Epidemiology, Evidence-based Medicine and Public Health

Yoav Ben-Shlomo, Sara Brookes, Matthew Hickman

• Editorial: Wiley-Blackwell
• Año: 2013
• ISBN:
  9781118463567
• Edición: 6
• Categoría: Medicina
• Categoría: Bioestadística

Translating the evidence from the bedside to populations This sixth edition of the best-selling Epidemiology, Evidence-based Medicine and Public Health Lecture Notes equips students and health professionals with the basic tools required to learn, practice and teach epidemiology and health prevention in a contemporary setting. The first section, 'Epidemiology', introduces the fundamental principles and scientific basis behind work to improve the health of populations, including a new chapter on genetic epidemiology. Applying the current and best scientific evidence to treatment at both individual and population level is intrinsically linked to epidemiology and public health, and has been introduced in a brand new second section: 'Evidence-based Medicine' (EBM), with advice on how to incorporate EBM principles into your own practice. The third section, 'Public Health', introduces students to public health practice, including strategies and tools used to prevent disease, prolong life, reduce inequalities, and includes global health.

Thoroughly updated throughout, including new studies and cases from around the globe, key learning features include:

• Learning objectives and key points in every chapter
• Extended coverage of critical appraisal and data interpretation
• A brand new self-assessment section of SAQs and 'True/False' questions for each topic
• A glossary to quickly identify the meaning of key terms, all of which are highlighted for study and exam preparation
• Further reading suggestions on each topic

Whether approaching these topics for the first time, starting a special study module or placement, or looking for a quick-reference summary, this book offers medical students, junior doctors, and public health students an invaluable collection of theoretical and practical information.

Part 1

Epidemiology

1

Epidemiology: defining disease and normality

Sara T. Brookes and Yoav Ben-Shlomo

University of Bristol

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Learning objectives

In this chapter you will learn:

• what is meant by the term epidemiology;
• the concepts underlying the terms ‘normal, abnormal and disease’ from a (i) sociocultural, (ii) statistical, (iii) prognostic, (iv) clinical perspective;
• how one may define a case in epidemiological studies.

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What is epidemiology?

Trying to explain what an epidemiologist does for a living can be complicated. Most people think it has something to do with skin (so you're a dermatologist?) wrongly ascribing the origin of the word to epidermis. In fact the Greek origin is epidēmia – ‘prevalence of disease’ (taken from the Oxford online dictionary) – and the more appropriate related term is epidemic. The formal definition is

‘The study of the occurrence and distribution of health-related states or events in specified populations, including the study of the determinants influencing such states and the application of this knowledge to control the health problems’ (taken from the 5th edition of the Dictionary of Epidemiology)

An alternative way to explain this and easier to comprehend is that epidemiology has three aims (3 Ws).

Whether	To describe whether the burden of diseases or health-related states (such as smoking rates) are similar across different populations (descriptive epidemiology)
Why	To identify why some populations or individuals are at greater risk of disease (risk-factor epidemiology) and hence identify causal factors
What	To measure the need for health services, their use and effects (evidence-based medicine) and public policies (Public Health) that may prevent disease – what we can do to improve the health of the population

Population versus clinical epidemiology – what's in a name?

The concept of a population is fundamental to epidemiology and statistical methods (see Chapter 3) and has a special meaning. It may reflect the inhabitants of a geographical area (lay sense of the term) but it usually has a much broader meaning to a collection or unit of individuals who share some characteristic. For example, individuals who work in a specific industry (e.g. nuclear power workers), born in a specific week and year (birth cohort), students studying medicine etc. In fact, the term population can be extended to institutions as well as people; so, for example, we can refer to a population of hospitals, general practices, schools etc.

Populations can either consist of individuals who have been selected irrespective of whether they have the condition which is being studied or specifically because they have the condition of interest. Studies that are designed to try and understand the causes of disease (aetiology) are usually population-based as they start off with healthy individuals who are then followed up to see which risk factors predict disease (population-based epidemiology). Sometimes they can select patients with disease and compare them to a control group of individuals without disease (see Chapter 5 for observational study designs). The results of these studies help doctors, health-policy-makers and governments decide about the best way to prevent disease. In contrast, studies that are designed to help us understand how best to diagnose disease, predict its natural history or what is the best treatment will use a population of individuals with symptoms or clinically diagnosed disease (clinical epidemiology). These studies are used by clinicians or organisations that advise about the management of disease. The term clinical epidemiology is now more often referred to as evidence-based medicine or health-services research. The same methodological approaches apply to both sets of research questions but the underlying questions are rather different.

One of the classical studies in epidemiology is known as the Framingham Heart Study (see http://www.framinghamheartstudy.org/about/history.html). This study was initially set up in 1948 and has been following up around 5200 men and women ever since (prospective cohort study). Its contribution to medicine has been immense, being one of the first studies to identify the importance of elevated cholesterol and high blood pressure in increasing the risk of heart disease and stroke. Subsequent randomised trials then went on to show that lowering of these risk factors could importantly reduce risk of these diseases. Furthermore the Framingham risk equation, a prognostic tool, is commonly used in primary care to identify individuals who are at greater risk of future coronary heart disease and to target interventions (see http://hp2010.nhlbihin.net/atpiii/calculator.asp).

Regardless of the purpose of epidemiological research, it is always essential to define the disease or health state that is of interest. To understand disease or pathology, we must first be able to define what is normal or abnormal. In clinical medicine this is often obvious but as the rest of this chapter will illustrate, epidemiology has a broader and often pragmatic basis for defining disease and other health-related states.

What is dis-ease?

Doctors generally see a central part of their job as treating people who are not ‘at ease’ – or who in other words suffer ‘dis-ease’ – and tend not to concern themselves with people who are ‘at ease’. But what is a disease? We may have no difficulty justifying why someone who has had a cerebrovascular accident (stroke), or someone who has severe shortness of breath due to asthma, has a disease. But other instances fit in less easily with this notion of disease. Is hypertension (high blood pressure) a disease state, given that most people with raised blood pressure are totally unaware of the fact and have no symptoms? Is a large but stable port wine stain of the skin a disease? Does someone with very protruding ears have a disease? Does someone who experiences false beliefs or delusions and imagines her/him-self to be Napoleon Bonaparte suffer from a disease?

The discomfort or ‘dis-ease’ felt by some of these individuals – notably those with skin impairments – is as much due to the likely reaction of others around the sufferer as it is due to the intrinsic features of the problem. Diseases may thus in some cases be dependent on subjects' sociocultural environment. In other cases this is not so – the sufferer would still suffer even if marooned alone on a desert island. The purpose of this next section is to offer a structure to the way we define disease.

A sociocultural perspective

Perceptions of disease have varied greatly over the last 400 years. Particular sets of symptoms and signs have been viewed as ‘abnormal’ at one point in history and ‘normal’ at another. In addition, some sets of symptoms have been viewed simultaneously as ‘abnormal’ in one social group and ‘normal’ in another.

Examples abound of historical diseases that we now consider normal. The ancient Greek thinker Aristotle believed that women in general were inherently abnormal and that female gender was in itself a disease state. In the late eighteenth century a leading American physician (Benjamin Rush) believed that blackness of the skin (or as he termed it ‘negritude’) was a disease, akin to leprosy. Victorian doctors believed that women with healthy sexual appetites were suffering from the disease of nymphomania and recommended surgical cures.

There are other examples of states that we now consider to be diseases, which were viewed in a different light historically. Many nineteenth-century writers and artists believed that tuberculosis actually enhanced female beauty and the wasting that the disease produces was viewed as an expression of angelic spirituality. In the sixteenth and seventeenth centuries gout (joint inflammation due to deposition of uric acid) was widely seen as a great asset, because it was believed to protect against other, worse diseases. Ironically, recent research interest has suggested a potential protective role of elevated uric acid, which may cause gout, for both heart and Parkinson's disease.

In Shakespeare's time melancholy (what we would now call depression)...