Introduction to Epidemiology

1
Day 1 Session 2 How do we measure the health
of the public?An introduction to epidemiology
delivered by Alison Hill
2

• What is epidemiology and what are its uses?
• Descriptive epidemiology
• Incidence and prevalence
• Qualitative information
• Analytical epidemiology
• Types of studies
• Association and causation

3
What is Epidemiology?

• the study of the frequency, distribution and
  determinants of health problems and disease in
  human populations
• The unit of interest is the population

4
Purpose of epidemiology

• To obtain, interpret and use health information
  to promote health and reduce disease

5
In the news

No evidence to support the role of antioxidant
supplements in increasing the lifespan of healthy
people or patients with various diseases
Diagnostic heart tests are underused in older
people, women, south Asians, and people from
deprived areas Uptake of HPV vaccine by
adolescent schoolgirls in Manchester is good
overall, but lower in areas with a higher
proportion of ethnic minority girls

6
How does Epidemiology help? (1)

• It allows the distribution of health and illness
  in a population to be described in terms of
• WHERE and WHEN does this health problem occur in
  the population?
• WHAT is the problem and its frequency?
• WHO is affected?
• WHY does it occur in this particular population?

7
How does Epidemiology help? (2)

• Epidemiological information is used to
• Prevent illness and promote health
• To help treat people with existing disease
• Evaluate existing health services

8
Epidemiological Studies
9
What is descriptive epidemiology?

• Frequency (of disease)
• (incidence prevalence)
• Distribution (of disease)
• descriptive epidemiology

10
Descriptive epidemiology

• Usually makes use of routinely collected data,
• (e.g. death certification data, hospital episode
  statistics, infectious disease notifications)
• May require special surveys (usually cross
  sectional)
• Cant answer why? but can raise a causal
  hypothesis
• Can often provide sufficient information for
  public health action to be taken

11
TIME, PLACE, PERSON

• Time Trends, seasonal variations, cohort
  effects
• Place Variations between geographical areas
  local, national, international
• Person Variations in health by age, sex,
  ethnicity, occupation, leisure interests...
• All help us examine variations (inequalities) in
  health

12
Example Pneumococcal meningitis incidence rate
per 100,000 population by age group, England and
Wales, 1996-2005 (Source HPA surveillance data)
13
Public Health Action

• On 4th September 2006 Pneumococcal vaccination
• introduced into childhood immunisation schedule!

14
Cumulative weekly number of reports of Invasive
Pneumococcal Disease due to any of the seven
serotypes in Prevenar Children aged lt 2 Years
in England and Wales by Epidemiological Year
July-June (2003- To Date)
15
Example 2
Why might death rates in the UK be high?
16
Descriptive epidemiology

• By studying frequency and distribution we can
  describe patterns of disease
• This can raise further questions and help us to
  generate hypotheses for the causes of disease
• It also helps us to respond to public health
  problems

17
Measures of disease frequency

• There are 2 major types of measure of disease
  frequency
• Incidence
• Prevalence

18
What is incidence?

The incidence is the number of NEW CASES of
disease that develop, in a population of
individuals at risk, during a specified time
period Usually expressed as the number of new
cases, per 100,000 population per year
19
Example 3 Measuring incidence

• Incidence of cervical cancer in a PCT during 2002
• Number of new cases during 2002 18
• Number of disease-free persons (population at
  risk) at the beginning of 2002 200,000
• Incidence is (18/200,000) x 100,000
• 9 cases of cervical cancer per 100,000 in 2002
• N.B. The denominator might be taken as the
  population at risk at the beginning, or the
  mid-point of the year, or the total person-time
  at risk

20
What is prevalence?

• Prevalence is the total number of EXISTING CASES
  of
• disease in a population at one point in time.
• It is expressed as a proportion of the total
  number of
• persons in that population.
• Also referred to as point prevalence
• Period prevalence is a variation which represents
  the
• number of persons who were a case at any time
  during
• a specified period, as a proportion of the total
  number
• of persons in that population

21
Prevalence

• Prevalence is expressed as a proportion
• (0-100)
• or as a rate
• (e.g. X cases per 100,000 population)
• It does not take into account WHEN people became
  infected / diseased

22
Example 4 Labouring the point!Incidence and
prevalence
Cases of cold infections in class 4J. Class size
20
January
February
March
What is the period prevalence during
February? What is the point prevalence on the
28th February? What is the incidence in February?
6/20 30
1/20 5
4/?
23
Incidence and prevalence
Incidence (new cases)
Sick population (Prevalence)
Healthy population
recover
die (mortality)
24
Analytical epidemiology

• Descriptive epidemiology
• Analysis of cause and effect
• analytical epidemiology

25
Example 5 John Snow

• John Snow, physician (1813-1858)
• Outbreaks of Cholera were common in London during
  the 19th century
• But what was causing the cholera? The popular
  theory at the time was that bad gases caused it
  (miasma theory)

26
What did he do?
Analysis by place he mapped the cases most
were near Broad Street (miasma would predict
even spread) Anecdote People had complained that
the water smelt bad. Cases from further afield
had water delivered by cart from Broad Street.
27
Public health action
He removed the handle from the Broad Street pump
and the number of infections fell.
28
What did he do?
Recorded deaths by water supplier The Lambeth
company had started to pump water from 20 miles
upstream from the Thames Conclusion Risk of
infection is highest in people using water from
the Southwark and Vauxhall water company.
29
Types of analytical study

• Observational studies
• Cross-sectional study
• (may be descriptive or analytical)
• Case control study
• Cohort study
• Intervention study (experimentation)
• Randomised controlled trial (RCT)

30
Cross-sectional study

• Information on health status and other
  characteristics is collected from each subject at
  one point in time
• Cross-sectional studies can be descriptive
• (eg. the prevalence of cough in a population)
• Or analytical
• (eg. the association between cough and risk
  factors such as type of house lived in or whether
  person is a smoker)

31
Example 6 cross sectional study

• A cross sectional survey of adult dental health
  in Cornwall, in 1996.
• Aims
• to provide a baseline measure of dental health
  status (descriptive)
• to compare dental health status in deprived and
  affluent neighbourhoods (analytical)

32
Sampling method
deprived e.d.s
randomly selected e.d.s
affluent e.d.s
...Townsend score .....-
Using deprivation data from the 1991 census,
participants were selected from the most deprived
and the most affluent enumeration districts, and
a random selection of e.d.s in between.
33
Survey of adult dental health in Cornwall

Deprived people in both age groups were more
likely than affluent people to be in poor dental
health.
34
After difficulty in finding a dentist, what was
the outcome?
Most people in deprived areas eventually found an
NHS dentist, or gave up. People in more affluent
areas were more likely to pay privately for
treatment.
PH action grants for service development
targeting high need areas.
35
Case-control study

• Compares people with a condition (cases) to a
  similar group of people without the condition
  (controls)
• The aim is to try and identify the risk factors
  which may have caused the cases to get the
  condition in the first place
• Often used to investigate the source of an
  outbreak of disease.

36
Example 7 Case control study

• What caused an outbreak of Salmonella in south
  east Wales?
• A case control study of people in SE Wales
  examined their diet and behaviour during the 3
  days before illness
• Those who were ill were found to have been 4.5 x
  more likely to have eaten sliced ham than those
  who were not ill
• Further investigations revealed that those who
  were ill were 25 x more likely to have eaten ham
  supplied by producer A

37
Exposure
Outcome
Exposure 1
Case (Person with outcome)
Exposure 2
Exposure 3
Control (Person without the outcome
Exposure 4
38
Cohort Study

• Follow up two groups of people over time and
  compare the occurrence of disease
• One group is exposed to a possible risk factor
  for the disease, while the other is not (the
  control group)
• The exposure is the starting point, the disease
  is the outcome of interest

39
Example 8 Cohort study

• Does being exposed to asbestos cause respiratory
  cancer?
• Asbestos miners were followed up for 6 years.
  These were compared to the control group
• Asbestos miners were 50 more likely to die of
  respiratory cancer than the control group.

40
Outcomes
Exposure
Exposed
Outcome
Population
Outcome
Unexposed
41
Cohort Study (2)

• Cohorts can be retrospective too
• The starting point is still the EXPOSURE
• Outbreak of salmonella amongst guests at a
  wedding
• Use wedding menu to identify potential exposures
  and then survey the guests
• Identify most likely source of the outbreak

42
Randomised Controlled Trial

• Compares effectiveness of a new intervention
  against the best current alternative (or a
  placebo)
• Can be for clinical or educational interventions

43
Randomised Controlled Trial

• Select people with the same disease or
  characteristics (a defined target population)
• Randomly allocate these people to intervention
  or control groups
• Intervention group receives the new treatment,
  the control group receives the standard or
  placebo treatment
• The benefits of each treatment are assessed by
  comparing the health gain in each group

44
Randomised controlled trial
intervention
group 1
Outcome
population
Outcome
group 2
control
45
Example 11 RCT
Didgeridoo playing as alternative treatment for
obstructive sleep apnoea syndrome randomised
controlled trial. Reported in BMJ Dec 2005.

• 25 adults with obstructive sleep apnoea,
  randomised to didgeridoo instructions and daily
  practice for 4 months (14), or placing on the
  waiting list for lessons (11).
• Didgeridoo players reported less daytime
  sleepiness and their partners reported less night
  time disturbance, compared with waiting list
  group.

46
In the news..BBC website
Sibling link to heart health risk Having a
brother or sister with cardiovascular disease
(CVD) is bad news for your own odds of developing
problems, research has found.

• Vitamin D can lower cancer risk
• High doses of vitamin D can reduce the risk of
  developing some common cancers by as much as 50,
  US scientists claim.

• Grapefruit 'may cut gum disease'
• Researchers found people with gum disease who
  ate two grapefruits a day for a fortnight showed
  significantly less bleeding from the gums.

Oily fish is a source of vitamin D
Grapefruit is full of vitamin C
Heart disease may run in the family
47
Interpreting results of analytical studies

• No association found
• Association may be artifactual (false)
• Due to Chance
• Due to Bias in the study
• Association may be real, but indirect
• Apparent relationship due to a confounding factor
  
• Association is direct (causal, true)

48
Central dogma of epidemiology

• An ASSOCIATION between a risk factor (smoking)
  and a disease (lung cancer)
• DOES NOT INDICATE
• a CAUSAL relationship

49
Association is not proof of causeBradford Hills
Criteria for Causation

• Strength of association
• Temporal relationship
• Geographical distribution
• Dose-response relationship
• Consistency of results
• Biological plausibility (but remember John Snow)
• Specificity (if a single causal agent)
• Reversibility

50
Assessing the relationship between a possible
cause and an outcome
51
Horses for courses
52
Conclusions

• Epidemiology is a core part of public health.
• It allows the distribution of health and
  ill-health in a population to be described, and
  possible causal factors to be identified.
• It enables public health professionals to
  understand health problems and take appropriate
  action.

53
What we have covered

• What is epidemiology and what are its uses?
• Descriptive epidemiology.
• Incidence and prevalence
• Analytical epidemiology
• types of studies
• association and causation

54
References

• Medical statistics at a glance Petrie and
  Sabin. Blackwell.
• Epidemiology in Medicine Charles Hennekins.
  Little, Brown and Company.
• Epidemiology for the uninitiated G.Rose and
  D.Barker.
• Health Knowledge website http//www.healthknowledg
  e.org.uk/Epidemiology/Epidemiology201.htm