INTRODUCTION TO EPIDEMIOLOGY

Week 2

What is epidemiology?

Key science of public health Focuses on examining the distribution of

disease across the population Use of largely quantitative methods to

study diseases, inform prevention and control

Epidemiology:

“ the study of the distribution and determinants of health-related states or

events in specific populations

And

the application of this study to the prevention and control of health problems”

Epidemiology: uses

Causation of disease: association between risk factors and outcome

Natural History of disease : course and outcome of disease in groups/ individuals

Health status of populations: disease burden (mortality, morbidity, disability etc)

Evaluating interventions: effectiveness/efficiency

PART I: Measuring Health & Disease

Defining presence or absence of health state/disease

Case Definition

Need to be clear about what definition you are using

Case Definition

What is and is not a case? Need to be clear, easy to use Standardised for use by others

Thinking of your research project- what is your case definition?

Epidemiologcal case not necessarily the same as clinical case

Measuring disease frequencyWhat is population at risk?Need correct estimation of population you are studying (denominator), if you want an accurate rate

Population at risk

Total populationWomen in population

Women aged 25-69 years

What is the population at risk in your study?

Measures of Health & Disease

Measures of disease/ health indicator frequency

Incidence- rate of new cases in a given time period in a specific population

Prevalence – frequency of existing cases in a defined population at a given time

Incidence vs. prevalenceIncidence Prevalence

Numerator No. NEW cases of disease in a specific time frame

No. EXISTING cases of disease at specific time

Denominator Population at risk Population at risk

Uses Expresses risk of becoming ill Estimates the probability of the population being ill at the period of time being studied

Acute conditionsUseful for causation

Useful in study of burden of chronic diseases and implication for health services

PREVALENCE = INCIDENCE X DURATION

Calculating prevalence

Prevalence = No. people with disease or condition at specific time

No. people in population at risk in specified time

Often expressed as cases per 100 (%) or per 1,000

Prevalence

Period Prevalence: Total No. of cases at any time during a specific period

Population at risk midway through the period

Point prevalence: data collected at one specific point in time

Lifetime prevalenceTotal no. persons known to have had the disease for at least some part of their lives

Factors influencing prevalence

Severity of illness (if severe with high fatality, prevalence reduces)

Duration of illness (if short, prevalence lower than if long)

Number of new cases (if many people develop a disease, its prevalence is higher than if fewer people do)

In migration & out-migration (of healthy or susceptible population)

Diagnosis and cure rates

Incidence

The rate at which new events occur in population.

Incorporates the variable time periods during which individuals are disease free – or ‘at risk’ of developing disease

Incidence

Incidence =

No. new events in specific period No. persons exposed to risk during period

Strictly new cases Refers to specific time period e.g. year,

lifetime.

Example of Incidence

6184 cases of OCD in a blantyre district population of 150,000

= 6184/150,000

= 0.0412

= 41.2 per 1,000 population or 4.12%

Cumulative incidence (or risk)

The proportion of persons in population initially disease free who develop the condition during a specified time interval

=

No new cases of disease in time period

No. disease- free persons at the beginning of that time period

Rate as cases per 1000 population

Cumulative Incidence

Can be interpreted as the probability, or risk, that an individual will develop a disease during a specified time frame

Assumes the entire population at risk at the beginning has been followed up for specified time period

Measures denominator only at beginning of the study

Other measures of incidence Incidence Rate

Takes into consideration that some participants will be lost to follow up – and that length of follow up varies: calculates time at risk: the sum of the time that each person remained at risk of becoming a case

Incidence Rate

No. new cases in given time period

Total person-time at risk during that period

Example of incidence rateNo. cases of schizophrenia in BT district 2004-2008 = 150

Population Mid-2006 = 22,554

Estimated total person years at risk=

5 (years) x 22,554 = 112,770 person years

Mean annual incidence rate of schizophrenia

= 150/112,700

= 1.3 per 1,000 person-years

Other measures of incidenceOdds of Disease The odds of disease to non-disease

=

No. new cases in given time period

No. persons who did not become a case in that time period

Denominator is all people who are NOT cases

Example of odds of disease10 women at HIV clinic – all tested

3 test positive

7 test negative

Odds = 3/7 = 0.43

Incidence rate

For each individual in the population the time of observation is the period that the person remains disease-free: person-time incidence rate

Denominator: sum of all disease-free person-time periods during the period of observation of population at risk

As can be hard to define disease-free periods: often approximate- : average size of study population x time period

Incidence, prevalence and duration of disease

Steady state population: where no. people with/without disease remain stable

Point ≈ Incidence rate + mean duration of prevalence disease

Provided prevalence is <0.1

Useful rule of thumb for estimating prevalence in steady state populations

Risks vs. Odds

Assume entire population has been followed over a specific time – are cumulative

Rates- more accurate measure of disease over timeAccount for ‘at risk’ time which may be

variable

Measures of exposure effectMeasure of association between risk factor (exposure) and effect (outcome)

This comparison can be summarised by measures of relative risk

Examines the likelihood of developing outcome in the exposed individuals relative to those unexposed or the difference between the two

Relative measures of exposure effect

3 types of relative measuresRisk ratio = risk(cumulative incidence) in exposed

risk (cumulative incidence in unexposed

Rate ratio = Incidence rate in exposed group

Incidence rate in unexposed group

Odds ratio = Odds of disease in exposed group

Odds of disease in unexposed group

Relative Risk

Measures aetiological strength

Value of 1 : exposed = unexposed Incidence of disease in exposed and

unexposed is the same No association between exposure and

outcome

Value > 1: positive association between risk fx and outcome (increased risk)

Value <1 :negative association (decreased risk/protective)

Relative Risk

Risk ratio of 2: exposed group twice as likely as unexposed group to get outcome

Risk ratio of 0.5 = exposed group is 50% less likely (half as likely) than unexposed group to get outcome

If disease is rare and studies appropriately designed, then

Odds Ratio ≈ Risk Ratio ≈ Rate Ratio

Odds ratios and rate ratios – used most often in epidemiology

Making absolute comparisons

Risk difference

Excess risk – the difference in rates of occurance between exposed and unexposed groups

= risk in exposed - risk in unexposed

Rate difference

= rate in exposed - rate in unexposed

Nb must be comparable populations

Attributable risks

The proportion of all cases that can be attributed to the exposure

Attributable risk = Risk difference

Incidence amongst exposed population

The proportion of disease in the specific population that would be eliminated if the exposure were eliminated

Useful for assessing priorities for public health action

Population attributable risk The incidence of a disease in a population that

is associated with exposure to a particular risk factor

The proportion by which incidence rate of outcome in whole population would be reduced if exposure were eliminated

= Incidence (population) – Incidence(unexposed)

Incidence (unexposed) group

Which measure for which study?Cross sectional studies:

Prevalence ratio and odds ratio of prevalent cases in different groups

Cohort studies/ Longitudinal intervention studies

Risk ratio, rate ratio and disease odds ratio

Case control studies

Cannot calculate incidence, can calculate odds of exposure in cases vs controls: Odds ratio of exposure, which is equivalent to odds ratio of disease

Other measures

Case Fatality Measure of disease severity Defined as proportion of cases with a specific

condition who die within a specified time. (%)

Case Fatality (%) =

No. deaths of diagnosed cases in a given period

No. diagnosed cases in same period X 100

Adult mortality rates

The probability of dying between ages of 15 and 60 years per 1,000 population

Enables comparison between countries

Crude mortality rate =

No deaths during specific period

No. persons at risk of dying during same period

Mortality Rates

ICD-10 classification of causes Verbal autopsy- indirect way of

ascertaining cuase of death from information on signs, symptoms and circumstances preceding death.

Used mainly in demographic surveillance and sample registration systems.

Challenges with mortality rates

Biases in diagnosis Incorrect or incomplete death certificates Misinterpretation of ICD-10 rules for

selection of underlying cause Variation in use of coding categories for

unknown and ill-defined causes

Mortality recording Certificates may not be complete Poorer segments of population may not be

covered Death may not be reported for

cultural/religious reasons Age at death may not be accurate Late registration Missing data Errors in reporting or classifying cause of

death

What are challenges of examining suicide rates?

Thinking about article from journal club, what are the potential biases in suicide rate estimation?

Standardisation death ratesAge- standardised death rate (age adjusted rate) – summary measure of death rate that a population would have if it had a standard age structure Enables comparison between populations that

have different age structures. Can be done for other variables apart from

age/death – enables comparison where there are different basic characteristics that can influence outcome (age, gender, SES)

Standardisation methods

Direct and indirect methods

Direct standardization: Applies disease rate of population studied to a

standard population (e.g. WHO standard population)

Provides the number of cases that would be expected if the age-specific rates in the standard population were true for the study population

Using standardisation Eliminates the influence of different age

distributions (or other fx) on the morbidity or mortality rates being compared.

Country Crude death rate Age standardised rate

Brazil 79 118

Finland 240 120

USA 176 105

CAUSALITY

A cause is an event/condition/characteristic which plays an important role in producing the health outcome

Causality: 9 Bradford Hill Critera

1. Temporal relation : cause must precedes effect

2. Plausability – is association consistent with knowledge

3. Strength – What is strength of association between cause and effect (relative risk)

4. Dose- Response Is increased exposure associated with increased effect

5. Specificity

6. Analogy - with effect of similar factors

Causality

7. Reversibility – does removal of cause reduce risk

8. Consistency – several studies give same result

9. Study design quality: experimental evidence

Does inevitable involve (subjective) judgement of the evidence

References

Basic epidemiology (2nd Edition): R Bonita; R Beaglehole; T Kjellstrom. World Health Organisation (2006) – available in library Chapter 2: measuring health and disease