Post on 26-Dec-2015
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Introduction to Epidemiology
Professor Iain Crombie
Course outline
13 days 11 lectures and tutorials 1 revision session 1 exam
plus private study
aim: to make you like an epidemiologist
Detailed course outline: identifying causes of disease
disease distributions and measuring health descriptive epidemiology, demography, standardisation
interpreting study findings bias, p-values, confounding
epidemiological designs survey, ecological, case-control, cohort, RCT pitfalls in study design and conduct
assess causality how do we know what causes disease how do we assess strength of evidence
A thinking epidemiologist
able to interpret the studies published in medical journals
Teenage pregnancy and sunshine: causal?
Teaching philosophy
given all the necessary explanation you have to use facts not just remember deep understanding is necessary
lots of practice in data interpretation if you don’t follow, ask
the course assessment is about study design
• key features
• identifying flaws/ strengths
interpreting data assessing causality
Assessment assignment 1 15%
data interpretation
assignment 2 15% interpretation of data from a paper
exam (3hrs) 70% section 1 data interpretation section 2 short notes section 3 essay question section 4 interpretation of an abstract
Learning objectives: today
You should be able to define epidemiology describe descriptive epidemiology define measures of disease frequency outline some key concepts in epidemiology think about data
What is epidemiology?
The study of epidemics?
The study of diseases?
The study of diseases of the skin?
Something scientists and academics use to confuse other people?
Definition of epidemiology
“The study of the distribution and determinants of health related states or events in specified populations”
Unpacking that definition
Distribution/ frequencywho, where, when
Determinantswhy
Health related statesdiseases or symptoms or..
Specified populationsread carefully
Definition of epidemiology
“The study of the distribution and determinants of health related states or events in specified populations and the application of this study to control health problems” - James Last A Dictionary of Epidemiology
Examples of determinants
Diseases• Lung cancer• Mesothelioma• Childhood leukaemia• Cervical cancer• Liver cancer• Coronary heart disease
Some causes• smoking, radon• asbestos• intra-uterine X-rays• human papilloma virus• aflatoxin• dietary fat, high blood
pressures, smoking
Evidence pyramid
Distribution: descriptive epidemiology
Person- Who?
Place- Where?
Time- When?
Guides the search to determine Why?
Assumptions in epidemiology
disease does not occur at random disease has causal and preventive factors epidemiology systematically explores
differences in disease frequency in sub-groups causal and preventive factors
Death rates by age E&W 2008
Age specific death rates
arrange people in age groupseg 15-24, 25-34, 35-44…….
count deaths in an age group count no. of people in an age group divide no. of deaths
no. of deaths
no. of people Age specific
death rate = (in an age group)
Mortality at a younger age
Using a logarithmic scale
Death rates by social class
Social class
Deathrates
Specific diseases
Deathrates
Social class
Death rates by deprivation score
Deprivation level
Deathrates
Limiting Long-Term Illness and Poor General Health, 2001
Percentage of women smoking during pregnancy, 2003
Descriptive epidemiology
person place: where time
Death rates in infants by country
Infant death rates by state
Lung cancer mortality
Colorectal cancer mortality
Stomach cancer mortality
Age-standardised death rates per 100,000 by quintile
20.6 – 41.1
41.2 – 50.7
50.8 – 57.7
57.8 – 68.9
69.0 – 136.7
Death rates from coronary heart disease in men
What does it show?
Rates of HIV diagnoses in people
What does it show?
Ischaemic Heart Disease in Men
WHO Global Atlas on cardiovascular disease, 2011
Stroke mortality in men
WHO Global Atlas on cardiovascular disease, 2011
Malaria Mortality
Endemicity of P. falciparum. Hay et al 2007
Frequency of P. vivax. Gething et al 2012
Endemicity of P. falciparum. Hay et al 2007
Prevalence of Duffy negative phenotype. Howes et al 2010
Frequency of P. vivax. Gething et al 2012
Descriptive epidemiology
• person• place• time: when
Death rates in England and Wales
Trends in CHD Mortality England and Wales
Lawlor D A et al. BMJ 2001;323:541-545
Trends in Cardiovascular Disease USA
Non-Hodgkins lymphoma 1971-2010
Monthly deaths and monthly mean temperature
Excess winter mortality by sex and age
What do the data show?
Excess winter mortality by sex and age
• Mortality goes up in winter• Affects older people more• Winter effect greater in older women• Insufficient data to comment on trends over time
Measuring disease frequency
2 main measures are usedPrevalenceIncidence
they are both rates # of diseases / # of people
Prevalence
The number of affected persons present in the population divided by the number of people in the population
# of cases (people with disease)Prevalence = -----------------------------------------
# of people in the population
Prevalence
The number of affected persons present in the population divided by the number of people in the population
If a = no. of people who have the disease b = no. of people who are disease free
aPrevalence = --------
a +b
Prevalence Example
In 1999, a US state reported an estimated 253,040 residents over 20 years of age with diabetes. The US Census Bureau estimated that the 1999 population over 20 in that state was 5,008,863.
What is the prevalence?
Prevalence ExampleIn 1999, a US state reported an estimated 253,040 residents over 20 years of age with diabetes. The US Census Bureau estimated that the 1999 population over 20 in that state was 5,008,863.
253,040Prevalence= = 0.051
5,008,863
• In 1999, the prevalence of diabetes was 5.1%(residents over 20 years of age)
• Can also be expressed as 51 cases per 1,000
Examples of prevalence
• smoking by 15 year old girls 18%• adult hypertension (150/90) 11.7%• adult schizophrenia 11 per 1000• MS in Europe 12.5 per
10,000
.
Prevalence of diabetes adults in the U.S.(Includes Gestational Diabetes)
1990 1995
2001
No Data <4% 4%-6% 6%-8% 8%-10% >10%
1999
Obesity Trends* Among U.S. AdultsBRFSS, 1990, 1999, 2008
(*BMI 30, or about 30 lbs. overweight for 5’4” person)
2008
1990
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
A bit more on prevalenceadult schizophrenia 11 per 1000ie at any time out of 1000 people 11 have schizophreniapoint prevalence
Suitable for conditions which are long lastingWhat about the frequency of having:
a cougha sore back
Period prevalence: measuring episodic conditions
have you had disabling back pain which lasted more than a day over the last six months six months prevalence
have you had a cough which lasted more that a day in the previous 12 months prevalence
Comparing prevalence measures:
Point prevalence 4.1%
Period prevalence (six months) 68%
Lifetime prevalence 84%
Low back pain
Prevalence
Useful for assessing the burden of disease within a population
Valuable for planning
Not useful for determining what caused disease
Check whether point or period
Incidence
The number of new cases of a disease that occur during a specified period of time
÷ the number of persons at risk of developing the disease during that period of time
# of new cases of disease over a specific period of time
Incidence = # of persons at risk of disease over that specific period of time
Lung cancer incidence in England(new cases per 100,000 per year)
Incidence of malignant melanoma (new cases per 100,000 per year)
Annual incidence
count deaths over calendar year use mid-year population as denominator
assume population size constant over the year
expressed ascases per 100,000 per yearcases per 1,000,000 per year (rare diseases)cases per 1,000 per year (common disease)
Incidence rates in sub-groups
2,000 publicans followed for 1 year48 arrests for drink drivingincidence rate = 24 per 1000 per year
ie No. of events/1000 people / year
Another example
201 adults with dementia admitted to a long-term care facility. Of the 201, 91 had a prior diagnosis of depression. Over the first year, 7 adults developed depression.
7Incidence = = 0.064
110why denominator of 110 not 201?The one year incidence of depression among adults with dementia is 6.4 per 100 or 6.4 %or 64 new depression cases per 1,000 persons with dementia
Cumulative incidence
frequency of new cases over a specified period denominator is no. of people at the start of the
period
350 people followed for 7 years and 15 cases of disease occur = 15/ 350 = 0.0429
cumulative incidence = 4.29%
Cummulative incidence of human papilloma virus after 1st intercourse
4 years, > 50%
A potential problem: lost to follow-up 350 people to be followed up for seven years say an epidemic of Black Death in second year kills 200 only 150 subsequently followed up fewer events
Cumulative incidence assumes everybody followed for same length of timeno major changes in death rates
An alternative approach
500 elderly women followed for two years say 300 died exactly at end of first year then 300 for 1 year = 300 person years at risk 200 for 2 year = 400 person years at risk total = 700 person years at risk
73 had hip fracturesincidence rate = 73 / 700 =0.104
or = 10.4 per 100 per year
Allowing for lost to follow up/death
Ten people aged 90 years followed up for 5 yearsnone died in first year
2 died in second year
1 died in third year
5 died in fourth year
none died in fifth year
How many person years at risk?assume deaths occurred at mid year
What was the incidence rate?
Adding it up
2 people lived 1.5 years= 3
1 person lived 2.5 years = 2.5
5 people lived 3.5 years= 17.5
2 people lived 5 years = 10 years
Total = 33 person years
Person years mortality = 8/ 33
= 0.24
= 24 deaths per 100 person years
Different types of incidence rate
annual incidence from routine data
cumulative incidence events divided by initial population
person years incidence allows for loss to follow up
What (annual) incidence tells us
number of new casesover defined period
sensitive to changes in disease risk more suitable for monitoring trends less suitable for assessing burden of disease
Incidence is different to prevalence
incidence number of new cases (per 1000)
• in a defined period
prevalence number of existing cases (per 1000)
Exploring prevalence: an initial look
Prevalence
= prevalent cases
Some time later
Old (baseline) prevalence
= prevalent cases = incident cases
New prevalence
Incidence
No cases die or recover
Later still
= prevalent cases = incident cases = deaths or recoveries
An example to work out
A town has a population of 3600. In 2003, 400 residents of the town are diagnosed as having a disease. The disease is lifelong but it is not fatal.
In 2004, 200 additional residents of the town are diagnosed with the same disease.
•What is the prevalence in 2003? In 2004?•What is the incidence in 2004?
Answers
• Population : 3600• 2003: 400 diagnosed with a disease• 2004: 200 additional diagnosed with the disease• No death, no recovery
Numerator
Denominator
Prevalence (2003)
400
3600
11.1%
Prevalence (2004)
600
3600
16.7%
Incidence (2004)
200
3200
6.3%
Prevalence and incidence of tuberculosis
Prevalence (per 1000)
Incidence (per 1000 per year)
Poorville 60 20Richville 70 10
Poorville: survival time = 3 years
Year Existing cases
New cases
Deaths Prevalence*
1 0 20 0 202 20 20 0 403 40 20 0 604 60 20 20 605 60 20 20 606 60 20 20 60
* survey on 31st December
Richville: survival time = 7 yearsYear Existing
casesNew cases
Deaths Prevalence*
1 0 10 0 102 10 10 0 203 20 10 0 304 30 10 0 405 40 10 0 506 50 10 0 607 60 10 0 708 70 10 10 709 70 10 10 70
* survey on 31st December
Prevalence and Incidence
Prevalence depends on the annual incidence of disease and the duration of disease (in years)
Prevalence and incidence
Incidence (per 100,000 per
year)
Duration (years)
Prevalence (per 100,000)
Poorville 20 3 60
Richville 10 7 70
Prevalence = Incidence x average disease duration(If incidence, survival and cure rates are constant)
Prevalence and incidence
Prevalence = Incidence x average disease duration(If incidence, survival and cure rates are constant)
Incidence (per 100,000 per year)
Duration (years) Prevalence (per 100,000)
Lung cancer 80 0.4 32
Breast cancer 20 5 100
Depression 12,000 0.5 6000
Common cold 50,000 0.01 5,000
Things you should know definition of epidemiology descriptive epidemiology
person, place, time: clues to possible causes
prevalencepointperiod
incidenceannual cumulativeperson years
P = I x D