Mesuring Risk in Epiemiology Trnsript Mesuring Risk in Epiemiology Welome to Mesuring Assoition n Risk in Epiemiology. My nme is Jim Gle. I m professor emeritus in the Deprtment of Epiemiology t the University of Wshington Shool of Puli Helth n Community Meiine. I spent 12 yers s lol helth offier in Kittits County, Wshington, n hve lso een US Puli Helth Servie Epiemi Intelligene Servie offier. Aout this Moule This moule n others in the epiemiology series from the Northwest Center for Puli Helth Prtie re intene for people working in the fiel of puli helth who re not epiemiologists ut woul like to inrese their fmilirity with n unerstning of the si terms n onepts use in epiemiology. Before you go on with this moule we reommen tht you eome fmilir, if you hven t lrey, with the mteril presente in the following moules, whih you n fin on the Center s We site: Wht Is Epiemiology in Puli Helth? Dt Interprettion for Puli Helth Professionls Stuy Types in Epiemiology It is prtiulrly importnt to unerstn the onepts of rtes, rtios, n mesures of isese frequeny, suh s iniene rtes n eth rtes. These onepts re overe in the moules Wht is Epiemiology in Puli Helth Prtie? n Dt Interprettion for Puli Helth Professionls. If you wnt to review efinitions of epiemiologil terms, you my ess the glossry t ny time from the tthments link t the top of the sreen. You n lso fin the trnsript in the tthments. You my wnt to print opy now n mke notes on it s you go through the moule. Lerning Ojetives In this moule we will explore the mening of risk n ssoition n their reltionship to iniene rtes in epiemiology. We will lso look t mesures of risk n their use n limittions in onsiering usl reltionships. By the en of this 45-minute moule you shoul e le: To efine risk s it is use in puli helth prtie Northwest Center for Puli Helth Prtie 1
Mesuring Risk in Epiemiology Trnsript To ientify mesures of ssoition n risk s they re use in epiemiology To interpret reltive risk n os rtios n e fmilir with their lultion using 2x2 tles, n To interpret the following mesures of risk ifferenes: ttriutle risk, popultion ttriutle risk, n popultion ttriutle risk perent. Defining Risk Epiemiologists use the term risk to men the proility of n outome (often negtive outome) in speifie perio of time. In epiemiology, risk usully implies quntifile onept, suh s the risk of ying or the risk of hert ttk, rther thn more generl onept suh s the risk of offening someone y speking frnkly. In this moule, I will use risk, proility, n likelihoo interhngely, sine they re mesure the sme wy. Why is it importnt to know out risk? In the prtie of puli helth, we re fe with mny hoies. A quntittive estimte of risk is useful in mking eisions out ourse of tion or intervention s well s how to llote finite resoures of time n money. Risk vs. Assoition In epiemiology, n ssoition mens orreltion, often etween n exposure n n outome. I like to puse for moment to tlk out orreltion n ustion. Correltion is the sitution in whih two or more vriles, in this se exposure n outome, hnge t the sme time. For exmple, s exposure to the sun inreses, the iniene of some types of ner inreses. It s importnt to rememer tht just euse oth vriles hnge, it oes not men tht one uses the other to hnge. In other wors, orreltion oes not equl ustion. Some other unknown ftor my e using oth the exposure n the outome to hnge. Deiing the egree to whih n ssoition might e usl, oupies gret el of n epiemiologist s thinking n effort. Where n ssoition is thought to e usl, s in the ssoition etween smoking n lung ner, we often use the term risk ftor in referring to the exposure we re ompring. Mesures of ssoition refer to speifi mthemtil expressions tht mesure the egree to whih n exposure, suh s exerise or smoking, is ssoite with n outome of interest, suh s helth sttus or isese. Some mesures of ssoi- Northwest Center for Puli Helth Prtie 2
Mesuring Risk in Epiemiology Trnsript tion we ll explore lter in this moule re reltive risk, os rtio, ttriutle risk, risk ifferene, popultion ttriutle risk, n popultion ttriutle risk perent. Now we ll puse for the first of severl intertive exerises tht will llow you to nswer questions out the mteril we hve just overe. Plese note tht the exerises n tke severl seons to lo. Rtios, Proportions, n Rtes Before we go ny further, let s review three terms we ll e using in this moule: rtios, proportions, n rtes. A rtio ompres two issimilr things y iviing one quntity y nother. For exmple, sy group of people hs 5 women n 7 men. The rtio of women to men is 5 to 7. We n lso express the reltionship of women to the entire group s proportion, or perentge, of the totl numer of people. A proportion or perentge is speil kin of rtio, euse the group ffete, or the numertor, must ome out of the popultion t risk, whih is the enomintor. For exmple, our group ontins 12 people. The proportion of women in the group is 5/12. We n lso express this frtion s 42 per 100, or 42%. The vlue of proportion never exees 1, or 100 perent. A rte is lso written s numertor n enomintor, ut rte hs n element of time. You will often see person-yers use s enomintor in lulting rtes. A multiple of 10 is often use to rete numertor with t lest one numer to the left of the eiml point. For exmple, the risk of ying lst yer from stomh ner my e 0.000023. However, for most people, it s esier to think out this rte when it is expresse s 2.3 eths per 100,000 per yer. Rtes n e written in severl wys. For exmple, the rte of 8 eths per 100,000 from suiie in 20 to 24 yer ols in Oregon in 1995 oul lso e expresse in these wys. If you wnt to review the rithmeti of ounts, numertors, enomintors, rtios, proportions, n rtes, they re well overe in slies 11 through 14 in the moule Dt Interprettion for Puli Helth Professionls. Before we go on to look t mesures of risk, or mesures of ssoition s we usully ll them, we shoul lso look t tool often use in lulting these mesures, the 2 y 2 tle. Northwest Center for Puli Helth Prtie 3
Mesuring Risk in Epiemiology Trnsript 2 x 2 Tles Epiemiologists use 2 y 2 tles, whih re lso sometimes lle ontingeny tles, to reor n nlyze the reltionship etween vriles. Sine we re often ompring two exposures n two sttes of illness, the 2x2 tle hs four ells, or options. The usul formt of the tle is to list the outomes or isese tegories in the vertil olumns, n the exposures, or ttriutes, in the tle rows. In this exmple, we ll lel the exposure rows expose n non-expose, n we ll lel the outome olumns, sik n well. Just for this exmple, we ll represent the ounts in the four ells s,,, n. A key point to rememer out 2x2 tles is tht the t in the ells re tul ounts, not rtes. As you go through the moule, you ll see how to use 2x2 tle to lulte vrious mesures of ssoition n risk. Dt Soures for Clulting Risk As I mentione efore, risk is the sme s the proility, hne, or likelihoo tht something will hppen. Risks n e inferre from pulishe eth rtes, from iniene rtes from n existing isese registry, suh s ner registry, or from ttk rtes from n outrek investigtion. But more frequently speil stuies, suh s ohort stuies, must e rrie out to etermine these rtes in popultions tht re or re not sujet to speifi exposures. The wy in whih we lulte risk epens on the type of stuy we onut. (For more informtion out these stuy types, see the moule Stuy Types in Epiemiology.) An iniene rte is the numer of new ses of illness ourring in popultion over speifi perio of time, usully yer, ivie y the totl popultion t risk. An ttk rte is speifi form of n iniene rte, initing the iniene of isese in popultion uring n epiemi or outrek, usully less thn yer. A eth rte is the numer of eths (in generl, or ue to speifi use) in popultion uring speifi time (usully yer) ivie y the totl popultion. Northwest Center for Puli Helth Prtie 4
Mesuring Risk in Epiemiology Trnsript A Prolem with Proportions I like to emphsize n importnt point. As you interpret reports or news stories, lwys sk yourself if sttements implying risk re se on rtes. In prtiulr, t from suh soures s in-ptient reors of hospitls must e interprete with ution, sine you usully o not know the popultion from whih eh group omes. The report is proly se on only proportion of ses within one fility, not on ll persons t risk in efine popultion. It woul e very iffiult to efine the popultion from whih these ifferent ge groups re rwn, exept uner speil irumstnes. To mke this point lerer, let s look t this list of hypothetil ses of stroke. It might e tempting to sy tht the risk of ying is highest in the 60 to 69 yer ge group. But we on t know the numer of persons t risk in eh ge tegory; tht is we n t efine the enomintors to lulte risks for ny of the ge tegories. Although we my know in generl, tht strokes inrese with ge, we ouln t use the t in this list to reinfore tht ssumption, euse there oul e lterntive resons for the numer of strokes. All the younger persons my hve left the ommunity for work elsewhere, for exmple, whih woul men tht the enomintors woul e smller, ut the rtes might e higher. The point I m mking is lwys to notie whether report uses proportions or rtes when tlking out risk. Keep in min tht proportions nnot e use to mke sttements regring risk. Let s puse now so you n nswer some more questions out wht you hve just lerne. Prtie: Rtios, Proportions, n Rtes Exerise 1 Reltive Risk (RR) Reltive risk is the first mesure of ssoition we will onsier. It is rtio of the risk of n event (or of eveloping isese) in two groups: persons who re n who re not expose to some ftor. It n e expresse, or written, s the iniene in the expose ivie y the iniene in the non-expose. The size of the reltive risk is one of the riteri we use in estimting the strength of usl reltionship etween n exposure n n outome. The lrger the reltive risk, Northwest Center for Puli Helth Prtie 5
Mesuring Risk in Epiemiology Trnsript the stronger the eviene is for usl reltionship, ll other things eing equl. For exmple, reltive risk of 10 provies etter eviene for usl reltionship thn woul reltive risk of 3. But rememer, lrge reltive risk lone oes not estlish usl reltionship. If the reltive risk is equl to 1, we sy there is no eviene of n ssoition. If the reltive risk is greter thn 1, thn the exposure is hrmful, n if the reltive risk is signifintly less tht one, we n sy there is eviene tht the exposure my e protetive. Now let s look in etil t how you lulte reltive risk. Clulting Reltive Risk As I si, we lulte reltive risk y iviing the iniene in the expose group y the iniene in the nonexpose groups. In this fititious exmple of ohort stuy, we foun tht in ftory of 3000 workers, 1000 workers were expose to toxi sustnes, n 2000 were not. We ll use this 2x2 tle to lulte the reltive risk of eveloping lung isese mong expose workers ompre to unexpose workers. During the stuy perio, 800 of the expose workers evelope some type of lung isese, n only 40 of the non-expose workers evelope lung isese. The iniene of lung isese uring the stuy perio mong expose workers ws 800 per 1000 person per yer. The iniene of lung isese mong nonexpose workers uring this time ws 40 per 2000. So tht we hve omprle rtes, we ll onvert this to 20 per 1000. By sutrting oth 800 n 40 from their respetive row totls, we n get the numer of persons with no lung isese in eh exposure row. Note tht the iniene in expose workers ws 800/1000, or 80%. The iniene in those not expose ws 40/2000, or 2%. Compring the iniene in the expose to the iniene in the non-expose, we get 80/2, for reltive risk of 40. We oul lso sy tht workers expose to toxi sustnes woul e forty times more likely thn non-expose workers to evelop lung isese. This elevte reltive risk strongly suggests, ut oes not prove, usl reltionship etween exposure to this toxi sustne n eveloping lung isese. Notie tht this is n exmple of ohort stuy. In se-ontrol stuies, reltive risk nnot e lulte iretly. It must e estimte using n os rtio. We ll isuss os rtios lter on in this moule. Northwest Center for Puli Helth Prtie 6
Mesuring Risk in Epiemiology Trnsript Reltive Risk Review Let s review few key points out reltive risk. Reltive risk is the likelihoo of n event in people who re expose to some ftor ompre to the likelihoo in nother group tht is not expose. Reltive risk is rtio of two iniene rtes. To lulte it, you ivie the iniene in the expose y the iniene in the non-expose. Erly in my work s n epiemiologist, I ws prt of tem investigting lrge outrek of St. Louis enephlitis, known s SLE, in Houston, Texs. This serious illness is trnsmitte through the ite of mosquito. We foun tht the iniene of SLE in people living in entrl Houston who were more likely to e expose to stning wter, where mosquitoes oul ree, ws 13 times the iniene in people living in neighorhoos on the outskirts of the ity who h little or no exposure to stning wter. After lulting the reltive risk of SLE reltive to exposure to stning wter, we onlue tht euse the reltive risk ws higher in the entrl prt of the ity, those neighorhoos might enefit from sprying with hemils to kill mosquito lrve. Let s puse now so you n nswer some more questions on wht you hve just lerne. Prtie: Clulting Reltive Risk (prt 1) Prtie: Clulting Reltive Risk (prt 2) Exerise 2 Attriutle Risk (AR) Rememer tht reltive risk is the likelihoo of n event (or of eveloping isese) in persons who re expose to some ftor, s ompre to nother group whih is not. Attriutle risk is more onrete. It is expresse s n solute rte of isese, rther thn s rtio. It s the rte, or iniene, of isese in n expose group tht is ttriutle to the exposure. Attriutle risk in n expose group gives us the solute mount of isese (or the numer of ses) resulting from the exposure. We express it s ses per multiple of the popultion. We n Northwest Center for Puli Helth Prtie 7
Mesuring Risk in Epiemiology Trnsript use ttriutle risk to etermine the mount of isese tht oul theoretilly e eliminte or prevente y removing the exposure in the expose popultion. Clulting Attriutle Risk We lulte ttriutle risk y sutrting the iniene in the unexpose from the iniene in the expose. Let s look t the exmple of ftory workers expose to toxi sustne n who evelop lung isese to see how this works. Rememer, in our fititious ohort stuy, 800 of the expose workers evelope some type of lung isese uring the stuy perio, n 40 of the non-expose workers evelope lung isese. So the iniene of lung isese mong expose workers ws 800/1000 n the iniene in non-expose workers ws 40 per 2000. Sine we hve to use iniene rtes with the sme enomintors, we ll onvert this to 20 over 1000. Plugging these numers into the ttriutle risk eqution, we get n ttriutle risk of 780 ses of lung isese per 1000 ftory workers expose to the toxi sustne ttriutle to their exposure. Attriutle risk n e use to unover unsuspete fetures of ssoitions etween exposures n iseses. Let s look t n exmple to lrify this importnt ie. Usefulness of Attriutle Risk In 1956, stuy of lung ner n smoking in British physiins reporte these results. The stuy showe tht lthough hevy smokers fe reltive risk of ying from lung ner 24 times higher thn non-smokers, they fe reltive risk of only 1.4 times of ying of hert isese, s ompre to non-smokers. Rememer, to lulte the reltive risk of eth from lung ner, you ivie the eth rte from lung ner in the hevy smokers y the eth rte from lung ner in the non-smokers; n to lulte the reltive risk of ying from hert isese, you ivie the eth rte from hert isese in the hevy smokers y tht in the non-smokers. By the wy, we use eth rtes here in the sme wy s we use iniene rtes euse they re form of iniene rte. The point I wnt to mke here is tht if we exmine only reltive risk, we ll miss ruil point. Northwest Center for Puli Helth Prtie 8
Mesuring Risk in Epiemiology Trnsript By lulting the ttriutle risk for lung ner eths in hevy smokers s ompre to non-smokers (tht is, sutrting the lung ner eth rte in the non-smokers from tht in the hevy smokers), n the ttriutle risk for eths from hert isese, we n see tht over ll, hevy smokers re more likely to ie of hert isese thn of lung ner, euse the eth rte from hert isese is muh higher thn the eth rte from lung ner in oth groups. Hert isese presumly hs mny other uses esies hevy smoking. However, if one were to eliminte smoking, the ttriutle risk tells us tht more people woul e sve from eth y hert isese thn from eth y lung ner. This informtion woul e importnt in rguing for funing ig nti-smoking mpign, sine it woul provie eviene tht mny itionl lives oul e sve y removing smoking s risk ftor for hert isese eth s well s for eth from lung ner. Attriutle Risk Review Let s review ttriutle risk efore we go on. Attriutle risk is n solute rte of isese, rther thn rtio. It s the iniene of isese in n expose group tht is ttriutle to, or thought to e use y, the exposure. The lultion is simple. We sutrt the iniene rte in the unexpose from the iniene rte in the expose. In the St. Louis enephlitis outrek in Houston tht I mentione erlier, we woul hve lulte the iniene rte of enephlitis tht theoretilly oul hve een reue y sprying mosquito lrviie in the highiniene neighorhoos n isovere tht 71 ses per 100,000 people living in the high risk res woul theoretilly hve een prevente y the sprying if stning wter were the only use of the ifferene in iniene. Let s puse now so you n nswer some questions on wht you hve just lerne. Exerise 3 Clulting Attriutle Risk Perent Sometimes it is more useful to express ttriutle risk in terms of perent, or proportion. Attriutle risk n e lulte s perentge y sutrting the risk in the unexpose from the risk in the expose n iviing the result y the risk in the expose. Here s n exmple of tht lultion using the ttriutle risks from the British stuy of eths ue to lung ner n smoking tht we just looke t. For lung Northwest Center for Puli Helth Prtie 9
Mesuring Risk in Epiemiology Trnsript ner eths, the ttriutle risk perent is 96%. This figure is known s the ttriutle risk perent in the expose. For hert isese eths, the ttriutle risk perent is 30%. When we ompre the ttriutle risk perents for eths ue to lung ner n to hert isese, it ppers tht eliminting smoking woul reue lrger perentge of eths ue to lung ner thn of eths ue to hert isese in smokers, ut s I si efore, sine the frequeny of hert isese eths in the generl popultion is so muh greter thn the frequeny of lung ner eths, more hert isese eths woul e prevente, even though the reltive risk of ying of hert isese in smokers, s ompre to non-smokers, is smller. Clulting Popultion Attriutle Risk If we know the eth rte ue to lung ner in the generl popultion n in non-smokers, we n lso lulte the risk in the generl popultion of lung ner eths ttriutle to smoking. To o this we tke the lung ner eth rte in the generl popultion n sutrt the lung ner eth rte in the non-smokers. The result is the popultion ttriutle risk (or PAR). This rte tells us the numer of lung ner eths tht woul e eliminte from the generl popultion if the exposure, in this se, smoking, were eliminte. Suppose we know tht the lung ner eth rte in the generl popultion is 62 per 100,000 persons n in non-smokers is 7 per 100,000 persons. The rte of lung ner eths in the generl popultion ttriutle to smoking is 62 minus 7 or 55 per 100,000 persons per yer. Popultion ttriutle risk is helpful for guiing puli helth eisions out where to fous resoures most effetively to protet the puli s helth. As with ttriutle risk, popultion ttriutle risk n e expresse s perent. We lulte it in wy similr to lulting ttriutle risk perent: the iniene in the generl popultion minus the iniene in the unexpose popultion ivie y the iniene in the generl popultion. Turning our smoking exmple into popultion ttriutle risk perent, we n sy tht of the 62 per 100,000 eths per yer ue to lung ner in the generl popultion, 62 minus 7 ivie y 62, or 89%, n e ttriute to smoking. Northwest Center for Puli Helth Prtie 10
Mesuring Risk in Epiemiology Trnsript In this exmple, I hve ssume tht ll persons re either smokers or non-smokers, n I hve not tken seonry smoke exposure into onsiertion. Uses of RR n PAR in PH Prtie As I mentione efore, reltive risk is importnt for inferring ustion. For exmple, puli helth reserhers looking t the use or soure of isese my use it to evlute the role of n exposure in using the isese. Popultion ttriutle risk, on the other hn, is more importnt to puli helth prtitioners n poliy mkers sine they wnt to know the numers of eths or illnesses prevente in orer to use their resoures to gretest vntge to ontrol or prevent isese in popultions in their jurisitions. The size of the prolem in tul numers ounts for muh when lloting limite puli helth resoures. Let s look t our ftory workers gin to lrify this point. Suppose the ftory is lote in ounty of 100,000 people. We know tht the reltive risk of eveloping lung isese for ftory workers expose to this toxi sustne ompre to other ftory workers is 40, s we showe erlier. This high reltive risk is very suggestive tht the exposure is usl. But how ig is this prolem in the rest of the ounty? When we lulte the ttriutle risk perent of the expose ftory workers, we get 98 perent. So we n sy tht 98 perent of the lung isese in the expose group is ttriutle to their exposure. If we ssume tht the iniene of lung isese in the rest of the ounty is the sme s tht in the non-expose ftory workers, we fin tht the overll iniene in the ommunity is 27.8 per thousn persons per yer. Keep in min tht this figure inlues the ftory workers euse they re prt of the ounty popultion. The popultion ttriutle risk is the iniene in the entire popultion (27.8 per thousn per yer) minus the iniene in the non-expose (20 per thousn per yer), or 7.8 ses per thousn persons per yer. The popultion ttriutle risk perent is the PAR ivie y the iniene in the totl popultion (2.8/27.8), or 28%. We n sy tht in this ommunity, 28% of the ses of lung isese re ttriutle to the exposure in the ftory. Expresse nother wy, if we eliminte the exposure to toxi sustnes in the ftory, we n reue lung isese in the ounty y 28%. Clerly, expose workers in the plnt hve high risk for eveloping lung isese, ut if we look t the ounty s whole, we n see tht this risk oes not onstitute s lrge puli helth prolem s the expose ftory workers ttriutle risk perent of 98 woul suggest. Northwest Center for Puli Helth Prtie 11
Mesuring Risk in Epiemiology Trnsript Mesures of Assoition Review Let s tke moment to review the mesures of ssoition we ve overe. Attriutle risk, or AR, is the solute rte of helth event in people who hve een expose to risk ftor tht is ttriutle to the exposure. We n express ttriutle risk s perentge of the overll risk y sutrting the iniene rte in the unexpose from the iniene rte in the expose, whih gives us the AR, n then iviing the resulting AR y the iniene rte in the expose. Popultion ttriutle risk, or PAR, on the other hn, tells us the mount of isese tht woul e eliminte from the generl popultion if the exposure to tht isese were eliminte. We lulte the PAR y sutrting the iniene in the non-expose from the iniene in the entire popultion. Why woul we wnt to know the popultion ttriutle risk? Beuse it n help guie puli helth eisions out where to fous resoures most effetively. In Houston, for exmple, the iniene of St. Louis enephlitis, or SLE, in the entire ity ws 34 per 100,000. We n lulte the risk of getting SLE for the generl popultion y sutrting the iniene rte in the people who weren t expose to stning wter, whih ws 6 per 100,000, from the iniene rte for the entire ity. An we get PAR of 28 ses per 100,000 people tht oul theoretilly e eliminte if stning wter were eliminte, n if exposure to stning wter ws responsile for the entire exess in SLE iniene. As with the AR perent, to turn the PAR into popultion ttriutle risk perent, we ivie the PAR y the iniene rte in the expose popultion. Let s puse now so you n nswer some questions on wht you hve just lerne. Prtie: Mesures of Assoition Exerise 4 Os Rtio (OR) So fr, the lultions we ve isusse re useful when iniene rtes (perhps from ohort stuies) re ville, sine you n lulte reltive risk iretly. However, sine ohort stuies re time-onsuming n expensive, epiemiologists often investigte ssoition Northwest Center for Puli Helth Prtie 12
Mesuring Risk in Epiemiology Trnsript n risk using t from se-ontrol stuies. Cse-ontrol stuies, though, o not proue iniene rtes, so we nnot lulte true reltive risk. Fortuntely, se-ontrol stuies n proue os rtios, whih pproximte reltive risks in ertin situtions: when the ses re from the sme popultions s the ontrols, n when the isese is reltively rre in the popultion (sy, less thn 5%). Let s use n exmple to see how to lulte os rtios. Clulting Os Rtio When we exmine the rtes of eth y suiie mong men n women living in Wshington Stte etween 2003 n 2005, we fin tht men h higher suiie rte. Suppose we hve n ie tht the higher rte in men might hve something to o with whether they were living lone. We eie to o se-ontrol stuy n interview 100 fmily memers of persons who ie y suiie in 2003 n lter, n 100 fmily memers of persons of the sme ge who i not ie from suiie. To lulte the os rtio, we multiply the numer in ell (the suiies who live lone) times the numer in ell (the non-suiies who in t live lone) n the numers in ells (nonsuiies living lone) n (suiies not living lone). We then ivie the prout y the prout. Here is the lultion. This rtio is our estimtion of the reltive risk for suiie for men living lone s ompre to men not living lone. We oul sy tht living lone inreses the risk for suiie in men y ftor of 6.8. Os Rtio Reviewe Os rtios pproximte, or llow you to estimte, reltive risk when iniene t in expose n non-expose popultions re not ville. We lso nee to mke two ssumptions: the ses re from the sme popultions s the ontrols n the isese is reltively rre in the popultion. Os rtios re lulte from se-ontrol stuies. We usully set up the t in 2x2 tle n o the lultions y ross-multiplying the t in the orner ells, n iviing the prouts. The numer of ontrols usully equls the numer of ses n re expresse in the olumn totls. In puli helth prtie, one of the most ommon uses of n os rtio is in etermining possily responsile foo item in resturnt-se foo-orne Northwest Center for Puli Helth Prtie 13
Mesuring Risk in Epiemiology Trnsript outrek. A helth eprtment investigtor questions oth ill n well people who te t the resturnt efore the eginning of the outrek. The investigtor then ompres the foo onsumption history for eh foo in people who re n who re not ill to try to ientify the foo tht might e responsile for the illness. Let s puse now so you n nswer some questions on wht you hve just lerne. Prtie: Clulting Os Rtio (prt 1) Prtie: Clulting Os Rtio (prt 2) Summry To summrize, in this moule we ve tlke out risk n ssoition s use y epiemiologists. Risk is the proility of n outome (often negtive outome) in speifie perio of time. Reltive risk is the rtio of the iniene in the expose to the iniene in the non-expose groups. Reltive risk mesures the strength of n ssoition n is useful when looking t possile uses of isese. A lrger reltive risk provies stronger eviene for usl role for the exposure ut oes not prove ustion. Attriutle risk n popultion ttriutle risk mesure the solute mount of isese ttriutle to n exposure in either the expose or totl popultion. Both n e lulte s perents. Puli helth poliy mkers use these mesures to help eie where to llote sre resoures. An os rtio is n estimte of reltive risk, using t from se-ontrol stuies. Os rtios re use when we on t hve tul iniene rtes. As with reltive risk, the lrger the os rtio, the stronger the eviene for usl reltionship etween n exposure n the outome of interest. Resoures If you woul like to lern more out the onepts in this moule, you might wnt to explore some of the resoures liste here. Now, if you re rey, plese go on to the finl ssessment. Northwest Center for Puli Helth Prtie 14