Information and readings
Epidemiologist in academic setting:
- ‘Scientific detective’
- Epidemiology here is about analysing patterns and causes
- A ‘detective’ aims to understand these patterns
Epidemiology in Public Health setting:
- ‘Crime prevention’
- Epidemiology is aso about using this information for prevention in populations
- Prevention through policies, programmes, and interventions
DISH model:
Determinants of diet and lifestyle
Intake of food and nutrients
Status and function of the body
Health and disease rise
-> The first two public, last two academic, must work together to prevent disease in society.
History of epidemiology and Public Health:
- Preformal epidemiology: 1662-1900, infectious diseases, nutritional deficiencies,
hygiene and sanitation, start travel over world, John Snow “founder of epidemiology”,
- Early epidemiology: 1900-1940, transition from acute infectious diseases to chronic
diseases, interdisciplinary nature of epidemiology.
- Classical epidemiology: 1940-1980, start academic field in US and UK, methodology,
case-control, gohort, RCT’s, chronic diseases, large-scale epidemiological studies.
- Modern epidemiology: >1980, theoretical basis in RCT, differentiation of expertise,
prevention strategies/trials.
, ->
Future:
- Epidemiology provides knowledge about health and its determinants
- Provides foundations for Public Health interventions, policies and programmes.
John Snow: video cholera in Londen: https://youtu.be/lNjrAXGRda4
Reading: Haveman et al. chapter 1
Greek term of Epidemiology: the study of what is upon the people.
Morabia term “”: epidemiology is characterized by the combination of population thinking
and group comprization aiming to discover the determinants of human health.
Hippocrates coined the terms:
- Endemics: diseases usually found in some places but not in others
- Epidemics: diseases that are seen at some times but not others
17th century -> combining of population thinking and group comparison.
Classical epidemiology definition: The study of the distribution and determinants of
health-related states of events in specified populations and the application of this study to
control health problems. This definition integrated population thinking (study of distributions)
and group comparisations (study of health determinants). The second part of the definition
specifies that the usage of these principles is oriented towards the improvement of public
health.
Modern epidemiology definition: the ultimate goal of most epidemiologic research is the
elaboration of causes that can explain patterns of disease occurrence. This definition is a
good reflection of the state of the discipline, because it creates its methods (elaboration of
causes or ‘aetiology’) to its subject matter (disease occurrence).
A recent dictionary of epidemiology offers a broader definition of the discipline, i.e. ‘the
study of the occurrence and distribution of health-related states or events in specified
populations, including the study of determinants influencing such states and the application
of this knowledge to control health problems. This latter definition distinguishes quantitative,
biomedical and environmental aspects that work together toward a common aim, the control
of health problems, that is to promote, protect and restore health in specified populations.
,Reading: Webb et al. chapter 1; Epidemiology is …
1970 definition epidemiology: the study of the distribution and determinants of disease ->
this definition includes the two core strands of traditional epidemiology: who is developing
the disease (and where and when), and why are they developing it.
Latest definition 2014: The study of the occurrence and distribution of health-related
events, states and processes in specified populations, including the study of the
determinants influencing such processes, and the application of this knowledge to control
relevant health problems.
Attack rate (with food poisoning): percentage of people that became ill after eating the food.
Relative risk (of sickness after eating the food in comparison to non-eaters of the food): For
example, 45% of people who ate hot chicken became ill, compared with 32% of people who
did not eat hot chicken. Hot-chicken eaters were therefore 1.4 times (45% 32% 1⁄4 1.4)
more likely to become ill than people who did not eat hot chicken.
The ‘attack rates’ and ‘relative risks’ are simple to calculate and are two very useful
epidemiological measures.
Occupational epidemiology has the longest history of all, with influential early observations
of diseases linked to occupations such as mining appearing in the sixteenth century.
Molecular epidemiology: aims to weld the population perspective of epidemiology with our
rapidly increasing understanding of how variations in genes and their products affect the
growth, form and function of cells and tissues. It thus has the potential to define genetic
contributions to disease risk and can also provide biological markers of some exposures
(e.g. DNA changes due to tobacco smoke).
Clinical epidemiology: is sometimes regarded as a separate discipline because it differs
from other branches of epidemiology in its focus on enhancing clinical decisions to benefit
individual patients, rather than improving the health of populations.
Life source epidemiology: attempts to integrate events across the lifetime, often going right
back to conception and sometimes to previous generations, to understand disease risk.
Questions that have long lain at the heart of epidemiology:
- What disease/condition is present in excess?
- Who is ill?
- Where do they live?
- When did they become ill?
- Why did they become ill?
The first question (what) needs a common definition of the disease for equal comparison.
Epidemiology is all about comparison - without some reference to what is usal, how can we
identify excess?
The next three questions (who/where/when) form the mantra of descriptive epidemiology:
‘person, place and time’. This description needs to capture the essence of the problem and
prompts the last question (why): what caused these epidemics?
1a: way more male participants
1b: Way more adult participants than children, also data abouts deaths is missing from
children.
1c: numbers in socioeconomic groups differ between men/women/children.
2a: adult men are more likely to die than children, adult women are less likely to die than
children.
2b: man are more likely to die than woman
, 2c: People in high eco.class were less likely to die dan in low ecoclass
2d: .
3a: men were 3.125 more likely to die than women.
3b: low SES were 1.995 more likely to die than high SES
4: Titanic deaths
The introduction of more quantitative methods into epidemiology and, in fact, into biology
and medicine in general, has been attributed to John Graunt (1620–1674) -> discovered
more male births and deaths than in woman, high rates of infant mortality and seasonal
variations of mortality, provided numeral account of the impact of the plague in London and
made the first attempts to estimate the size of the population.
in 1950, the publication of two case–control studies of lung cancer, by Richard Doll
(epidemiologist) and Austin Bradford Hill (statistician) in the UK and Ernest Wynder (medical
student) and Evart Graham (surgeon) in the USA, publicly marked the start of modern
epidemiology -> more lung cancer in smoking patients.
Prevalence proportion
Prevalence = how much cases there are
Proportion = percentage
Point prevalence: number of people with a disease on a specific time point.
Period prevalence: number of people with a disease in a specific time period.
Incidence
Incidence = counting new cases, especially it measures how fast people are ‘getting’ the
disease over a period of time (month or year).
We express this in one of two ways:
- Incidence proportion (IP): proportion of people who develop the disease in a
specific time period (0.05 or 5%) -> people who developed disease/people at risk for
disease.
- Incidence rate (IR) or mortality rate: rate at which new cases of a disease have
occurred (5000 new cases per 100.000 persons per year) -> people who developed
disease/total person-time when people were at risk of getting disease.
Relation between incidence and prevalence
Prevalence varies directly with both incidence and duration
- If incidence is low, and duration is long (chronic), prevalence will be large in relation
to incidence.
- If duration is short (due to recovery, migration or death), prevalence will be small in
relation to incidence.
As a formula: P = IR x D
- Assuming that population does not change (stationary population)
- Valid for diseases with low frequency only
- Generally valid: (P/1-P) = IR x D -> official formula
Fixed population: no more people will be added, they can drop out, so populatio will only
decrease.
Open population: people can come in and out of the population.
Calculate the number of person years: multiplying the average size of the population wih the
observation period.
