Association between sociodemographic status and cardiovascular risk factors burden in community populations: implication for reducing cardiovascular disease burden

The burden of cardiovascular disease (CVD) in China has been consistently increasing since 2006 [1]. CVD causes substantial health and economic burden in China [2, 3]. In 2016, nearly 13% of admission was due to CVD, and the cost for three main CVD (acute myocardial infarction, intracranial hemorrhage and cerebral infarction) was more than 100 billion RMB [1]. Nearly 40% of death was due to CVD in the Chinese adults [4]. Recognizing these burdens, the Chinese government has launched several national health-promotion plans and programs [5]. For example, in 2016, the Chinese government endorsed the blueprint of “Healthy China 2030”, which has made population health the ultimate goal of economic development and political reform. Two of the goals are to improve longevity and healthy life expectancy and to increase disease prevention, aiming at reaching a health standard on par with developed countries by 2030 [6]. To achieve these goals, reducing the CVD burden is imperative.

The burden of CVD can be reduced through effectively preventing and controlling cardiovascular (CV) risk factors [7]. Smoking, drinking, overweight/obesity, hypertension, dyslipidemia and diabetes mellitus are the most common and important CV risk factors. Epidemiologic studies have shown that there was a trend toward increasing the prevalence of CV risk factors in China. For example, the 2018 China Hypertension Survey shows that nearly 23.2% (244.5 million) of adults aged ≥ 18 years had hypertension [8], which was 5.2% higher than that in the 2002 survey [9]. The prevalence of diabetes mellitus increased from 10.9% to 2013 to 12.4% in 2018 [10], and obesity increased in an alarming rate, from 31.9% to 2007 to 37.2% in 2017 [11]. Several studies, that have reported the nationwide status of smoking [12], drinking [12], overweight/obesity [13, 14], hypertension [8, 15], dyslipidemia [16‐18] and diabetes mellitus [19, 20], uniformly show that the epidemiological characteristics of CV risk factors differed widely across different regions of China, which might be partly explained by the regional differences in sociodemographic status (SDS).

In recent four decades, Guangdong Province has experienced rapid economic, social, and cultural changes, that might have impacted the epidemiological characteristics of CV risk factors.

Enhancing our knowledge in these aspects is crucial for CVD prevention and management. However, there are no contemporary epidemiological data on the CV risk factors in Guangdong Province. From 2016 to 2020, Guangdong Province has participated in the China Patient-Centered Evaluative Assessment of Cardiac Events (PEACE) Million Persons Project, which is a government-funded, nationwide, and population-based CVD screening study [21, 22]. Leveraging this study, we aimed to (1) evaluate the contemporary CV risk factors burden in Guangdong Province, and (2) evaluate the association between SDS and CV risk factors burden.

Compared to the nationwide population of the China PEACE Million Persons Project [12, 13, 15, 16], the prevalence of smoking (20.0% vs. 17.2%), drinking (7.8% vs. 5.3%), overweight/obesity (53.5% vs. 48.9%), hypertension (44.7% vs. 39.9%) and dyslipidemia (33.8% vs. 18.6%) seemed to be numerically lower in Guangdong Province. These differences could be partly explained by the differences in SDS between Guangdong Province and other regions of China. Prior study suggests that in most provinces of China, the prevalence of CV risk factors were higher in urban than rural areas, which was probably due to higher levels of unhealthy lifestyles in rural residents [25]. Guangdong is one of the most developed provinces in China and participants in this study were from the most developed areas of Guangdong Province. It is thus probable that participants of the study had a relatively higher level of healthy lifestyles. Furthermore, people with well economic status are more likely to have regular health examination and seek medical services for health promotion [26]. In addition, people in developed areas are more likely to have high education attainment, which could facilitate them uptake health literacy. Indeed, in this study, we noticed that higher education attainment was associated with significantly lower odds of CV risk factors. Although having a lower prevalence of overweight/obesity, the prevalence of diabetes mellitus was numerically higher in Guangdong Province than the other two nationwide population-based studies (16.1% vs. 12.8% vs. 10.9%) [19, 20]. We are unsure the reasons. While these findings suggest a high burden of diabetes mellitus in Guangdong Province, and specific efforts are needed to reduce the burden. For example, public health promotion in terms of encouraging people to eat low-carbohydrate diet, do physical activity regularly, reduce sedentary time and decrease consumption of sugar-sweetened beverage could help to ease the burden of diabetes mellitus [10]. Overall, our results are consistent with prior nationwide population-based report that the burden of CV risk factors was lower in South China [12].

Among the six CV risk factors, overweight/obesity and hypertension are the two most common risk factors in the community populations of Guangdong Province. Given the high prevalence of these two risk factors, population-based cost-effective strategies are immediately needed. Some interventions have been demonstrated effective. For example, long-term modest salt reduction is associated with a significant reduction in blood pressure [27]. Unfortunately, one population-based survey showed that the average salt-intake for individual person was 7.6 g/day in Guangdong Province [28], which is higher than the World Health Organization recommendation (< 5 g/day). Labeling the adverse effects of high-salt intake in the container could be a cost-effective way to reduce salt in cooking. In addition, incentivizing the manufactures to use potassium chloride as a partial substitute for sodium chloride could have fundamental impacts on reducing salt-intake at the population level. We can also leverage the social media such as the WeChat or Weibo to advocate low salt diet, regular physical activity, and reduced energy-dense food consumption. Through these platforms, health knowledge can be disseminated rapidly and immensely. Furthermore, convenient apps such as the Apple Fitness Plus can help people do physical activity in a more scientific and effective way, and people can also use the apps to communicate with their counterparts, creating a positive feedback loop. Furthermore, algorithms derived from machine learning could be used to help better quantify the CV risk factors burden in these community populations. Taken together, we believe that these novel health-techs will be the solution to a lot of the cardiovascular challenges. Through combination of these health-techs with behavioral analysis, we can find solutions quicker and maintain the positive feedback loop between healthcare workers and the community populations.

We found that overweight/obesity often coexists with other risk factors, suggesting that overweight/obesity might play a central role during other CV risk factors development. Indeed, prior studies have demonstrated that overweight/obesity is significantly associated with elevated blood pressure [29], cholesterol and triglyceride [30] and blood glucose [31]. Therefore, preventing overweight/obesity development could concurrently help reduce the burden of hypertension, dyslipidemia and diabetes mellitus.

Even in people aged 35–44, nearly 60% had at least 1 CV risk factor, and the burden of CV risk factors increased with increasing age, underscoring the importance of preventing CV risk factors development from young age. As overweight/obesity and hypertension are the two most common risk factors in young adults, regular moderate-to-vigorous physical activity combined with low-carbohydrate and low-salt diet could be a cost-effective way to prevent these risk factors development.

In general, women had a lower burden of CV risk factors than men, which is consistent with prior findings in a nationwide population-based study [25], suggesting that specific efforts would be needed to mitigate the CV risk factors burden in men. There were some sex-differences in the prevalence of risk factors. Compared to men, women were more likely to have dyslipidemia while less likely to have other risk factors. Among the nationwide population of the China-PEACE Million Persons Project, women were less likely to have overweight/obesity [13] but more likely to have dyslipidemia [16]. A lower prevalence of diabetes mellitus in women was observed in the other nationwide population-based study [19]. In a national level, women were more likely to have hypertension [15], which was contrast to our current study. These findings demonstrate the heterogeneous features of CV risk factors burden by sex.

There are variations in the association between individual SES metric and the burden of CV risk factors, indicating the complex relationship between SES and cardiovascular health. Notably, the association between education attainment and the burden of CV risk factors was consistent. Higher education attainment was associated with significantly lower odds of CV risk factors. Similar trends were also observed in the nationwide population of China PEACE Million Persons Project [13, 15, 16], demonstrating the importance of education in mitigating the burden of CV risk factors and reinforcing the necessary to promote education at the population level. Indeed, prior report demonstrates that lower education attainment is the second modifiable risk factor for CVD in middle-income country like China [32]. Higher annual household income was associated with higher odds of drinking, overweight/obesity and dyslipidemia, which might be due to adverse effects of nutritional excess. Indeed, in the context of rapid economic and cultural change, nutritional transition in Guangdong Province has followed the patterns that developed countries have experienced in the past. For example, people in this region are in favor of eating refined grains, edible oils and animal-source foods which is accompanied by substantial cooking behavior changes (e.g., frying and broiling with cooking oil) [33], leading to overweight/obesity and dyslipidemia. The association between urban residence and CV risk factor varied, which might be due to differential changes in economy and culture between the urban and rural areas. These findings suggest that specific prevention strategies are needed in the rural and urban areas. After adjusting for covariates, occupation was not associated with CV risk factors, suggesting that occupation per se might not be an independent determine of CV risk factors burden. In light of the variations of the CV risk factors burden by SES, it is needed to allocate health resources in a targeted way. For example, to individuals with low education level, we can use cardiovascular health videos to educate them on how to maintain healthy lifestyle; to individuals with low annual household income, implementation of public fitness equipment is crucial which can facilitate them to participate in regular physical activity; and to individuals who live in the rural areas, improvement in accessibility to the high quality of healthcare is fundamentally important.

There are some limitations of the study. First, the current study did not use random sampling method to recruit participants because it was not possible with such rapid, large-scale recruitment. This limitation might lead to overrepresentation of women and prohibited estimation of weighted prevalence of CV risk factor in Guangdong Province. Future studies using stratified multistage random sampling method are needed to obtain a representative sample of the general Chinese population. Second, participants in the study were from developed areas of Guangdong Province. Due to the urban-rural disparities in CV risk factor burdens, it is possible that the current study underestimated the burden of CV risk factors in Guangdong Province. It is needed to randomly sample participants from rural and urban areas in the future. Third, data on other CV risk factors such as daily salt-intake and physical inactivity were not captured. This limitation could have prevented us to investigate the reasons for a high prevalence of hypertension and overweight/obesity in Guangdong Province, which should be investigated in the future. Fourth, CV risk factors such as smoking and drinking were determined based on self-report, which was subject to recall biases and/or social stigma. Quantitative analysis of lifestyle habits could be analyzed with the help of the tech apps which can track intake, and if anonymized at source this may help overcome limitations due to recall bias and stigma. In addition, we assessed smoking and drinking status qualitatively. Further studies are needed to assess cigarette smoking and alcohol drinking in a quantitative way, which would provide more detailed information regarding the burden of these two risk factors at the population level.