Modifiable risk factors in the Indonesian adult population
Tobacco smoking contributes to almost 50% of cardiovascular-related deaths in the Southeast Asian region [
23]. In the current study, 29.6% of adults were active smokers, and this proportion was higher than the global average [
24]. Althought a study by Yusuf et.al showed that among behavioral risk factors, tobacco smoking was the most strongly associated with the occurrence of CVDs [
25], our study indicated that 20% of participants with a prior CVDs diagnosis were still active smokers, The prevalence of smoking was extremely high in men (64.7% vs. 2.8% in women) and there was no significant change from 2013 in both sexes [
26]. A study by Marie Ng et.al showed an average of cigarette consumption in Indonesia was 11 sticks per day, which was lower than global average of 18 sticks per day [
27]. The distribution of tobacco smoking between men and women in the current study is commonly found in the Southeast-Asian populations but differs from the western population where the number of smoking women almost as high as in men [
24]. Despite of national efforts to reduce tobacco consumption, smoking remains a major risk factor for CVDs in Indonesia.
Many studies have shown that an unhealthy diet (high-risk food intake or inadequate fruit and vegetable consumption) is associated with an increased risk of cardiovascular events [
28]. We found that in Indonesia, a high proportion of participants consumed high-risk food and had inadequate fruit and vegetable consumption, independent of the presence of CVDs. This is in line with the result of other studies that found the majority of the population still consumes less fruit and vegetables than recommended by the standard [
29,
30].
There is a clear association between adequate physical activity with better cardiovascular health and diabetes in which lifestyle interventions based on physical activity are promoted for both primary and secondary care [
31]. However, our analyses demonstrated a significant difference in physical activity level between participants with and without CVDs, approximately 6 out of 10 participants with known CVDs diagnosis had a low physical activity level according to the WHO standard. Although the prevalence of an inadequate physical activity level was lower in participants without CVDs in our study, it was still much higher than other East and Southeast Asian countries [
32]. Several factors might influence the physical activity level. In Indonesia, rapid urbanisation, economic development, and technology advancement, particularly transportation creating an environment conducive to sedentary behavior and physical inactivity, might partly explain the situation.
Mental and emotional disorders were more prevalent in participants with a prior CVDs diagnosis and more common among women than men; our finding was in line with those of other studies [
33]. The underlying reason for the variation in the presence of mental and emotional disorders between sexes remains unclear. Associations of anxiety, stress, and depressive disorder with an increased risk of CVDs have been shown in healthy and pre-existing CVDs populations [
34]. Although not included in our analysis, disease risk perception is an important risk factor worth mentioning. According to studies from Indonesia, people who have a higher disease perception positively correlated with better cardiovascular health behavior and medication adherence for those who have already developed risk factors and have been diagnosed with CVDs [
35,
36]. Thus, understanding a person’s perception of a disease is essential for health professionals when planning and delivering prevention and treatment strategies. The high prevalence of mental and emotional disorders among participants in our study, especially in the manifested CVDs population, may suggest that improving knowledge and disease perception, creating awareness, and addressing mental problems among CVDs patients by health care services would be beneficial [
37].
Anthropometric measurements for body fat distribution, including BMI, WC, and WtHR, are good predictors of cardiovascular health and the risk of cardiovascular events [
38,
39]. Obese, a high WC, and a high WtHR were common in participants with a prior CVDs diagnosis and consistently high among women. Our findings agree with those of other studies [
40‐
42]. Complex hormonal and metabolic fluctuations in their life course combined with unhealthy lifestyles, including a low physical activity level and an unhealthy diet, are possible explanations for why women have a higher risk of anthropometric indices than men [
43].
The prevalence of major risk factors, namely hypertension, diabetes, and hyperlipidemia, in the current study, were higher than those in the previous Riskesdas in 2013 [
26]. Furthermore, excluding a low HDL cholesterol level, we found these risk factors significantly more prevalent in the prior CVDs group and in women. Our findings differed from the global pattern, in which the prevalence of hypertension, diabetes, and cholesterol were higher among men [
2]. Two methods of estimating hypertension and diabetes prevalence were used in the Riskesdas study, firstly, estimation of prevalence based on the participants’ self-reporting of physician diagnosis, secondly, with direct blood pressure and blood glucose level measurement during a house visit. A significant prevalence discrepancies between both methods where self-reported assessment shows lower estimates than direct measurements indicate a missed opportunity for diagnosis among this population.
The present study explored the co-occurrence of multiple CVDs risk factors (also known as risk factors clustering) in the Indonesian adult population. Our study demonstrated that the co-occurrence of multiple risk factors is highly prevalent. Approximately 1 out of 5 adults have at least four risk factors of CVDs, even higher in the manifested CVDs group and older group (> 55 years) and slightly higher in men. The risk factors clustering pattern in Indonesia seems comparable to other studies [
9,
44,
45]. Risk factors for CVDs are typically clustered in an individual due to the inter-correlation of risk factors with each other. Unhealthy lifestyles and behavior are known to be associated with increased risk of metabolic syndrome, including hypertension, dyslipidemia and diabetes which eventually increases the likelihood of developing CVDs.
In Indonesia, several initiatives have been implemented to reduce the burden of CVDs [
46]. Screening for NCD risk factors through the Posbindu, comprehensive training on screening and managing NCD risks for health professionals and health volunteers, implementing tobacco control measures, and strengthening the capacity of the Puskesmas for prevention and control are several examples of nationwide efforts to reduce the disease burden [
46]. Nevertheless, as the current study highlights, the prevalence of modifiable risk factors for CVDs remains high. A study conducted by Maharani and Tampubolon [
47] demonstrated that the high prevalence of modifiable risk factors for CVDs in Indonesia is due to unmet needs for care and is strongly correlated with socioeconomic factors. The Indonesian government introduced the National Healthcare Insurance program (
Jaminan Kesehatan Nasional or JKN) in 2014 to ensure the availability of medication for primary and secondary prevention and adequate access to quality health services, including CVDs care [
48].
Despite numerous efforts to reduce the burden of CVDs and their risk factors, limited analyses of these efforts have considered population heterogeneity [
49]. Future research and prevention strategies for CVDs in Southeast Asia, particularly Indonesia, should consider the broad range of risk factors, the heterogeneity of the population, and the co-occurrences of multiple risk factors.
Strengths and limitations of the study
To the best of our knowledge, this study is the first to investigate the estimated prevalence of modifiable risk factors in participants with and without CVDs using representative Indonesian national-level data. Furthermore, the large sample size provided sufficient power to calculate the prevalence of risk factors to represent national estimates. Several important limitations were identified, including the self-reporting of CVDs diagnosis and excluding peripheral artery disease, potentially leading to an underestimation of the prevalence of CVDs. A self-reported assessment, especially in behavioral risk factors, may introduce recall bias that possibly hinders our findings. As participants tend to overestimate exercise and underestimate food intake, our findings may thus be an underestimation of the already high prevalence of cardiovascular risk factors in this population. Future studies could include specific food and exercise recall forms to limit this bias.
Moreover, the smoking quantity was also not available from our data, thus preventing us from further analyzing the amount of tobacco consumption patterns. There was only a 77.7% response rate among the targeted participants for blood examination; this may have led to sampling bias which could affect the accuracy of the prevalence estimation. Furthermore, the study did not include other known risk factors, such as excessive alcohol consumption, household indoor air pollution, family history of CVDs, ethnicity, or perceived risk and awareness of the disease.