{"id":2093,"date":"2026-10-08T11:48:09","date_gmt":"2026-10-08T11:48:09","guid":{"rendered":"https:\/\/plantbasedrunners.com\/vegan-blog\/?p=2093"},"modified":"2026-10-09T09:03:42","modified_gmt":"2026-10-09T09:03:42","slug":"2093","status":"publish","type":"post","link":"https:\/\/plantbasedrunners.com\/vegan-blog\/2026\/10\/08\/2093\/","title":{"rendered":"Framingham to Agatston Score: The Evolution of Individual Cardiovascular Risk Assessment"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\"><strong>Individual Cardiovascular Risk: From Framingham to the Agatston Score<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>From population evidence to the cardiovascular profile of the individual<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Cardiovascular disease is often discussed using population statistics.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">We hear that a particular dietary pattern is associated with lower cardiovascular risk, that a blood marker is associated with heart disease, or that a particular lifestyle is generally considered &#8220;healthy&#8221;.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Those statistics are useful. In fact, they are the foundation of evidence-based prevention.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But an important question can become lost when we talk about populations:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What does the evidence tell us about the individual?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Cardiovascular disease does not happen to an average population.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It happens to individual human beings, each with a particular combination of age, blood pressure, lipoproteins, glucose metabolism, physical activity, smoking history, body composition, genetics, family history, kidney function and other risk factors.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That is one reason the history of the Framingham Heart Study is so important.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The study began in Framingham, Massachusetts, in 1948. Its purpose was to investigate prospectively the characteristics associated with cardiovascular disease. Rather than examining people only after disease had developed, researchers followed participants over time and repeatedly measured characteristics that might be associated with subsequent cardiovascular events. Framingham Heart Study+1<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The significance of this approach was profound.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It helped establish the modern concept of cardiovascular &#8220;risk factors&#8221; and demonstrated that cardiovascular disease could not be adequately understood as the consequence of a single variable. High blood pressure, cholesterol, smoking, obesity, diabetes and physical inactivity, among other characteristics, emerged as important components of cardiovascular risk. Framingham Heart Study+1<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But there is an important distinction.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Framingham did not produce a perfect measurement of an individual&#8217;s future.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It established relationships between characteristics measured in populations and subsequent disease. Those observations could then be used to construct statistical models that estimate the probability of future cardiovascular events in people with particular combinations of characteristics.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That distinction remains fundamental to cardiovascular prevention today.<br><br><strong>The hierarchy of evidence<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A useful way to understand cardiovascular research is to recognise that different forms of evidence answer different questions.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Population studies tell us what tends to happen; risk models quantify that evidence; individual measurements tell us which characteristics a particular person has; longitudinal observation tells us how those characteristics change; and imaging can sometimes provide evidence of subclinical disease. The challenge is to integrate these layers without confusing one type of evidence for another.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A simplified framework might look like this:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Population epidemiology<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u2193<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Risk prediction<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u2193<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Biomarkers<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u2193<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Subclinical disease and imaging<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u2193<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Clinical outcomes<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u2193<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Randomised intervention evidence<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">These categories overlap, but they should not be confused.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>From risk factors to risk prediction<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A person can have a number of characteristics that influence cardiovascular risk:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>elevated blood pressure<\/li>\n\n\n\n<li>elevated LDL cholesterol or other atherogenic lipoproteins<\/li>\n\n\n\n<li>smoking<\/li>\n\n\n\n<li>diabetes<\/li>\n\n\n\n<li>excess adiposity<\/li>\n\n\n\n<li>low physical activity<\/li>\n\n\n\n<li>advancing age<\/li>\n\n\n\n<li>impaired kidney function<\/li>\n\n\n\n<li>genetic susceptibility<\/li>\n\n\n\n<li>a family history of premature cardiovascular disease<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">These factors do not operate in isolation.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A person&#8217;s overall cardiovascular risk emerges from the combination of multiple characteristics, accumulated over time.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is why asking whether a single food, supplement, exercise programme or lifestyle practice is simply &#8220;healthy&#8221; can sometimes be an inadequate way of thinking about prevention.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A more useful question is:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What does the total cardiovascular risk profile of this individual look like?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Framingham helped establish the scientific basis for asking that question quantitatively.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Its risk functions combine multiple characteristics to estimate the probability of specified cardiovascular outcomes over defined periods. Importantly, there is not one universal &#8220;Framingham risk&#8221;. Different models predict different outcomes, populations and time horizons. The Framingham Heart Study itself emphasises choosing a risk function according to the cardiovascular outcome, population, time horizon and available risk factors.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For example, the Framingham 10-year general cardiovascular disease model applies to individuals aged 30\u201374 who were free of cardiovascular disease at baseline and incorporates age, diabetes, smoking, systolic blood pressure, antihypertensive treatment, total cholesterol and HDL cholesterol, with BMI available in a simpler model. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The Framingham 30-year model extends the time horizon considerably. It was developed for individuals aged 20\u201359 who were free of cardiovascular disease and cancer at baseline and used factors including age, sex, systolic blood pressure, antihypertensive treatment, smoking, diabetes, total cholesterol, HDL cholesterol and BMI. The underlying follow-up extended to a maximum of 35 years.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The important conceptual development was therefore not simply the discovery of individual risk factors. &#8211; Framingham Heart Study<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It was the demonstration that <strong>multiple characteristics could be combined into a statistical estimate of future risk<\/strong>.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>A risk score is not the same as disease<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This distinction is important.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A risk calculator estimates probability.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A biomarker measures a biological characteristic.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">An imaging test can provide evidence of a structural or pathological process.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A clinical event is an outcome.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">These are related, but they are not interchangeable.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A person can have a relatively low estimated short-term risk while already having evidence of subclinical atherosclerosis.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Another person can have a relatively high estimated lifetime risk without currently having detectable coronary calcification.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A third person can have an elevated LDL-C or ApoB without having experienced a cardiovascular event.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The purpose of risk assessment is therefore not to reduce the individual to a single number.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is to assemble the most useful available information into a clinically meaningful picture.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>From Framingham to contemporary risk prediction<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Framingham was foundational, but cardiovascular risk prediction has continued to evolve.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Contemporary populations differ from the populations in which many earlier risk equations were developed. Medical treatment has changed. Smoking prevalence has changed. Blood pressure and lipid management have changed. Population demographics have changed.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Risk prediction therefore has to be periodically recalibrated and validated.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The 2026 ACC\/AHA guideline on dyslipidemia represents an important stage in this evolution. For primary prevention, it recommends the American Heart Association <strong>PREVENT-ASCVD equations<\/strong> rather than the older Pooled Cohort Equations for adults aged 30\u201379 without known ASCVD or subclinical atherosclerosis and with LDL-C between 70 and 189 mg\/dL. The guideline recommends using PREVENT to estimate 10-year risk in adults aged 30\u201379 and 30-year risk in adults aged 30\u201359. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">PREVENT is itself an illustration of the same underlying philosophy that Framingham helped establish.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The model uses multiple characteristics rather than attempting to predict cardiovascular risk from one measurement.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It also incorporates more contemporary information, including kidney function and statin use, with optional variables such as HbA1c, urinary albumin-to-creatinine ratio and social deprivation measures in appropriate applications. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The historical progression is therefore important:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Framingham demonstrated the value of prospective risk-factor measurement.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Subsequent risk equations formalised multivariable prediction.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Contemporary models such as PREVENT attempt to improve calibration using newer and more diverse populations and additional clinically relevant information.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The philosophy has remained remarkably consistent even as the models have changed.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Risk is not merely a number. It is a trajectory.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Cardiovascular disease is generally not an event that appears from nowhere.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Atherosclerosis develops over years and decades, while many of the characteristics associated with cardiovascular disease also change over time.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Blood pressure can change.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Body composition can change.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Lipoprotein concentrations can change.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Glucose regulation can change.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Physical fitness can change.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Smoking status can change.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Diet can change.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Medication can change.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Kidney function can change.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Consequently, an individual&#8217;s cardiovascular risk profile can change as well.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This makes longitudinal observation particularly valuable.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A measurement today tells us something about the present.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Repeated measurements can tell us something about direction.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But there is an important qualification:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>a change in a risk marker is not automatically equivalent to a change in clinical-event risk.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If LDL-C falls, we can say that LDL-C has fallen.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If blood pressure falls, we can say that blood pressure has fallen.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Whether that change translates into fewer heart attacks or strokes depends on the strength of evidence connecting the intervention and the change in the marker to clinical outcomes.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This distinction prevents a common error in personalised health reasoning: assuming that every favourable-looking biomarker change is itself proof of improved long-term cardiovascular outcomes.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The value of longitudinal measurement is therefore not that it provides certainty.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It provides additional information.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Population evidence does not become irrelevant when we individualise it<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">There is a misconception that individualised health requires rejecting population research.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is actually the opposite.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Population research provides the foundation for individual assessment.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Without large-scale epidemiological studies, randomised trials and other forms of clinical research, we would have far less understanding of the relationship between blood pressure, atherogenic lipoproteins, smoking, diabetes, physical activity, diet and cardiovascular outcomes.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The individual exists within that evidence base.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A person&#8217;s measurements can be interpreted using knowledge derived from large numbers of people.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This creates a bridge between population evidence and personal health.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Population research asks:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What tends to happen to people with particular characteristics or exposures?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Individual assessment asks:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>How do those characteristics appear in this particular person?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Longitudinal assessment asks:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>How are those characteristics changing over time?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">These questions complement one another.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Individualisation should therefore not mean ignoring population evidence.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It should mean applying population evidence intelligently to an individual.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>The Framingham contribution: cardiovascular disease is multifactorial<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This multifactorial perspective is particularly important when discussing nutrition.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is tempting to search for a single cause.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Perhaps it is saturated fat.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Perhaps it is sugar.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Perhaps it is meat.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Perhaps it is carbohydrates.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Perhaps it is obesity.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Perhaps it is inflammation.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Perhaps it is cholesterol.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But cardiovascular disease is not adequately explained by one simplistic variable.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Consider two people of the same age.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">One has elevated blood pressure, elevated LDL-C and ApoB, excess visceral adiposity, impaired glucose regulation, low physical activity and a strong family history of premature cardiovascular disease.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The other has normal blood pressure, favourable lipoprotein levels, good cardiorespiratory fitness, normal glucose regulation, no smoking history and no significant family history.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The two individuals have different cardiovascular risk profiles.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It would therefore be inappropriate to assume that they are interchangeable simply because they eat the same food.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This does not mean that the health effects of a food are completely individual.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Population evidence still matters.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It means that <strong>the consequences of a dietary exposure occur within a broader physiological context.<\/strong><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Risk factor, risk marker and cause are not the same thing<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This distinction is especially important when interpreting biomarkers.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A characteristic can be:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>associated with cardiovascular disease;<\/li>\n\n\n\n<li>predictive of cardiovascular events;<\/li>\n\n\n\n<li>biologically related to disease;<\/li>\n\n\n\n<li>causally involved in disease;<\/li>\n\n\n\n<li>or useful for identifying people who may benefit from an intervention.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">These are not necessarily identical propositions.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For example, LDL-containing lipoproteins occupy a particularly important position because evidence from genetics, epidemiology, mechanistic biology and randomised trials supports a causal role for atherogenic lipoproteins in atherosclerotic cardiovascular disease.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Other biomarkers may be excellent predictors without necessarily functioning as direct causal targets.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Still others may provide information about residual risk without being readily modifiable themselves.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This distinction matters because personalised medicine should not become synonymous with simply measuring more variables.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The question is not:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&#8220;What can we measure?&#8221;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&#8220;What can we measure that meaningfully improves risk assessment, diagnosis, prognosis or management?&#8221;<\/strong><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>The importance of atherogenic lipoproteins<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Modern cardiovascular medicine has increasingly moved beyond treating &#8220;cholesterol&#8221; as a single measurement.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">LDL-C remains a central clinical measure, but atherosclerosis is fundamentally related to exposure to atherogenic lipoprotein particles.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Apolipoprotein B can provide additional information about the number of circulating atherogenic particles, particularly in circumstances where LDL-C may not fully represent the burden of atherogenic lipoproteins.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The 2026 ACC\/AHA dyslipidemia guideline therefore recommends selective ApoB measurement to improve risk assessment and guide treatment, particularly in people with elevated triglycerides, diabetes or low achieved LDL-C.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The guideline also recommends that <strong>Lp(a) be measured at least once in adulthood<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Lp(a) is substantially genetically determined and is relatively resistant to lifestyle modification. Its importance is therefore somewhat different from a biomarker such as triglycerides or blood pressure.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">An elevated Lp(a) concentration can reveal inherited cardiovascular risk that may not be apparent from the conventional lipid profile.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The 2026 guideline considers Lp(a) of at least 125 nmol\/L (50 mg\/dL) a risk-enhancing factor and recommends more intensive management of modifiable cardiovascular risk factors in people with elevated Lp(a).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This illustrates an important principle:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>individualised cardiovascular assessment is not simply about measuring how an individual responds to lifestyle. It is also about identifying inherited and otherwise non-obvious sources of risk.<\/strong><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Cumulative exposure matters<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Another important development in cardiovascular thinking is the recognition that atherosclerotic risk is related not simply to an individual&#8217;s current lipid concentration, but to exposure over time.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Atherosclerosis is a life-course process.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">An individual with moderately elevated atherogenic lipoproteins for several decades has a different biological history from someone who has only recently developed the same concentration.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is one reason the 2026 guideline places greater emphasis on earlier management of dyslipidemia and reducing prolonged exposure to atherogenic lipoproteins. Pprofessional.heart.org<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This also changes how the idea of a personal baseline should be understood.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A baseline is not necessarily the beginning of the individual&#8217;s cardiovascular history.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is simply the point at which measurement begins.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The most useful question may therefore be:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What does this person&#8217;s cardiovascular profile look like now, and what can we infer about the trajectory that brought them here?<\/strong><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Animal foods are not a single exposure<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This distinction is particularly important when discussing nutrition.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">&#8220;Animal products&#8221; encompasses an enormous range of foods.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Fish is not nutritionally identical to processed meat.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Eggs, yoghurt, cheese, poultry, red meat and processed meat differ in their nutrient composition, degree of processing and typical dietary context.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The cardiovascular implications of a food also depend partly on what it replaces.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A dietary change that increases one food while displacing another is not equivalent to simply adding that food to the existing diet.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Therefore, a serious discussion of animal-derived foods needs to consider:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>the specific food;<\/li>\n\n\n\n<li>quantity and frequency;<\/li>\n\n\n\n<li>degree of processing;<\/li>\n\n\n\n<li>the food being displaced;<\/li>\n\n\n\n<li>total dietary pattern;<\/li>\n\n\n\n<li>fibre intake;<\/li>\n\n\n\n<li>saturated and unsaturated fat;<\/li>\n\n\n\n<li>sodium intake;<\/li>\n\n\n\n<li>total energy intake;<\/li>\n\n\n\n<li>body weight and body composition;<\/li>\n\n\n\n<li>physical activity;<\/li>\n\n\n\n<li>metabolic health;<\/li>\n\n\n\n<li>lipoprotein response;<\/li>\n\n\n\n<li>blood pressure;<\/li>\n\n\n\n<li>and the individual&#8217;s pre-existing cardiovascular risk.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">This does not mean that population-level dietary evidence should be discarded.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It means that <strong>dietary exposure and individual cardiovascular risk should be considered together.<\/strong><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Individual response does not override outcome evidence<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is an important safeguard against an overly personalised interpretation of nutrition.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Suppose two people consume the same dietary pattern.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">One experiences a substantial increase in LDL-C and ApoB.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The other experiences little change.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That tells us that their physiological responses differ.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It does not automatically tell us that the dietary pattern is harmful for the first person and harmless for the second.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Similarly, an apparently favourable short-term biomarker response does not prove that a dietary pattern is optimal for long-term cardiovascular outcomes.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Population evidence remains necessary because clinical outcomes cannot usually be inferred perfectly from a handful of biomarkers measured over a short period.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The most defensible approach is therefore neither:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&#8220;Population averages tell us everything about the individual.&#8221;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">nor:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&#8220;My biomarkers are favourable, so population evidence does not apply to me.&#8221;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The stronger position is:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Population evidence establishes the expected effects and risks; individual assessment helps determine how those considerations apply to a particular person.<\/strong><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>From statistical risk prediction to imaging<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This brings us to one of the most interesting developments in individual cardiovascular assessment:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>coronary artery calcium scoring.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In 1990, Arthur S. Agatston, Warren Janowitz and colleagues published their landmark paper, <em>Quantification of Coronary Artery Calcium Using Ultrafast Computed Tomography<\/em>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The study examined 584 subjects, including 109 with clinical coronary artery disease and 475 without it. Ultrafast CT was used to detect and quantify coronary calcium according to the number, area and density of calcified lesions. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The work established the basis of what became known as the <strong>Agatston Score<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The conceptual significance is different from that of a conventional risk calculator.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A risk calculator uses characteristics such as age, blood pressure, smoking and lipid measurements to estimate future probability.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A coronary calcium scan provides imaging evidence that calcification is actually present within the coronary arteries.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In simplified terms:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Risk models estimate probability from measured characteristics.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>CAC provides direct imaging evidence of coronary calcification.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Neither is a complete measurement of cardiovascular health.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>CAC is not the same thing as total atherosclerosis<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The distinction is important.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Coronary artery calcium is a marker of calcified coronary plaque.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is not a complete measurement of all coronary plaque.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It does not detect every form of atherosclerosis.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It does not directly measure plaque vulnerability.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">And it does not measure cardiovascular disease outside the coronary arteries.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A CAC score is therefore best understood as a <strong>specific anatomical risk marker<\/strong>, not as a universal measure of cardiovascular health.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Nevertheless, it can add information that is not contained in a conventional risk-factor calculation.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That is why CAC has become an important tool for selected individuals in whom the treatment decision remains uncertain.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Zero is not the same thing as no risk<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">One of the most interesting features of CAC scoring is the significance of a score of zero.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The original Agatston work demonstrated a strong relationship between calcium burden and clinical coronary artery disease in the study population. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Subsequent prospective studies have helped establish the prognostic importance of CAC in asymptomatic populations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For example, the Multi-Ethnic Study of Atherosclerosis demonstrated that individuals with CAC=0 had very low event rates over the follow-up period studied, while even minimal detectable CAC was associated with higher risk. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But CAC=0 should never be interpreted as:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&#8220;I have no cardiovascular risk.&#8221;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A calcium score measures calcified coronary plaque.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It does not eliminate other risk factors.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Someone can have CAC=0 and still have elevated LDL-C, ApoB, Lp(a), hypertension, diabetes, smoking exposure or a strong family history of premature cardiovascular disease.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The correct interpretation is therefore:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>CAC=0 is a powerful risk modifier, not a declaration of cardiovascular health.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This distinction is reflected in contemporary guidance.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The 2026 ACC\/AHA guideline recommends selective CAC assessment to improve risk classification in appropriate adults, with both the absolute CAC score and its standardised percentile providing prognostic information. Pprofessional.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Framingham and Agatston represent different kinds of evidence<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is worth being precise here.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The Framingham Heart Study is fundamentally a <strong>longitudinal epidemiological cohort<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Its strength lies in following people over time and identifying relationships between characteristics and subsequent outcomes.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The Agatston method is fundamentally an <strong>imaging methodology<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Its value lies in providing a reproducible way to quantify coronary artery calcium.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Neither replaces the other.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">And neither is sufficient by itself to provide a complete assessment of an individual.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instead, they illustrate two complementary ideas:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Risk can be estimated from multiple characteristics.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">and:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Some aspects of disease-related anatomy can be measured directly.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Modern cardiovascular prevention combines these forms of information rather than treating them as competing philosophies.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Building an individual cardiovascular picture<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A useful cardiovascular assessment can therefore contain several layers.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>History<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Age<\/li>\n\n\n\n<li>Family history<\/li>\n\n\n\n<li>Smoking<\/li>\n\n\n\n<li>Physical activity<\/li>\n\n\n\n<li>Dietary pattern<\/li>\n\n\n\n<li>Previous medical conditions<\/li>\n\n\n\n<li>Medication history<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Physical measurements<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Blood pressure<\/li>\n\n\n\n<li>Weight<\/li>\n\n\n\n<li>Waist circumference<\/li>\n\n\n\n<li>Body composition where clinically useful<\/li>\n\n\n\n<li>Cardiorespiratory fitness<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Laboratory measurements<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>LDL-C<\/li>\n\n\n\n<li>HDL-C<\/li>\n\n\n\n<li>Triglycerides<\/li>\n\n\n\n<li>Non-HDL-C<\/li>\n\n\n\n<li>ApoB where appropriate<\/li>\n\n\n\n<li>Lp(a)<\/li>\n\n\n\n<li>Glucose and\/or HbA1c<\/li>\n\n\n\n<li>Kidney function and other clinically relevant measures<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Risk estimation<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">An appropriate, validated risk model for the person&#8217;s age, clinical circumstances, outcome of interest and time horizon.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For contemporary primary prevention, this increasingly means PREVENT-ASCVD rather than relying on older Framingham or Pooled Cohort equations. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Imaging where appropriate<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Coronary artery calcium assessment can provide additional information when risk classification or treatment decisions remain uncertain.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The important word is <strong>appropriate<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">More information is not automatically better information.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A test is valuable when its result is sufficiently reliable and likely to change understanding or management.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>The individual baseline<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This brings us back to the concept of a personal baseline.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Imagine establishing a cardiovascular baseline consisting of appropriate measurements and relevant history.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That baseline provides a starting point.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Lifestyle interventions can then be considered.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Selected measurements can subsequently be repeated when there is a clinical reason to do so.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The resulting information may show improvement, deterioration, stability or a mixed picture.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But interpretation still requires context.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A change in LDL-C is not the same thing as a change in CAC.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A change in HbA1c is not the same thing as a change in myocardial infarction risk.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A change in body weight is not necessarily equivalent to a change in cardiovascular risk.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">And an improved risk score does not prove that a particular intervention caused the improvement.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The purpose of longitudinal measurement is therefore not to create the illusion of perfect personal experimentation.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is to obtain better information than would otherwise be available.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Risk factors are not destiny<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Another important principle is that a risk factor is not the same thing as an inevitable outcome.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Having elevated blood pressure does not mean that someone will definitely have a heart attack.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Having elevated LDL-C does not make a cardiovascular event inevitable.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Having a family history does not mean that the same outcome must occur.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Likewise, having favourable measurements today does not guarantee lifelong cardiovascular health.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Risk is probabilistic.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The purpose of identifying risk factors is to understand where opportunities for prevention exist.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This prevents two opposite mistakes.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The first is fatalism:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&#8220;My family has heart disease, so there is nothing I can do.&#8221;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The second is false reassurance:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&#8220;I look fit and feel healthy, therefore I have no cardiovascular risk.&#8221;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Neither conclusion follows from the evidence.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Appearance is not a cardiovascular risk assessment<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is particularly relevant in the age of social media.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Someone can look extremely fit.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Someone can be thin.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Someone can run marathons.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Someone can have substantial muscular development.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">These characteristics may indicate good physical fitness or favourable aspects of health.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But appearance does not directly measure LDL-C, ApoB, Lp(a), blood pressure, glucose regulation or coronary calcium.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Conversely, someone who does not look like a stereotypical athlete is not automatically metabolically unhealthy.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Fitness and body composition matter.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But they are not substitutes for cardiovascular assessment.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Measurement adds another layer of information.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>The danger of one-size-fits-all nutrition<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is why nutritional discussions require some care.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A statement such as:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&#8220;Everyone should eat exactly X grams of Y.&#8221;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">may be attractive because it is simple.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But human beings differ in age, genetics, metabolic health, physical activity, body composition, medical history and cardiovascular risk.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">They also differ in dietary context.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">An evidence-informed approach can therefore begin with population-level dietary evidence while still asking what happens in the individual.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But individualisation should not mean abandoning evidence-based dietary recommendations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It means adding relevant individual information to the evidence base.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What does &#8220;how much is too much?&#8221; actually mean?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This leads to a difficult but important question:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>How much of a potentially harmful dietary exposure is too much for a particular individual?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">There is no universal answer that can be extracted from Framingham alone.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Framingham was not designed to establish a personal threshold for consumption of meat, dairy, eggs or other animal foods.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The Agatston Score cannot tell us how many servings of those foods someone should consume.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A CAC score does not translate directly into a dietary prescription.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">These studies answer different questions.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But together with broader nutritional research, clinical trials, lipid measurements, metabolic markers, blood pressure, physical activity and\u2014where appropriate\u2014coronary calcium, they can contribute to a much richer framework.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Rather than asking only whether someone has consumed an arbitrary amount of a particular food, we can ask:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>What does the population-level evidence show?<\/li>\n\n\n\n<li>What is the individual&#8217;s overall cardiovascular risk?<\/li>\n\n\n\n<li>What dietary pattern are they following?<\/li>\n\n\n\n<li>What food is being replaced by the exposure?<\/li>\n\n\n\n<li>What are the individual&#8217;s measurable responses?<\/li>\n\n\n\n<li>What other risk factors are present?<\/li>\n\n\n\n<li>What does the longitudinal trajectory look like?<\/li>\n\n\n\n<li>Is there evidence of established or subclinical disease?<\/li>\n\n\n\n<li>Would additional testing actually change management?<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">These are harder questions.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But they are also closer to the complexity of human cardiovascular disease.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>The purpose of measurement is better decision-making<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Measurement itself is not the objective.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The objective is prevention.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If an individual has elevated blood pressure, that may create an opportunity for intervention.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If LDL-C or ApoB is elevated, that may create another.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If smoking is present, cessation can be highly consequential.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If physical activity is inadequate, increasing activity may be appropriate.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If excess adiposity or impaired metabolic health is present, nutrition, exercise, sleep and other interventions may become relevant.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If Lp(a) is elevated, it may change the interpretation of overall risk and increase the importance of controlling other modifiable risk factors. Pprofessional.heart.org+1<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If CAC is present, it may provide additional information that changes how overall risk is understood.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The purpose of measurement is therefore not to collect numbers for their own sake.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>The purpose of measurement is to improve the decision.<\/strong><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>More data is not automatically better data<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is an important limitation of the personalised-health concept.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is tempting to assume that the more measurements we collect, the more accurately we understand the individual.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That is not necessarily true.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A test is useful when:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>it measures something sufficiently valid and reliable;<\/li>\n\n\n\n<li>the result can be interpreted meaningfully;<\/li>\n\n\n\n<li>the result provides information beyond what is already known;<\/li>\n\n\n\n<li>and the result could reasonably change management.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">A large collection of poorly validated biomarkers can create the appearance of precision without actually improving decision-making.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Individualisation should therefore mean <strong>useful precision<\/strong>, not maximal measurement.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Evidence, measurement and uncertainty<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Individualisation does not mean pretending that we can know everything.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Risk calculators have limitations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Cohort studies have limitations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Biomarkers have limitations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Imaging has limitations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">No single test captures the entire biology of atherosclerosis.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The Framingham cohort itself was not a perfectly representative sample of the entire population. The original cohort was predominantly White and was not a random sample of the United States; the study&#8217;s own historical documentation describes important limitations in recruitment and response. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That does not make Framingham unimportant.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It means its findings must be interpreted within their historical and population context and supplemented by evidence from other populations and contemporary cohorts.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Likewise, contemporary risk equations are not perfect.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">PREVENT represents an important advance, but prediction models remain statistical models. They estimate probability; they do not determine an individual&#8217;s future.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The same principle applies to CAC.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A calcium score provides valuable information about coronary calcification, but it does not capture every form of plaque or every mechanism of cardiovascular disease.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Good cardiovascular reasoning therefore requires humility.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The goal is not certainty.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>The goal is better information.<\/strong><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>A modern extension of the Framingham philosophy<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">More than 75 years after the beginning of the Framingham Heart Study, its underlying philosophy remains remarkably relevant.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Cardiovascular disease is multifactorial.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Risk factors accumulate over time.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Those characteristics can be measured.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Risk can be estimated.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Some aspects of atherosclerotic disease can be visualised.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Inherited risk can sometimes be identified.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">And individuals differ.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Modern cardiovascular prevention has extended the original framework considerably.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">We now have contemporary multivariable risk equations such as PREVENT-ASCVD, increasingly sophisticated measurements of atherogenic lipoproteins, Lp(a), kidney and metabolic function, and imaging techniques such as coronary artery calcium scoring. The 2026 ACC\/AHA guideline brings these components together in a more explicitly individualised approach to risk assessment and lipid management. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The result is not a perfect prediction of the future.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is something more modest and arguably more useful:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>a progressively better-informed estimate of where an individual stands today, together with information about factors that may change future risk.<\/strong><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>From information to intervention<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The ultimate purpose of cardiovascular risk assessment is not to win an argument about which lifestyle philosophy is correct.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is prevention.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instead of treating health as a competition between competing ideologies\u2014plant-based versus omnivorous, low-carbohydrate versus high-carbohydrate, exercise versus diet\u2014we can ask a more fundamental set of questions:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What does the population evidence show?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What is this individual&#8217;s baseline risk?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Which risk factors are modifiable?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Which measurements are clinically meaningful?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What changes when an intervention is introduced?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>And does the evidence support those changes as likely to improve meaningful health outcomes?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That framework does not eliminate uncertainty.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It makes uncertainty explicit.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It does not eliminate population research.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It makes population research more useful.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>The bigger picture<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The history from Framingham to Agatston illustrates a broader transformation in cardiovascular medicine.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">First, researchers identified characteristics associated with cardiovascular disease.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Then they developed statistical models that combined those characteristics into estimates of future risk.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Later, researchers developed increasingly sophisticated measurements of lipoproteins, inherited risk and metabolic health.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Then imaging provided another layer of information by allowing calcified coronary plaque to be detected and quantified.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Modern cardiovascular prevention combines these approaches.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The result is not a single perfect number.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is a multidimensional picture.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A person has a history.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">They have measurable physiology.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">They have a genetic and familial context.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">They have an exposure history.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">They may have evidence of subclinical disease.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">And all of these exist within the evidence accumulated from populations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That is what individualisation should mean.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Not ignoring population evidence.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Not replacing clinical outcomes with biomarkers.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Not assuming that one favourable measurement proves that a lifestyle is harmless.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">And not pretending that one scan or one blood test can reveal the entire future.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instead:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>use population evidence to understand risk;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>use individual measurements to understand the person;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>use longitudinal measurements to understand change;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>use imaging selectively when it adds meaningful information;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>and use all of that information to make better prevention decisions.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Perhaps that is the most important lesson of all.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">We should not ask only:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&#8220;What is healthy for people?&#8221;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">We should also ask:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&#8220;What does the evidence tell us about this person?&#8221;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But there is an equally important companion question:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&#8220;How strong is the evidence connecting what we measure today with what we ultimately care about\u2014preventing cardiovascular events?&#8221;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The individual is where cardiovascular disease ultimately occurs.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But our understanding of that individual&#8217;s risk comes from evidence accumulated across populations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Cardiovascular disease does not happen to populations.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>It happens to people.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">And the challenge of modern prevention is to connect those two realities as intelligently as possible.<br><br><br><strong>Additional Frameworks for Interpreting Individual Cardiovascular Risk<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The framework above can be strengthened further by distinguishing several concepts that are often combined in discussions of cardiovascular health.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Individualisation is useful, but it does not mean that every measurement has the same meaning, that every association is causal, or that a favourable short-term biomarker response necessarily translates into improved long-term clinical outcomes.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Four additional concepts are particularly important.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Risk prediction is not the same as causal inference<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">One of the most important distinctions in cardiovascular medicine is the difference between <strong>association, prediction, causation and treatment effect<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">These concepts are related, but they are not interchangeable.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A characteristic can be:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>associated with cardiovascular disease;<\/li>\n\n\n\n<li>useful for predicting cardiovascular events;<\/li>\n\n\n\n<li>causally involved in disease;<\/li>\n\n\n\n<li>or a useful target for intervention.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Those are four different propositions.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For example, suppose a biomarker is consistently associated with higher cardiovascular risk.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That tells us that people with higher levels tend to experience more cardiovascular events.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It does not, by itself, prove that lowering the biomarker will reduce cardiovascular events.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Likewise, a biomarker may be an excellent predictor of risk without being the biological mechanism responsible for that risk.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Conversely, a causal factor may be clinically important even if measuring it does not substantially improve a particular risk prediction model.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This distinction is especially important when interpreting individual data.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Suppose an individual changes their diet and their LDL-C falls.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is reasonable to say:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&#8220;Their LDL-C decreased.&#8221;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is not automatically reasonable to conclude:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&#8220;Their cardiovascular event risk decreased by the same amount.&#8221;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The latter requires evidence linking the intervention and the change in LDL-C to meaningful clinical outcomes.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is why cardiovascular evidence needs to be interpreted across several levels.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Epidemiological studies can identify associations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Risk models can quantify probability.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Mechanistic and genetic evidence can contribute to causal inference.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Randomised trials can provide evidence about the effects of interventions.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Clinical outcomes ultimately tell us whether those interventions translate into fewer events, less disease or longer life.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The distinction can be summarised simply:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Prediction asks: Who is more likely to experience an event?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Causation asks: What contributes to causing the event?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Intervention evidence asks: What happens if we change it?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Those questions overlap, but they are not the same question.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This distinction protects individualised medicine from becoming overly reductionist.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A person should not be told that a single biomarker determines their future.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Nor should a favourable biomarker response be treated as proof that a particular lifestyle intervention has eliminated cardiovascular risk.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The most useful interpretation combines the individual&#8217;s measurements with the strength and type of evidence connecting those measurements to clinical outcomes.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Why a low 10-year risk does not necessarily mean low lifetime risk<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Time horizon is another critical component of cardiovascular risk assessment.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A person&#8217;s 10-year risk and their lifetime risk can tell very different stories.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Consider a relatively young adult with moderately elevated atherogenic lipoproteins but otherwise favourable characteristics.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Because age is such a powerful component of short-term absolute risk, that individual may have a relatively low estimated 10-year risk.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But if the elevation in atherogenic lipoproteins persists for decades, cumulative exposure may become much more important.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is particularly relevant to LDL-C and ApoB.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Atherosclerosis is a cumulative, life-course process.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Two people can have the same ApoB concentration today while having very different histories of exposure.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">One may have had a relatively favourable lipid profile until recently.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The other may have experienced elevated atherogenic lipoprotein levels since early adulthood.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Their present measurements are identical.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Their biological histories are not.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is one reason that a low short-term risk estimate should not automatically be interpreted as evidence that prevention can be ignored.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The 2026 ACC\/AHA dyslipidemia guideline reflects this broader perspective by incorporating both 10-year and 30-year PREVENT-ASCVD risk estimation in appropriate age groups and placing greater emphasis on earlier management of important risk factors. <a href=\"https:\/\/professional.heart.org\/en\/science-news\/2026-guideline-on-the-management-of-dyslipidemia?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\"><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\"><strong>2026 ACC\/AHA Dyslipidemia Guideline<\/strong><\/mark><\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Family history and Lp(a) are also relevant here.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">An individual with a strong family history of premature cardiovascular disease or substantially elevated Lp(a) may have important lifetime risk that is not fully captured by a short-term risk estimate.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This leads to an important principle:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Short-term risk and lifetime risk answer different questions.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A 10-year estimate asks:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">What is the estimated probability of an event over the next decade?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A lifetime or longer-term perspective asks:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">What might prolonged exposure to this individual&#8217;s risk factors mean over the course of decades?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Neither perspective is inherently superior.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">They are complementary.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A young person can have low 10-year risk and still have an important opportunity for prevention.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">An older person may have a substantially higher short-term risk because age itself contributes strongly to absolute risk.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Good cardiovascular assessment therefore requires attention not only to <strong>where the individual is today<\/strong>, but also to <strong>how long important risk factors have been present and what their future trajectory might look like<\/strong>.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What CAC can and cannot tell you<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Coronary artery calcium scoring is one of the most useful examples of why different measurements answer different questions.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A CAC scan can tell us whether calcification is detectable within the coronary arteries and can quantify the amount of coronary calcium using the Agatston method.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In appropriate individuals, this information can improve cardiovascular risk classification and help inform treatment decisions.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But CAC has important limitations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>CAC can tell us:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>whether detectable calcified coronary plaque is present;<\/li>\n\n\n\n<li>approximately how much coronary calcium is present;<\/li>\n\n\n\n<li>how the individual&#8217;s CAC compares with relevant reference populations;<\/li>\n\n\n\n<li>how coronary calcium modifies estimated cardiovascular risk;<\/li>\n\n\n\n<li>whether there is objective evidence of coronary calcification despite otherwise uncertain risk classification.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>CAC cannot tell us:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>that no atherosclerosis exists when the score is zero;<\/li>\n\n\n\n<li>that all coronary plaque is absent;<\/li>\n\n\n\n<li>that non-calcified plaque is absent;<\/li>\n\n\n\n<li>that existing plaque is necessarily stable or unstable;<\/li>\n\n\n\n<li>that cardiovascular risk is zero;<\/li>\n\n\n\n<li>what an individual&#8217;s lifetime LDL-C or ApoB exposure has been;<\/li>\n\n\n\n<li>which particular food or dietary component caused the plaque;<\/li>\n\n\n\n<li>which particular dietary intervention will reverse cardiovascular risk;<\/li>\n\n\n\n<li>or that a favourable CAC score makes all other risk factors irrelevant.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">This distinction is particularly important when interpreting CAC=0.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A zero score can be highly reassuring in appropriate clinical circumstances because it indicates that no detectable coronary calcification was identified.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But it is not equivalent to saying:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&#8220;This person has no cardiovascular disease.&#8221;<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The absence of detectable coronary calcium is not the same as the absence of all atherosclerosis.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Nor does CAC replace the assessment of blood pressure, smoking, diabetes, atherogenic lipoproteins, Lp(a), family history or other important risk factors.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The most appropriate interpretation is therefore:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">CAC<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">Selected references<\/h2>\n\n\n\n<ol start=\"1\" class=\"wp-block-list\">\n<li><strong>Framingham Heart Study. Cardiovascular Disease 10-Year Risk.<\/strong><\/li>\n<\/ol>\n\n\n\n<p class=\"wp-block-paragraph\">Framingham Heart Study. The current Framingham cardiovascular disease risk function incorporates age, diabetes, smoking, systolic blood pressure, antihypertensive treatment, total cholesterol and HDL cholesterol, with BMI available in a simpler model.<br><strong><a href=\"https:\/\/www.framinghamheartstudy.org\/fhs-for-researchers\/fhs-risk-functions\/cardiovascular-disease-10-year-risk\/\" target=\"_blank\" rel=\"noopener\"><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">https:\/\/www.framinghamheartstudy.org\/fhs-for-researchers\/fhs-risk-functions\/cardiovascular-disease-10-year-risk\/<\/mark><\/a><\/strong><\/p>\n\n\n\n<ol start=\"2\" class=\"wp-block-list\">\n<li><strong>Pencina MJ, D&#8217;Agostino RB Sr, Larson MG, Massaro JM, Vasan RS.<\/strong> Predicting the Thirty-Year Risk of Cardiovascular Disease: The Framingham Heart Study. <em>Circulation.<\/em> 2009;119:3078\u20133084. doi:10.1161\/CIRCULATIONAHA.108.816694.<\/li>\n<\/ol>\n\n\n\n<p class=\"wp-block-paragraph\"><strong><a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/19506114\" target=\"_blank\" rel=\"noopener\"><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">https:\/\/pubmed.ncbi.nlm.nih.gov\/19506114<\/mark><\/a><\/strong><\/p>\n\n\n\n<ol start=\"3\" class=\"wp-block-list\">\n<li><strong>Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M Jr, Detrano R.<\/strong> Quantification of coronary artery calcium using ultrafast computed tomography. <em>Journal of the American College of Cardiology.<\/em> 1990;15(4):827\u2013832. doi:10.1016\/0735-1097(90)90282-T.<\/li>\n<\/ol>\n\n\n\n<p class=\"wp-block-paragraph\"><strong><a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/2407762\" target=\"_blank\" rel=\"noopener\"><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">https:\/\/pubmed.ncbi.nlm.nih.gov\/2407762<\/mark><\/a><\/strong><\/p>\n\n\n\n<ol start=\"4\" class=\"wp-block-list\">\n<li><strong>Blumenthal RS, Morris PB, Gaudino M, et al.<\/strong> 2026 ACC\/AHA\/AACVPR\/ABC\/ACPM\/ADA\/AGS\/APhA\/ASPC\/NLA\/PCNA Guideline on the Management of Dyslipidemia: A Report of the American College of Cardiology\/American Heart Association Joint Committee on Clinical Practice Guidelines. <em>Circulation.<\/em> Published online March 13, 2026. doi:10.1161\/CIR.0000000000001423.<\/li>\n<\/ol>\n\n\n\n<p class=\"wp-block-paragraph\"><strong><a href=\"https:\/\/professional.heart.org\/en\/science-news\/2026-guideline-on-the-management-of-dyslipidemia\" target=\"_blank\" rel=\"noopener\"><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">https:\/\/professional.heart.org\/en\/science-news\/2026-guideline-on-the-management-of-dyslipidemia<\/mark><\/a><\/strong><\/p>\n\n\n\n<ol start=\"5\" class=\"wp-block-list\">\n<li><strong>Framingham Heart Study. Framingham Risk Functions.<\/strong><\/li>\n<\/ol>\n\n\n\n<p class=\"wp-block-paragraph\">The Framingham Heart Study provides outcome-specific risk functions across different time horizons and populations and emphasises selecting an appropriate algorithm according to cardiovascular outcome, population, time horizon and available risk factors.<br><strong><a href=\"https:\/\/www.framinghamheartstudy.org\/fhs-for-researchers\/fhs-risk-functions\/\" target=\"_blank\" rel=\"noopener\"><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">https:\/\/www.framinghamheartstudy.org\/fhs-for-researchers\/fhs-risk-functions\/<\/mark><\/a><\/strong><\/p>\n\n\n\n<ol start=\"6\" class=\"wp-block-list\">\n<li><strong>Framingham Heart Study. Cardiovascular Disease Risk Functions and Calculators.<\/strong><\/li>\n<\/ol>\n\n\n\n<p class=\"wp-block-paragraph\">Framingham provides risk functions for different cardiovascular outcomes and time horizons, including 10-year and 30-year cardiovascular disease risk.<br><strong><a href=\"https:\/\/www.framinghamheartstudy.org\/fhs-for-researchers\/fhs-risk-functions\/\" target=\"_blank\" rel=\"noopener\"><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">https:\/\/www.framinghamheartstudy.org\/fhs-for-researchers\/fhs-risk-functions\/<\/mark><\/a><\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Individual Cardiovascular Risk: From Framingham to the Agatston Score From population evidence to the cardiovascular profile of the individual Cardiovascular disease is often discussed using population statistics. We hear that a particular dietary pattern is associated with lower cardiovascular risk,<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1,4],"tags":[148,149,140,136,104,141,147,146,145,143,142,102,138,150,144,139,137],"class_list":["post-2093","post","type-post","status-publish","format-standard","hentry","category-blog","category-health","tag-bill-clinton-frmaingham","tag-bill-clinton-heart-bypass","tag-cardio-vascular-disease","tag-cardiovascular-disease","tag-cvd","tag-cvd-risk","tag-framingham-heart-attack","tag-framingham-heart-study","tag-framingham-vegan","tag-heart-attack-risk-vegan","tag-heart-attack-risk-vegans","tag-heart-disease","tag-heart-disease-vegans","tag-the-last-heart-attack","tag-vegan-heart-attack","tag-veganism-heart-disease","tag-vegans-heart-disease"],"_links":{"self":[{"href":"https:\/\/plantbasedrunners.com\/vegan-blog\/wp-json\/wp\/v2\/posts\/2093","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/plantbasedrunners.com\/vegan-blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/plantbasedrunners.com\/vegan-blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/plantbasedrunners.com\/vegan-blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/plantbasedrunners.com\/vegan-blog\/wp-json\/wp\/v2\/comments?post=2093"}],"version-history":[{"count":8,"href":"https:\/\/plantbasedrunners.com\/vegan-blog\/wp-json\/wp\/v2\/posts\/2093\/revisions"}],"predecessor-version":[{"id":2113,"href":"https:\/\/plantbasedrunners.com\/vegan-blog\/wp-json\/wp\/v2\/posts\/2093\/revisions\/2113"}],"wp:attachment":[{"href":"https:\/\/plantbasedrunners.com\/vegan-blog\/wp-json\/wp\/v2\/media?parent=2093"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/plantbasedrunners.com\/vegan-blog\/wp-json\/wp\/v2\/categories?post=2093"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/plantbasedrunners.com\/vegan-blog\/wp-json\/wp\/v2\/tags?post=2093"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}