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Health Analytics Summary
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Health AnalyticsLecture 1.
What is a variable?
- Gender
- Age
- Socioeconomic status
- Intelligence
- Disease status
- Ethnicity
- Genetic markers
A good variable should
- Have an impact on health in individuals and populations
- Be measurable accurately
- Differentiate populations in some underlying characteristic relevant to health
- Generate
o Testable aetiological hypotheses and/or
o Help to develop health policy and/or
o Help to plan and deliver health care and/or
o Help to prevent and control diseases
Length of influence on behaviour
How do you measure a variable?
“The first question for the epidemiologist, in any investigation, is the nature and validity of the
definition of the disease or other problem under investigation”
You should strive to be specific as possible. However, you do not always have the specific data.
Replication crisis: famous things are mis proven, because there are a lot of articles that just been
replicated.
→ when is the boundary? 35 case control studies? With a lot of things, you are bound by
observational studies, since it is unethical to force someone to begin smoking.
→ be aware that there are lot of biases.
Practical 1.
Onderwerpen
- Effectief gebruik van data van fit
- Astma meten bij kinderen, voorspellen en voorkomen
- Monitoren hormonen burn-out
- Uitdroging / smart mirror system
https://economictimes.indiatimes.com/magazines/panache/click-click-snap-one-look-at-patients-
face-and-ai-can-identify-rare-genetic-diseases/articleshow/67486179.cms?from=mdr
Book chapter 1.
1.1 The individual and the population
Population groups have unique and distinctive patterns of disease. This pattern is a result of
variations in the exposure of the individuals in the population to the causes of disease that are
mainly behavioural and environmental. If different populations were exposed equally to the same
,causes they would have more or less the same patterns of disease. Some variation would remain due
to genetic differences, which are extremely small between populations.
The population pattern of disease s not solely dependent on the characteristics of individuals
but also on the interaction between individuals with each other and the environment in which they
live. Distinctive population patterns of diseases arse from difference in the interaction of individuals
in a social setting. The risk for some diseases (depression, anorexia, etc) would change if society or
the environment changed.
1.2 Definition of epidemiology and statement of its central paradigm
The word epidemiology derived from the Greek words meaning study upon populations. Looks like
the concept demography, which is the study of characteristics of populations. However,
epidemiology is concerned primarily with disease, and how disease detracts from health.
Last’s definition of epidemiology includes ‘the study of the distribution and determinants of health-
related states or events in specified populations, and the application of this study to control of health
problems’. Kuhn’s concept of scientific paradigm is a helpful concept to epidemiology. The paradigm
of epidemiology is that patterns of dissease in populations may be analysed systematically to provide
understanding of the causes and control of disease. It is important to seek out the differences and
similarities in the disease patterns of populations to gain new knowledge.
1.3 directions in epidemiology and its uses
Epidemiology has been useful in the laboratory, for example, for defining standards and ranges for
the normal values of biological and social measures. Currently epidemiology is seen as useful in:
- Yielding understanding of what causes or sustains disease in population
- Preventing and controlling disease in population
- Guiding health and healthcare policy and planning
- Assisting in the management and care of health and disease in individuals
1.4 epidemiology as a science, practice, and craft
Science is about knowledge. There is a wide range or meanings where the word is used to indicate a
systematic way of doing anything. The idea, the question, the testable hypothesis, the research test,
and the interpretation of the research data to advance understanding of natural phenomena,
together, comprise science. Epidemiology studies the nature of disease, and their causes, and it uses
systematic methods of measurement to test ideas, questions and hypotheses, and hence it is a bio-
science, serving medicine and public health just as medical sciences such as pathology and
microbiology do. Since it studies disease within a cultural context, it is also a social science. In
addition, populations exist in a physical environment which is a dominant force in determining
health. Therefore, it is also science of the ecology.
1.5 the nature of epidemiological variables
A variable is anything which varies and has different values. in epidemiology, the word variable is
often applied to factors which help to describe and understand disease patterns. These are also
called exposure variables. A good epidemiological variable should:
- Have an impact on health in individuals and populations
- Be measurable accurately
- Differentiate populations in their experience of disease or health
- Differentiate populations in some underlying characteristic relevant to health e.g. income,
childhood circumstance, hormonal status, etc.
- Generate testable aetiological hypotheses, and/or
o Help to develop health policy, and/or
o Help to plan and deliver health care, and/or
o Help to prevent and control disease.
,1.6 a disease and health problem: an illustration of the interdependence of clinical medicine and
epidemiology
The craft of epidemiology is presenting the scientific evidence in ways which lead to effective public
health action.
If the cause of a disease is unknown, the disease must be defined on the clinical picture. The first
question is the nature and validity of the definition of the disease or other problem under
investigation. Clinicians need to study cases and agree on a definition which will permit the
classification of sick people into one of two groups: probably suffering from the disease or probably
not. …
1.7 seeking the theoretical foundations of epidemiology
A theory is a statement which provides an explanation or coherent account of a group of ideas, facts,
or observed phenomena. Epidemiology draws upon and contributes to theories of health and
disease. In most disciplines theories are at the core of thinking and practice. The main
epidemiological theories and principles that have guided this chapter includes:
- Disease in populations is more than the sum of the disease in individuals
- Populations differ in their disease experience
- Disease experiences within populations differ in subgroups of the population
- Disease variations can be described, and their causes explored by assessing whether
exposure variables are associated with disease patterns
- Knowledge about health and disease in human populations can be applied to individuals and
vice versa
- Health policies and plans, and clinical care can be enriched by understanding of disease
patterns in populations
Book chapter 2.
2.1 the individual and the population
Family is the basic unit of group for humans, but nearly all humans live in larger populations. The
interaction of humans in societies is the keystone of epidemiology as a medical science. No
epidemiological study can be done on one person.
Time, place and personal can be
thought of as exposure variables. We
are, then, examining how time, place,
and personal characteristics are
associated with disease pattern. The
strategy of epidemiology is to discover
the causes of these patterns, and
ultimately the causes of disease.
Epidemiological conclusions are
directly applicable to the groups
studied, but only indirectly to
individuals, and then only to those
who are reasonably typical of the
population which has been studied.
However, it still benefits individuals.
2.2 harnessing heterogeneity
Epidemiological study of disease patterns should be based on populations defined in terms of
location, size, age and sex structure, and a wide range of data on the life and environmental
circumstances of the people. The idea is to define and utilize the inherent heterogeneity of the
population, and measure characteristics that are potential explanations for disease variation.
, Paradoxically, the heterogeneity so vital to epidemiological investigation of disease poses challenges
in interpreting and applying research. While tobacco and alcohol, for example, are damaging to
health in populations, there are people and groups for whom these substances are harmless and
perhaps even beneficial in some respects. For example, tobacco use is clearly linked to fewer
problems with ulcerative colitis, and it suppresses the appetite and prevents weight gain. Alcohol in
small amounts is widely agreed to reduce the risk of atherosclerotic heart disease and possibly stroke
too.
2.3 disease patterns as a manifestation of individuals living in changing social groups
Diseases are expressed biologically, however, the cause is social. Individuals shape society, and in
turn society exerts a powerful influence on individuals, which manifests itself in attitudes, behaviour,
and diseases. For nearly all diseases the pattern would be greatly different if the social organization
differed.
2.5 individual and population level epidemiological variables
Information collected at the individual level may not portray the true state of the society or
population. Equally, information on a population or the environment may not have meaning at an
individual level. Epidemiology is generally based on studies of the entire population of interest and
on samples selected using methods like random sampling and stratified sampling. In epidemiological
studies the population distribution must be examined to assess whether it follows the normal
distribution. If it does, then the mean and standard deviation provide an accurate picture of the
distribution. If not, the distribution should be shown because summary statistics do not permit the
reader to envision it accurately. Epidemiological findings based on variables that have no meaningful
individual counterpart may be applicable only at population level.
2.6 epidemiology and demography: interdependent population sciences
Demography s the study of population, including the impact of birth, death, fertility, marriage,
migration, and other social factors on population structure and trends. There is an overlap between
demography and epidemiology. Epidemiology is dependent on demography and is difficult to do well
when demographic data are not available. The work of demographers and health statisticians who
work to develop disease rates clearly overlaps with that of epidemiologists and yet differs from it in
one important goal: epidemiology needs to understand, explain and use, and not just describe, the
pat- terns of disease and that means understanding enough about the population to generate and
test causal hypotheses. When generalization is not appropriate, epidemiological data can still be
used for local assessment of the health state of the people actually studied.
2.7 the dynamic nature of human population
In natural living communities the size and composition of populations is constantly changing owing to
deaths, births and migrations. However, even when the population size remains fixed, the population
is still changing. Obviously, within any fixed group the individuals are getting older so the average age
increases, and that will have a profound effect on the pattern of disease. In closed populations
people who are dying and migrating are not replaced. In open populations there are gains as well as
losses, as people are born and migrate into the population.
2.8 applications of the population concept
Traditionally, healthcare systems have been designed around those who voice their need by
consulting a doctor or other healer. Increasingly, healthcare systems are broadening their scope and
focusing on their goals of improving the health of the whole population by using the concept of
population in a number of ways.
1. They are planning services based on the pattern of health problems in the population as a
whole, taking into account variation in the health of subgroups within the population, and
not just of users of the service.
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