Epidemiology of CVD

Epidemiology

Epidemiological transition (Omran)

India, trend of death causes

Transition in different countries

Preston curve

Radeksz, Public domain, via Wikimedia Commons
ourworldindata.org

How to study cardiovascular epidemiology?

Ongoing pandemic

Thoughtful observations

Surveillance (official statistics)

Cohort studies

Case-control studies

Framingham Heart Study, 1948–now

Cohort study, ~5000 healthy inhabitants of Framingham 30-69 y.o.
Total population 28,000, of whom 10,000 are 30-69 y.o.

Detailed biennial examinations (including ECG, blood tests, physical)

HTN, EKG-LVH, cholesterol, smoking, body weight, gender, age, diabetes

(baldness, gray hair — no association found)

Smoking and education

(Dawber, Moore, and Mann 2015)

Framingham, 26 years

(Lerner and Kannel 1986)

Seven Countries Studies

Ancel Keys, physiologist from Minnesota

16 cohorts, ~12 000 participants 40-59 years (all men!)

Extensive diet information was collected at baseline in subsamples of generally 20 to 50 men in all 16 cohorts.
Duplicates of the amounts of foods as eaten at home during a week were weighed, prepared for shipping for central laboratory chemical analysis of fatty acids, nitrogen, and ash.

Risk factors are the same in all the countries

But their level is different

Lot of data on the diet (fish, saturated fat)

Seven Countries Study

Registry: MONICA

1978 Bethesda conference on declining CHD mortality: is it genuine?

Monitoring of CV incidence, mortality across the countries.

Cases registered and cases and deaths independently ajudicated.

Mortality is indeed declining.

Two thirds due to incidence and one third due to treatment (CFR).

Official mortality overestimates MONICA registry mortality.

(Tunstall-Pedoe et al. 1994)

Case-control study: INTERHEART (2004)

52 countries (incl. Russia), all continents

Cases — myocardial infarction

15152 cases, 14820 matched controls (other patients or attendants/relatives)

Potentially modifiable risk factors:

• Smoking, hypertension (self-reported), diabetes, (self-reported), waist/hip ratio (instead of BMI), dietary patterns, physical activity, alcohol, lipids, psychosocial factors

Cohort study PURE (2020) (high, mid, low income countries)

Yusuf et al. (2020)

NHANES (National Health and Nutrition Examination Survey)

Random (representative) sample of 5000 people across the country

Regular surveying (nutrition, health), physical exam, biological sampling

First surveys started in 1960s, from 1999 — continuous program

A lot of data are publicly available, other can be requested (eg. linkage with mortality)

https://www.cdc.gov/nchs/nhanes/index.htm

Research project of Institute of Health Metrics and Evaluation

Global Burden of Disease

DALY — disability adjusted life years, measure of healthy life span

YLL — years of life lost (quantity)

YLD — years of healthy life lost due to disability (quality)

Time discounting and age weighting (discarded)

DALY = YLL + YLD

DALY, YLL, YLD (details)

Global Burden of Disease

JACC 2022: https://www.jacc.org/global-burden-cvd-2022 

JACC 2019 (maps) https://www.jacc.org/doi/10.1016/j.jacc.2020.11.010 

GBD Compare: https://vizhub.healthdata.org/gbd-compare/

Sources: https://ghdx.healthdata.org/gbd-2019/data-input-sources

From knowledge to prevention

RCT: Women Health Initiative

Male sex as risk factor, estrogen as a causal link ((Lerner and Kannel 1986))

Women Health Initiative Study

16608 postmenopausal women aged 50-79 years with an intact uterus at baseline were recruited by 40 US clinical centers in 1993-1998.

Conclusions: Results from WHI indicate that the combined postmenopausal hormones CEE, 0.625 mg/d, plus MPA, 2.5 mg/d, should not be initiated or continued for the primary prevention of CHD. In addition, the substantial risks for cardiovascular disease and breast cancer must be weighed against the benefit for fracture in selecting from the available agents to prevent osteoporosis.

(Writing Group for the Women’s Health Initiative Investigators 2002)

Cholesterol reduction — is it important?

WOSCOPS trial (high risk men)

CVD mortality reduction

AFCAPS-TexCAPS trial (moderate risk men and women)

No mortality benefit shown (power?)

JUPITER (men and women with low cholesterol)

Primary point (combined) 0.77 vs. 1.36 (HR 0.56; 95% CI 0.46-0.69)

All-cause mortality 0.96 vs. 1.19 (HR 0.81; 95% CI 0.67-0.98)   

PREDIMED: case for health education

7447 participants (55 to 80 years of age, 57% women) 

high cardiovascular risk, but no cardiovascular disease

• Mediterranean diet supplemented with extra-virgin olive oil

• Mediterranean diet supplemented with mixed nuts

• control diet (advice to reduce dietary fat).

Participants received quarterly educational sessions and, depending on group assignment, free provision of extra-virgin olive oil, mixed nuts, or small nonfood gifts. 

(Estruch et al. 2018)

Burden of the proof (IHME project)

https://vizhub.healthdata.org/burden-of-proof/

Pharmacotherapy

• Aspirin

• Statins

• Antihypertensive

• Diet

• Exercise

What we treat: risk factor or risk?

Risk estimation 

Framingham score

ASVCD risk estimator (https://tools.acc.org/ascvd-risk-estimator-plus/)

SCORE risk (Europe), mortality

SCORE2 risk (Europe): high risk countries, morbidity + mortality (burden) 

Guidelines are based on risk (no direct evidence)

Polypill approach: PolyIran study

Cluster randomized trial (villages), 6838 participtants

Inclusion criteria: age > 50 years, living in rural area

Intervention: polypill (HCTZ 12.5mg + enalapril 5 mg + atorvastatin 20 mg + ASA 81 mg) or nothing.

Enalapril changed to valsartan if cough emerges.

Adherence 80.5%. 

8.8% vs. 5.9% MACEs during follow-up of (HR 0.66 95%  CI 0.55—0.80).

(Roshandel et al. 2019)

Summary

Risk factor concept (PAR)

Risk factors modification (incidence) + disease treatment (CFR) + secular trends

Risk factors are different in different countries, territories, groups

Risk factors and diseases are changing over time, so should interventions

RCTs should be performed when feasible (not all risk factors are causal)

Cultural iatrogenesis / health education

Assignment

Calculate prevalence of arterial hypertension in U.S. population based on NHANES physical exam data using the first BP measurement.

Is this an overestimation or underestimation and why?

Calculate it for ACC/AHA and ESC/ESH diagnostic criteria for HTN.

What are your thoughts about results?