Characteristic | No. (Weighted %) |
---|---|
Age, mean (SE), y | 45.6 (15.9) |
Female | 10,911 (50.3) |
Married | 16,102 (76.9) |
Social risk factors | |
Low household incomea | 8,223 (38.6) |
Low level of educationb | 6,085 (24.0) |
Single livingc | 1,852 (8.0) |
Framingham risk factors (except age and sex) | |
Total cholesterol, mean (SE), mg/dL | 189.6 (35.7) |
High-density lipoprotein cholesterol, mean (SE), mg/dL | 51.2 (12.4) |
Has ever smoked | 7,076 (40.3) |
Has diabetes | 2,240 (9.5) |
Systolic blood pressure, mean (SE), mm Hg | 116.7 (15.8) |
Receives treatment for hypertension | 3,945 (15.5) |
Occurrence of a lifetime CVD eventd | |
Stroke | 420 (1.6) |
Myocardial infarction | 172 (0.7) |
Angina | 364 (1.4) |
Cumulative social risk scoree | |
0 | 8,671 (50.8) |
1 | 5,790 (31.0) |
2 | 3,688 (15.1) |
3 | 998 (3.1) |
Population-Weighted Characteristics of the Study Sample, Adults Aged ≥19 (n = 19,147) From the Korea National Health and Nutrition Examination Survey (KNHANES), 2013–2016
Abbreviation: CVD, cardiovascular disease.
a Participants were categorized into 4 quartiles of household income (upper, moderate, moderate-low, and low). Household income lower than the 50th percentile (ie, moderate-low and low) was categorized as low household income.
b KNHANES asked, “What is the highest qualification you obtained from school?” Response categories were college graduate, high school graduate, middle school graduate, and elementary school graduate. Middle school graduate and elementary school graduate were classified as low level of education.
c KNHANES asked, “How many people are cohabiting with you?” Response categories ranged from 0 to 9 persons. Respondents who reported zero people were classified as single living.
d KNHANES asked, “Have you ever been diagnosed with [stroke, myocardial infarction, or angina] by a physician?” Respondents who answered yes were categorized as having a lifetime occurrence.
e Possible range, 0–3: 0, no social risk factors reported; 1, 1 social risk factor reported; 2, 2 social risk factors reported; 3, 3 social risk factors reported.
Cardiovascular Disease | Unadjusted | Adjustedd |
---|---|---|
Stroke | ||
Framingham risk score | 1.81 (1.70–1.95) [<.001] | 1.42 (1.31–1.53) [<.001] |
Cumulative social risk score | 2.53 (2.25–2.84) [<.001] | 1.89 (1.64–2.17) [<.001] |
Myocardial infarction | ||
Framingham risk score | 1.66 (1.51–1.83) [<.001] | 1.37 (1.22–1.55) [<.001] |
Cumulative social risk score | 2.11 (1.79–2.49) [<.001] | 1.63 (1.31–2.01) [.002] |
Angina | ||
Framingham risk score | 1.88 (1.72–2.06) [<.001] | 1.56 (1.41–1.73) [<.001] |
Cumulative social risk score | 2.35 (2.08–2.66) [<.001] | 1.64 (1.42–1.89) [<.001] |
Table 2. Weighted Logistic Regression of Cardiovascular Disease on Framingham Risk Scorea and Cumulative Social Riskb, Adults Aged ≥19 (n = 19,147) From the Korea National Health and Nutrition Examination Survey, 2013–2016c
a Computed by using the algorithm described by D’Agostino et al (6). Components of the risk score are age, total cholesterol, high-density lipoprotein cholesterol, smoking status, diabetes status, systolic blood pressure, and whether or not the participant was treated for hypertension.
b Consistent with previous studies [14,15], we computed a cumulative social risk score (range, 0 to 3) by using 3 binary social risk factors: low household income (yes/no), low level of education (yes/no), and single-living status (yes/no).
c All values are relative risk (95% confidence interval) [P value].
d In the adjusted model, each cardiovascular disease was regressed on the Framingham risk score and cumulative social risk.
This activity is intended for cardiologists, neurologists, internists, and other clinicians caring for patients with or at risk for cardiovascular disease (CVD).
The goal of this activity is to describe the contribution of the cumulative social risk score (CSRS) (range 0-3; based on income, education, and single-living status) to CVD risk beyond the Framingham risk score (FRS) among South Korean adults using nationally representative data (Korea National Health and Nutrition Examination Survey [KNHANES]) from 19,147 adults age ≥ 19 years from 2013 to 2016.
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Introduction
The Framingham risk score (FRS) is widely used to predict cardiovascular disease (CVD), but it neglects to account for social
risk factors. Our study examined whether use of a cumulative social risk score in addition to the FRS improves prediction
of CVD among South Korean adults.
Methods
We used nationally representative data on 19,147 adults aged 19 or older from the Korea National Health and Nutrition Examination Survey 2013–2016. We computed a cumulative social risk score (range, 0–3) based on 3 social risk factors: low household income, low level of education, and single-living status. CVD outcomes were stroke, myocardial infarction, and angina. Weighted logistic regression examined the associations between cumulative social risk, FRS, and CVD. McFadden pseudo-R
2 and area under receiver operating characteristic curve (AUC) assessed model performance. We conducted mediation analyses
to quantify the association between cumulative social risk score and CVD outcomes that is not mediated by the FRS.
Results
A unit increase in social risk was associated with 89.4% higher risk of stroke diagnosis, controlling for the FRS (P < .001). The FRS explained 8.0% of stroke diagnosis (R
2) with fair discrimination (AUC = 0.728), and adding the cumulative social risk score enhanced R
2 and AUC by 2.4% and 0.039. In the association between cumulative social risk and stroke, the proportion not mediated by the
FRS was 65% (P < .001). We observed similar trends in myocardial infarction and angina, such that an increase in social risk was associated
with increased relative risk of disease and improved disease diagnosis, and a large proportion of the association was not
mediated by the FRS.
Conclusion
Controlling for the FRS, cumulative social risks predicted stroke, myocardial infarction, and angina among adults in South
Korea. Future research is needed to examine non-FRS mediators between cumulative social risk and CVD.
Cardiovascular disease (CVD) has been the leading cause of death in the past 20 years [1]. In 2016, ischemic heart disease and stroke accounted for a combined 26% (15.2 million) of global deaths [2]. To curb the incidence of CVD, a comprehensive understanding of CVD etiology is needed.
Epidemiological and biomedical research has made progress in understanding CVD etiology and the mechanisms through which determinants manifest as CVD. Among the better-known studies is the Framingham Heart Study, an ongoing longitudinal cohort study. Many known determinants of CVD, such as smoking, cholesterol, blood pressure, and physical activity, were first reported by the Framingham Heart Study [3–5]. The Framingham risk score (FRS) was developed to predict a person’s 10-year risk for CVD on the basis of demographic information, such as age and sex, and biobehavioral markers, such as cholesterol levels, smoking status, systolic blood pressure, and diabetes [6].
A limitation of the FRS is that it is based solely on individual-level factors. Hence, it does not sufficiently account for the role of social factors in determining CVD risk. For example, empirical data suggest that the FRS underestimates CVD mortality and morbidity among adults with low socioeconomic status in the United States [7] and Scotland [8]. A wealth of evidence corroborates the relationship between socioeconomic factors (household income, education, occupation, marital status, social support) on health, with some research even suggesting a causal influence [9,10]. Evidence on the social determinants of CVD has accumulated such that current scientific literature recommends including socioeconomic factors such as income, education, and social isolation in the FRS to enhance prediction of CVD [11,12]. Associations between socioeconomic status and CVD risk persist even after controlling for age, sex, smoking, hypertension, diabetes, physical activity, diet, cholesterol, and body weight [13]. In 2 recent studies, CVD researchers examined composite measures of cumulative social risk [14,15] by identifying indicators of social disadvantage that were consistently related to health outcomes, including household income, education, solitude (ie, whether one lives alone), and ethnicity [14,16]. In a nationally representative sample of US adults, cumulative social risk factors were associated with increased CVD mortality [15]. An important gap in this research, however, is that we do not know whether cumulative social risk predicts CVD independently of the individual-level biobehavioral factors measured in the FRS.
Most evidence on CVD risk is based on participants sampled in the Western Hemisphere, despite studies indicating that the prevalence of chronic disease is increasing rapidly across the world, in nations such as South Korea [17]. The economic growth in South Korea since the 1960s [18] has been accompanied by increases in inequalities in income and education. Concerns are emerging about health disparities in overall mortality and the prevalence of noncommunicable diseases [19–21].
The objective of our study was to examine the effect of cumulative social risk and the FRS on CVD incidence among adults in South Korea, with the following 3 aims. First, we investigated the association between the FRS and CVD incidence to assess the utility of the FRS among adults in South Korea. Second, we assessed the association between a cumulative social risk score (based on low household income, low level of education, and single-living status) and CVD incidence. Finally, we examined the association between the cumulative social risk score and CVD incidence, controlling for the FRS.
Summary