k6.risk

Populasi dan Sampel

Fotarisman ZaluchuPutri Eyanoer, MD.,Ms.Epi.,Ph.D.

Presenter

Presentation Notes

For Corporate Training & Presentation Services, Call : 087-8816-000-78 e-mail : [email protected]

Populasi dan Sampel

Fotarisman Zaluchu

The likelihood of people exposed to ‘risk factors’ will subsequently develop a particular disease

NO RISK= 0RISK PRESENCE = 1

Prepared by.Putri Eyanoer,MD.,Ms.Epi.,Ph.D

Presenter

Presentation Notes


HELP

HEALTHY

SICK

RISK FACTORS

PROBABILITY

Populasi dan Sampel

Fotarisman Zaluchu

Long latency diseasesFrequent exposures to risk factorsLow incidence of diseaseSmall riskCommon diseaseMultiple cause and effects

PredictionCauseDiagnosis


Presenter

Presentation Notes


Populasi dan Sampel

Fotarisman Zaluchu

Experiments take decadesUn-ethical to impose exposureReluctantly responds


Presenter

Presentation Notes


Populasi dan Sampel

Fotarisman Zaluchu


Presenter

Presentation Notes


Populasi dan Sampel

Fotarisman Zaluchu

CASE CONTROL COHORT


Presenter

Presentation Notes


Informative: estimates the association between an exposure & the risk of developing a diseaseAccomplish by:

Calculating the ratio of the measures of disease frequency for the 2 populationCalculating the difference between the 2 population


contingency table of case control study

MCI (+) MCI (-) TotalOC use (+) 23 304 327

OC use (-) 133 2816 2949

total 156 3120 3276

contingency table of cohort study

bac (+) bac (-) TotalOC use (+) 27 455 482

OC use (-) 77 1831 1908

Total 104 2286 2390


contingency table of case control study

Disease(+) Disease(-) Person- time unit

Exposure(+) a -- PY1

Exposure (-) c -- PY0

Total a+c PY1+PY0

CHD(+) CHD(-) Person-time unit

HRT(+) 30 -- 54,308.7HRT (-) 60 -- 51,477.5

Total 90 105,786.2


Estimates the magnitude of an association between exposure & disease & indicates the likelihood of developing the disease in the exposed group relative to those who are not exposed The ratio of incidence in the exposed (Ie)divided by the corresponding incidence in the unexposed (I0)

RR = Ie = CIe = a/(a+b)I0 CI0 c/(c+d)

RR = Ie = IDe = a/(PY1)I0 ID0 c/(PY0)


RR = 1 indicates no associationIncidence rates expose = unexposed

RR > 1Indicates positive associationIncrease risk among exposed to a factor

RR < 1Indicates inverse associationDecrease risk among those exposed


In case control study:Participants selected on the basis of disease statusNot possible to calculate the rate of development of disease given the presence or absence of exposure

RR estimates by calculating the ratio of the odds of exposure among cases to control

RR ≅ OR = a/c = adb/d bc


Calculation of OR & RR from a hypothetical data of a cc-study of smoking and lung CA among 100 cases and 100 controls

Lung CA (cases)

Lung CA (control)

Total

Smoking (+) 70 30 100

Smoking (-) 30 70 100

Total 100 100 200

OR = ad = (70)(70) = 5.4 RR = a/(a+b) = 70/100 = 2.3

bc (30)(30) c/(c+d) 30/100Prepared by.Putri Eyanoer,MD.,Ms.Epi.,Ph.D

Calculation of OR & RR from a hypothetical data of a cc-study of smoking and lung CA among 100 cases and 1000 controls

Lung CA (cases)

Lung CA (control)

Total

Smoking (+) 70 300 370

Smoking (-) 30 700 730

Total 100 1000 1100

OR = ad = (70)(700) = 5.4 RR = a/(a+b) = 70/370 = 4.6

bc (30)(300) c/(c+d) 30/730Prepared by.Putri Eyanoer,MD.,Ms.Epi.,Ph.D

A measure of association that provides information about the absolute effect of the exposure or the excess risk of disease in exposed compared with unexposed‘Difference’ between incidence rates in two groups (Risk difference)

AR = Ie – I0


In cohort studyAR= CIe – CI0= a/(a+b) – c/(c+d) AR= 27/482 – 77/1908= 0.0156= 1566/105

bac (+)

bac (-)

Total

OC (+)

27 455 482

OC (-)

77 1831 1908

Total 104 2286 2390

Thus, excess occurrence of bacteriuria among OC users attributable to their OC use is 1566 per 100,000 person


AR expressed as percentageAR% = AR / Ie x 100%= (Ie – I0) / Ie x 100%= 1566/105 x 100%

27/482= 27.96%

bac (+)

bac (-)

Total

OC (+)

27 455 482

OC (-)

77 1831 1908

Total 104 2286 2390

Thus, excess occurrence of bacteriuria among OC users attributable to their OC use is 1566 per 100,000 person


AR quantifies the risk of disease in the expose group that can be considered attributable to the exposure by removing the risk of disease that would have occurred anyway due to other causeThus, no association between exposure & outcome there will be no difference between the incidence rate , AR = 0AR > 0, # of cases among exposed that could be eliminated if the exposure is eliminatedUseful as a measure of the public health impact of a particular exposure


To estimates the excess rate of disease in the total study population of exposed & unexposed individuals that is attributable to the exposure

PAR = Ir – I0the rate of disease in the population (Ir) minus the rate in the unexposed (I0)

PAR = (AR) (Pe)alternatively, multiplying the attributable risk (AR) by the proportion of exposed individuals in the population (Pe)


PAR = Ir – I0 = 104/2390 – 77/1908 = 316/105/yearPAR = (AR) (Pe)= 1565/105 x (482/2390) = 316/105/year

Thus, if OC use were stopped, the excessannual incidence of bacteriuria that could beeliminated among women in this study is316 per 100,000


PAR = Ir – I0 = 104/2390 – 77/1908 = 316/105/yearPAR = (AR) (Pe)= 1565/105 x (482/2390) = 316/105/year

PAR % = PAR/ Ir x 100 = 316/4351.5 x 100 = 7.3 %

Thus, if OC use were stopped, the excessannual incidence of bacteriuria that could beeliminated among women in this study is316 per 100,000

Thus, if OC use causes bacteria, about 7% of all bacteriuria in the study population could be prevented if OC use were eliminated


Attributable risk provides a measure of the public health impact of an exposure, assuming the association is one of a cause and effect

The magnitude of RR alone does not predict the magnitude of the AR


k6.risk

Documents

risk presence

exposure disease

oc use

particular diseaseno

measures of disease

time unitexposure

time unithrt

py1exposure c