In this population-based study that was conducted in the framework of the TLGS, the association of the ideal CVH score and each of the seven CVH metrics with cIMT was evaluated. The participants in this study had a mean age of 30 years, and the prevalence of ideal CVH among them was 9.3%. A 1-point increase in the CVH score was associated with a decrease of 0.128 mm in cIMT and decreased the probability of presenting with a high cIMT (>95 percentile) by 32%. Each ideal glucose, ideal blood pressure, and ideal BMI had a significant inverse association with cIMT. Also, having ideal blood pressure and ideal BMI factors reduced the chances of developing high cIMT by 69% and 53%, respectively.
Cardiovascular health metrics introduced by the AHA in the past decade to predict cardiovascular events consist of seven metrics (3). Based on studies, an ideal CVH status correlates with better cardiovascular outcomes (5, 7). The low prevalence of ideal CVH is an important global concern, especially in the middle- and low-income countries (22). In our study, the prevalence of ideal CVH in a young adult Iranian population was 9.3%. The prevalence of the ideal CVH status varies among studies, depending on populations’ age and gender distribution and geographic variances (23). A systematic review of 88 studies reported that the prevalence of having five or more ideal CVH metrics was 19.6 % (95% CI: 15.2 % 23.9 %), and a poor CVH status was about twice in the elderly than in the young population (23). Previous studies have reported a low prevalence (0.3–4%) of ≥ 6 ideal CVH metrics in developing countries (5). Similarly, in the STEPwise study in Iran, although the prevalence of ideal CVH metrics among the population aged 20 to 65 years old reached about 7.2% in 2011, it again decreased to <4% in 2016 (24).
The results of our study supported earlier studies demonstrating an inverse relationship between ideal CVH and cIMT (13–16). This is important as cIMT is a subclinical marker of atherosclerosis and a factor predisposing people to cardiovascular diseases (5, 11). We found that a 1-point increase in the CVH score was associated with a decline of 0.128 mm in cIMT and decreased the probability of presenting with a high cIMT after adjustment for age and sex. Nevertheless, the association of ideal CVH with cIMT did not change after further adjustments for the family history of premature CVD and educational level. The age range of our participants was between 20 and 40 years old. To our knowledge, there is only one cross-sectional study on a similar population, in which five different cohorts of western populations were assessed, reporting that cIMT was 0.006 mm (95% CI: 0.012-0.003 mm) thinner for each additional ideal CVH score (14). Likewise, other studies investigating the association between ideal CVH score and cIMT in adult populations in Spain, USA, and Africa revealed that a 1-point increase in the ideal CVH score was associated with 0.011, 0.04, and 0.005 mm cIMT reduction, respectively (13, 15, 16). It is important to note that to our knowledge, there is only one longitudinal study conducted in China that evaluates the association between CVH metrics and cIMT. Wang et al.(25) after excluding individuals with elevated cIMT at the baseline, examined the association of CVH metrics with cIMT changes over approximately four years and showed that ideal CVH score were significantly and inversely related to the risk of developing subclinical atherosclerosis.
Ideal glucose, ideal blood pressure, and ideal BMI had a significant inverse association with cIMT. Similarly, Nonterah et al.(13) demonstrated an inverse association between the same ideal CVH metrics and cIMT in populations from four African countries. On the other hand, Oikonen et al. (14) indicated that the ideal status of each of blood pressure, BMI, cholesterol, and diet was independently and inversely associated with cIMT, whereas physical activity was directly associated with cIMT. According to these findings, differences in the weight of each of the seven metrics on cIMT should be considered when evaluating the effectiveness of the metrics.
The findings of this report are subjected to at least two limitations. First, it should be kept in mind that the observed inverse associations between ideal CVH metrics and cIMT were based on cross-sectional data, precluding the analysis of causal associations. The second limitation was that based on a previous study (16), the two groups of CVH were merged into one group due to sample size restrictions. As the main strength, this study is the first population-based report on the association of CVH metrics with cIMT in a young adult population in the MENA region. Also, various CVH metrics were measured by trained individuals instead of being based on self-reports.
In conclusion, in this population-based study on young adults, the prevalence of ideal CVH was 9.3 %. An inverse graded association was observed between ideal CVH score and cIMT, which also decreased and the probability of presenting a high cIMT by 32%. Moreover, cIMT was significantly and inversely associated with each ideal glucose, ideal blood pressure, and ideal BMI. It is suggested that future studies with larger sample sizes; investigating the relationship between ideal CVH metrics and cIMT and other surrogate markers of subclinical atherosclerosis; are needed in the MENA region. It is also necessary to conduct longitudinal studies to evaluate cIMT changes over time and assess its relationship with ideal CVH metrics, considering the weight of each of the seven CVH metrics on cIMT.