Prevalence-incidence bias is a type of selection bias. It is also known as “Neyman bias”.
Prevalence-incidence bias occurs when individuals with severe or mild disease are excluded, resulting in an error in the estimated association between an exposure and an outcome. There are a number of different ways that this bias can arise in research.
If, when studying cardiac arrest, one only collects data on arrival the the emergency department, you would miss all the patients who were declared dead on scene, who may be systematically different from those who make it to hospital.
If you were studying risk factors for myocardial infarction among patients admitted to a cardiac ward, you could get a skewed result if you failed to include healthier patients [perhaps those who has “silent MIs”] or sicker patients, such as those who have already died from a cardiac arrest.
This post is part of a series of posts on bias in medical research. You can find the whole bias catalogue here.
You can find more evidence based medicine resources here.
References
Sackett DL. Bias in analytic research. Journal of chronic diseases. 1979; 32[1-2]:51-63. PMID: 447779
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Epidemiology is the branch of medical science that investigates all the factors that determine the presence or absence of diseases and disorders. Epidemiological research helps us to understand how many people have a disease or disorder, if those numbers are changing, and how the disorder affects our society and our economy.[1] Epidemiology is often described as the basic science of public health.[2]Image 1: a disease outbreak investigation.
Epidemiology is the study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to the control of health problems[3]
Key Terms[edit | edit source]
Incidence: The number of new cases of a disease or disorder in a population over a period of time. An example of incidence: Auckland in New Zealand, often has epidemics of meningococcal disease, with annual incidences of up to 16.9/ 100,000 people.[4]
Prevalence: The number of existing cases of a disease in a population at a given time. An example of prevalence: A recent Scottish study showed that the prevalence of obesity in a group of children aged from 3 to 4 years was 12.8% at the time.[5]
Cost of illness: Many reports use expenditures on medical care [i.e., actual money spent] as the cost of illness. Ideally, the cost of illness would also take into account factors that are more difficult to measure, such as work-related costs, educational costs, the cost of support services required by the medical condition, and the amount individuals would pay to avoid health risks.
The disability-adjusted life year [DALY] is a measure of overall disease burden. It was developed in the 1990s as a way of comparing the overall health and life expectancy of different countries.[6]
- Burden of disease: The total significance of disease for society, beyond the immediate cost of treatment. It is measured in years of life lost to ill health, or the difference between total life expectancy and disability-adjusted life expectancy [DALY].
- DALY [Disability-Adjusted Life Year]: A summary measure of the health of a population. One DALY represents one lost year of healthy life and is used to estimate the gap between the current health of a population and an ideal situation in which everyone in that population would live into old age in full health
Important Principles of Epidemiology[edit | edit source]
Study - a scientific discipline with sound methods of scientific inquiry at its foundation. Various methods can be used to carry out epidemiological investigations: surveillance and descriptive studies can be used to study distribution; analytical studies are used to study determinants.[7]
Distribution - the frequency [number of health events in a population and it's relationship of that number to the size of the population - prevalence] and pattern [the occurrence of health-related events by time, place, and person - incidence] of health events in a population.
Determinants - the causes and other factors that influence the occurrence of disease and other health-related events.
Health-related states or events - these may include communicable and non-communicable diseases, chronic diseases, injuries, birth defects, maternal-child health, occupational health, and environmental health. More recently studies have included behaviours related to health and well-being and genetic markers of disease risk.
Specified populations - the epidemiologist is concerned about the collective health of the people in a community or population[2]. A key feature of epidemiology is the measurement of disease outcomes in relation to a population at risk.[8] Implicit in any epidemiological investigation is the notion of a target population about which conclusions are to be drawn and are often observations that can only be made on a study sample, which is selected in some way from the target population.[8]
Application - Epidemiology is not just “the study of” health in a population; it also involves applying the knowledge gained by the studies to community-based practice.
Epidemiology is the study [scientific, systematic, data-driven] of the distribution [frequency, pattern] and determinants [causes, risk factors] of health-related states and events [not just diseases] in specified populations [patient is community, individuals viewed collectively], and the application of [since epidemiology is a discipline within public health] this study to the control of health problems.[2]
Incidence versus Prevalence[edit | edit source]
Incidence is often confused with prevalence. The easy way to remember the difference is that prevalence is the proportion of cases in the population at a given time rather than rate of occurrence of new cases. Thus, incidence conveys information about the risk of contracting the disease, whereas prevalence indicates how widespread the disease is.