH total cholesterol, GLU glucose

Cluster analysis showed a correlation between SHS score (including total index SHSQ-25
and sub-scales of the SHSQ-25), risk factors for cardiovascular system, and indicators
of endothelial dysfunction (p??0.001). Among the risk factors for cardiovascular diseases, the greatest distance
between the clusters 1, 2, 3 on one side and 4, 5 clusters on the other side were
observed according to age, body mass index, and blood pressure, indicating that the
association between stiffness of vascular wall with a number of traditional determinants
of cardiovascular diseases at suboptimal health stage.

The present study combined evaluation of suboptimal health status with the analysis
of the state of endothelial dysfunction, which allows us to identify the risk of developing
cardiovascular disease, which enables people early intervention in terms of predictive,
preventive, and personalized medicine 12], 13]. However, there are limitations of the present study: information of physical activity
habits, dietary profile, meals frequency, and sleep habits have not been assessed.
All these parameters are relevant with health status measurements 14], 15].