The association between education and cardiovascular disease incidence is mediated by hypertension, diabetes, and body mass index

Dégano, Irene R.; Marrugat, Jaume; Grau, María; Salvador-González, Betlem; Ramos, Rafael; Zamora, Alberto; Martí, Ruth; Elosúa, Roberto

doi:10.1038/s41598-017-10775-3

Cited by 86 publications

(67 citation statements)

References 41 publications

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“…Evidence from higher income countries also supported that BMI mediates the association between education and the risk of cardiovascular diseases. 32…”

Section: Discussionmentioning

confidence: 99%

Socioeconomic Differentials in Hypertension based on JNC7 and ACC/AHA 2017 Guidelines Mediated by Body Mass Index: Evidence from Nepal Demographic and Health Survey

Rana

Ahmmad

Sen

et al. 2019

Preprint

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27Background: Unlike developed countries; higher socioeconomic status (SES, education, and 28 wealth) is associated with hypertension in low and middle-income countries (LMICs) with 29 limited evidence. We examined the associations between SES and hypertension in Nepal and 30 the extent to which these associations vary by sex and urbanity. The body mass index (BMI) 31 was examined as a secondary outcome and assessed as a potential mediator. , using a multistage stratified 34 sampling technique. Participants aged 15 years or older from selected households were 35 interviewed with an overall response rate of 97%. Main outcomes were hypertension and 36 normal blood pressure defined by the widely used Seventh Report of the Joint National 37 Committee (JNC 7), and the American College of Cardiology/American Heart Association 38 (ACC/AHA) 2017. 39Results: The prevalence of hypertension was higher in Nepalese men than women. The 40 likelihood of having hypertension was more than double for individuals in the highest versus 41 lowest wealth quintiles [men: OR 2.13, 95% CI 1.60-2.85); women: OR 2.54, 95% CI 2.00-42 3.24] and for individuals with the higher education versus no education [men: OR 2.38, 95% 43 CI 1.75-3.23; women: OR 1.63, 95% CI 1.18-2.25]. The associations between SES and 44 hypertension were different by sex and urbanity. These associations were mediated by BMI. 45 Conclusions: Higher SES was positively associated with the higher likelihood of having 46 hypertension in Nepal according to both JNC 7 and ACC/AHA 2017 guidelines. These47 associations were mediated by BMI, which may help to explain broader socioeconomic 48 differentials in CVD and related risk factors, particularly in terms of education and wealth. Our 49 study suggests that the mediating factor of BMI should be tackled to diminish the risk of CVD 50 in people with higher SES in LMICs. Introduction 56 57 Hypertension is a growing public health problem in low and middle-income countries 58 (LMICs) 1 with concurrent risks of cardiovascular and kidney diseases. 2 A review warned that 59 although about three-quarters of people with hypertension (639 million people) live in LMICs, 60 there is no improvement in awareness or control rates. 1 Hypertension is a major contributor to 61 death and disability in South Asian countries, including Nepal with a low level of control and 62 awareness. 3-6 The World Health Organization (WHO) implemented `STEP-wise approach to 63 surveillance' (STEPS) using nationally representative sample in 2008 and 2013 reported an 64 increasing trend of prevalence of hypertension among 15-69 years Nepalese population ranging 65 from 21.5% in 2008 to 26.0% in 2013. 7,8 Based on the recent Nepal Demographic and Health 66 Survey (NDHS) 2016, Kibria and colleagues reported that the estimated prevalence of 67 hypertension in Nepal using the widely used Seventh Report of the Joint National Committee 68 (JNC 7) guideline 9 was 21.2%, and the corresponding prevalence was 44.2% when using a 69 new hypertension guideline rec...

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“…Evidence from higher income countries also supported that BMI mediates the association between education and the risk of cardiovascular diseases. 32…”

Section: Discussionmentioning

confidence: 99%

Socioeconomic Differentials in Hypertension based on JNC7 and ACC/AHA 2017 Guidelines Mediated by Body Mass Index: Evidence from Nepal Demographic and Health Survey

Rana

Ahmmad

Sen

et al. 2019

Preprint

View full text Add to dashboard Cite

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“…A number of studies have used observational multivariable regression methods to support mediating roles of BMI, SBP and smoking in the pathway between education and CVD risk (7, 8, 37, 38), with consistent results obtained using various measures of education, including time spent in schooling and academic qualifications. In an analysis of Dutch individuals, Kershaw et al , attributed almost 27% of the association between education and CHD to be due to smoking, with 10% and 5% attributed to obesity and hypertension respectively (37).…”

Section: Discussionmentioning

confidence: 91%

“…Recent studies have suggested that socioeconomic risk factors such as education play a causal role in the aetiology of CVD (3-5). Education may prevent CVD, in part through its effects on modifiable risk factors (6-8), and understanding this relationship can be used to inform public health policy.…”

Section: Introductionmentioning

confidence: 99%

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What explains the effect of education on cardiovascular disease? Applying Mendelian randomization to identify the consequences of education inequality

Carter

Davies

Taylor

et al. 2018

Preprint

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Key PointsQuestionWhat is the role of body mass index, systolic blood pressure and smoking in mediating the effect of education on cardiovascular disease risk?FindingWe find consistent evidence that body mass index, systolic blood pressure and smoking mediate the effect of education, explaining up to 18%, 27% and 33% respectively. Including all three risk factors in a model together explains around 40% of the effect of education.MeaningIntervening on body mass index, systolic blood pressure and smoking would lead to reductions in cases of CVD attributable to lower levels of education. Over half of the effect of education on risk of cardiovascular disease is not mediated through these risk factors.ImportanceLower levels of education are causally related to higher cardiovascular risk, but the extent to which this is driven by modifiable risk factors also associated with education is unknown.ObjectiveTo investigate the role of body mass index, systolic blood pressure and smoking in explaining the effect of education on risk of cardiovascular disease outcomes.DesignMultivariable regression analysis of observational data and Mendelian randomization (MR) analysis of genetic data.SettingUK Biobank and international genome-wide association study consortia.ParticipantsPredominantly individuals of European ancestry.Main outcomes and measuresThe effects of education (per 1-standard deviation increase, equivalent to 3.6 years) on coronary heart disease, cardiovascular disease (all subtypes), myocardial infarction and stroke risk (all measured in odds ratio, OR), and the degree to which this is mediated through body mass index, systolic blood pressure and smoking.ResultsEach additional standard deviation of education associated with 13% lower risk of coronary heart disease (OR 0.87, 95% confidence interval [CI] 0.84 to 0.89) in observational analysis and 37% lower risk (OR 0.63, 95% CI 0.60 to 0.67) in Mendelian randomization analysis. As a proportion of the total risk reduction, body mass index mediated 15% (95% CI 13% to 17%) and 18% (95% CI 14% to 23%) in the observational and Mendelian randomization estimates, respectively. Corresponding estimates for systolic blood pressure were 11% (95% CI 9% to 13%) and 21% (95% CI 15% to 27%), and for smoking, 19% (15% to 22%) and 33% (95% CI 17% to 49%). All three risk factors combined mediated 42% (95% CI 36% to 48%) and 36% (95 % CI 16% to 63%) of the effect of education on coronary heart disease in observational and Mendelian randomization respectively. Similar results were obtained when investigating risk of stroke, myocardial infarction and all-cause cardiovascular disease.Conclusions and relevanceBMI, SBP and smoking mediate a substantial proportion of the protective effect of education on risk of cardiovascular outcomes and intervening on these would lead to reductions in cases of CVD attributable to lower levels of education. However, more than half of the protective effect of education remains unexplained and requires further investigation.

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“…The combination of education, professional status, and zip code average income was used to estimate financial status [6]. Education links to cardiovascular disease as a proxy for other risk factors have been studied [11,22]. Surveys were given to users to obtain their age, smoking status, height, weight, and waist circumference.…”

Section: Rq2: Multi-factorial Approach To Healthmentioning

confidence: 99%

Cross-Modal Health State Estimation

Nag

Pandey

Putzel

et al. 2018

Proceedings of the 26th ACM International Conference on Multimedia

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Individuals create and consume more diverse data about themselves today than any time in history. Sources of this data include wearable devices, images, social media, geo-spatial information and more. A tremendous opportunity rests within cross-modal data analysis that leverages existing domain knowledge methods to understand and guide human health. Especially in chronic diseases, current medical practice uses a combination of sparse hospital based biological metrics (blood tests, expensive imaging, etc.) to understand the evolving health status of an individual. Future health systems must integrate data created at the individual level to better understand health status perpetually, especially in a cybernetic framework. In this work we fuse multiple user created and open source data streams along with established biomedical domain knowledge to give two types of quantitative state estimates of cardiovascular health. First, we use wearable devices to calculate cardiorespiratory fitness (CRF), a known quantitative leading predictor of heart disease which is not routinely collected in clinical settings. Second, we estimate inherent genetic traits, living environmental risks, circadian rhythm, and biological metrics from a diverse dataset. Our experimental results on 24 subjects demonstrate how multi-modal data can provide personalized health insight. Understanding the dynamic nature of health status will pave the way for better health based recommendation engines, better clinical decision making and positive lifestyle changes.

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The association between education and cardiovascular disease incidence is mediated by hypertension, diabetes, and body mass index

Cited by 86 publications

References 41 publications

Socioeconomic Differentials in Hypertension based on JNC7 and ACC/AHA 2017 Guidelines Mediated by Body Mass Index: Evidence from Nepal Demographic and Health Survey

Socioeconomic Differentials in Hypertension based on JNC7 and ACC/AHA 2017 Guidelines Mediated by Body Mass Index: Evidence from Nepal Demographic and Health Survey

What explains the effect of education on cardiovascular disease? Applying Mendelian randomization to identify the consequences of education inequality

Cross-Modal Health State Estimation

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