Cross Sectional (2)

7/21/2019 Cross Sectional (2)

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Cross sectional (2)

Cross-Sectional

• Instead of looking at a ratio ofprevalences, we can also look at aratio of odds.

• Odds are not intuitively appealing:tey are te likeliood of an eventoccurring divided !y te likeliood of

te event not occurring.

Cross-Sectional Studies

353588

88889595GrapGrap

TomatoTomato

(+)(+) --

DZ = RashDZ = Rash

95/183

PR= ------- =2.68/43

Odds of grape work in rash pts:(95/ 103) / (8/ 103)= 95 / 8=11.9Odds of grape work in healthy:

(88/ 123) / (35/ 123)= 88 / 35=2.5

103 123

353588

88889595GrapGrap

TomatoTomato

(+)(+) --

DZ = RashDZ = Rash

95/183

PR= ------- =2.68/43

Odds of grape work in rash pts: 95 / 8=11.9Odds of grape work in healthy: 88 / 35=2.5

Odds ratio=(95 / 8)/(88 / 35)=11.9/2.5=4.7

Cross-Secto!a" St#$es

%orma"&

400100*h

%o CDCD

Cho"estero"

100 & (100 + 400) 02,rea"e!ce Rato = --------------------- = ----= 20

50 & (50 + 450) 01

100 & (100 + 400) 02,rea"e!ce Rato = --------------------- =---- = 20

50 & (50 + 450) 01

.!terpretato!/ .! ths st#$ pop#"ato!

the prea"e!ce o CD s 2 tmes h*her amo!* those th h*h cho"estero"

compare$ to the prea"e!ce ! those

th !orma" or "o cho"estero"

Cross-Secto!a" St#$

!e"ical exam # $%rays to "iagnose

osteoarthritis of the knee

steoarthrts

- 3 4 e s t 0

Cross-Secto!a" St#$

&revalence of osteoarthritis amongobese s'b(ects: )0*+0 , 0-.

&revalence of osteoarthritis amongnon%obese s'b(ects: /0*+0 , 0-)

&revalence ratio , 0-.*0-) , /-0

Cross-Secto!a" St#$

Obese s'b(ects are to

times more likely to have

osteoarthritis of the knee

than non%obese s'b(ects-

Cross-Secto!a" St#$

hat came first2

Obesity or Osteoarthritis

Chicken or eggdilemma

Study "esign

• #$ infectioninfection, sown !y a positive skintest, usually re%ains dor%ant.&owever, infected persons sould !e

treated wit I'& to prevent future #$

diseasedisease.

• :: &ow can you deter%ine ow !ig a

pro!le% #$ infection is a%ong%igrant far% workers and if tere areany ig-risk su!groups

• *n e+a%ple fro% te literature:

#u!erculin reactivity a%ongCalifornia %igrant &ispanic far%workers.

Introduction:Introduction:• igrant far% workers at increased

risk for #$.

• etods:etods:

• Study population all residents > 1 year of age

• Brief health and work questionnaire

• Tuberculin skin test (TST) for persons

not known to be TST(+)• Followup for TST(+) as needed

•esultsesults•Se+

– ales - 2/ (/0.1)

3e%ales - 241 (14.5)•*ge

– 25.6 7 85.8 y ( ean 7 S")

•9lace of !irt – .S. - 821 (24.5) – 'on-.S. - 0// (50.8)

Multivariate odds ratios for positive TB skin test

• "iscussion"iscussion• Overall prevalence 84.4

• ;ower tan o!served in oter settings

• Increased prevalence for – en (O 8.22)

– 3S (O 0.88)

– 81-06y (O 2.16)

– 'on-S $orn (O 2.6)

• "iscussion"iscussion

• Increased risk for. . .• < en: as in oter studies

• = 81-06 yrs. < not seen in oter studies

• = 3S < not seen in oter studies

• = 'on-S $orn < as in oter studies

CRSS SCT.%6'

CRSS-SCT.%6'

ST7D.S

E- Sample selection by expos're

Example: orkers ith an" itho'texpos're to asbestos are compare" forthe sim'ltaneo's presence of l'ng cancer-

3- Sample selection by o'tcome

Example: orkers "etermine" to have ornot have l'ng cancer at a point in time arecompare" for sim'ltaneo's expos're toasbestos

4- Sample selection neither by

o'tcome nor by expos're

Example: 5ll orkers in a plant are

sim'ltaneo'sly assesse" both forasbestos expos're an" l'ng cancer

stat's-

6Sampling schemes 78 E an" 4 arelikely to be inefficient9

The act that past e:pos#re a!$ hea"th$ata are co""ecte$ $oes !ot ma;e t a

retrospecte cohort st#$

The $st!cto! s that ! the cross-secto!a" st#$ o# start th peop"e

here the are !o

.! the retrospecte cohort st#$ o# start$e!t!* peop"e ! the past eore the

o#tcomes occ#rre$

. o# start th peop"e here the are!o some are mss!* rom the cohort

as o# *ot the ro!* a!ser

Se"ecto! as/ a"asco!s$er t ! cross-secto!a" st#$es

Se"ecto! as ! cross-secto!a"Se"ecto! as ! cross-secto!a"

st#$esst#$es

• &ow did te people wo are participating in yourstudy get to !e were tey are >as it related toe+posure >as it related to disease

• *re tose wo ended up in your studyrepresentative of te source population Couldteir participation relate to e+posure Could it

relate to disease

• o# sho#"$ !ot $o a cross-secto!a" st#$ o# sho#"$ !ot $o a cross-secto!a" st#$

tho#t po!$er!* ao#t the a!sers totho#t po!$er!* ao#t the a!sers to

these >#esto!sthese >#esto!s

Sa%pling $ias in Cross-Sectional Studies

• .s st#$ pop#"ato! represe!tate o tar*etpop#"ato!? – Often use a non-pro!a!ility sa%ple: Convenience

sa%ple wit non-consecutive enroll%ent• .s there sstematc !crease or $ecrease o

cases? – ;engt-!iased sa%pling. Cases are

overrepresented if illness as long duration and areunderrepresented if sort duration (9 ? k + inc + t)

• .s there sstematc !crease or $ecrease o

e:pos#re? – 9revalence-incidence !ias. @+posure does not alterdisease risk, !ut alters disease duration.

• ↑e+posure in cases if %ild disease eg, &;*-*2• ↓e+posure in cases if rapidly fatal

" i St t i t i i i

"esign Strategies to ini%iAeSa%pling $ias

• 9opulation-!ased sa%ple – 9ro!a!ility sa%ple – 'on-pro!a!ility sa%ple

se consecutive enroll%ent if conveniencesa%ple• *dBust for seasonal or oter ti%e-dependent

trends

easure%ent $ias in Cross-Sectional Studies

Outco%e• isclassied (dead, %isdiagnosed, undiagnosed)

@+posure• "iDerential %isclassication due to recall !ias• #i%e fro% e+posure i%portant indicator of

accuracy• 'eed etiologically relevant e+posure. se current

e+posure if: – @+posure is +ed eg, !lood type – ecent e+posure correlates well wit prior e+posure – ecall of prior e+posure unlikely to !e relia!le eg, diet

Strategies to ini%iAeeasure%ent $ias

– StandardiAe %easure%ent %etods

– #rain and certify assessors

– ene te instru%ents

– Cali!rate te instru%ents

– *uto%ate te instru%ents

– ake uno!trusive %easures

– 3or key varia!les, use data fro% E 8 source

– $linding of su!Bect and o!server

I%ple%entation of tese strategies dependson i%portance of varia!le, potential eDectof inaccuracy, feasi!ility and cost.

" ' $ %

cc#pato!a" 'ea$ %e#roto:ct/cc#pato!a" 'ea$ %e#roto:ct/

a ehaora" a!$a ehaora" a!$

e"ectrophso"o*ca" ea"#ato!e"ectrophso"o*ca" ea"#ato!

• #o evaluate te eDects of cronic lead

e+posure on te nervous syste% in adults,a set of tests was ad%inistered to 66 leade+posed foundry e%ployees and 48une+posed workers.

• #is is a cross-sectional study

#ose workers wit te igest !lood lead concentrationswere

more tense

more angry more depressed more fatigued more confused

and had less vigor tan tose wit low !lood lead

Se"ecto! as?

Who choose (or are chosen for) dirty jobs?

Who stay there?Who get dirtiest on the job?

Right: Those who are tense, angry, depressed, fatigued,

confused, and have lest vigor

Kelebihan Studi Potong Lintang:

• dapat untuk melihat distribusi frekwensi penyakit dipopulasi

• dapat untuk melihat hubungan variabel “exposure”dan variabel “outcome”

• hasil analisisnya dapat dipakai untuk membangun

hipotesis baru

Kelemahan Studi Potong Lintang

• tidak dapat untuk melihat hubungan sebab akibat,

karena variabel “exposure” dan variabel “outcome”diukur secara simultan

Cross-Secto!a" St#$esStre!*ths/

@ ,ro$es prea"e!ce estmates oe:pos#re a!$ $sease or a e""-$e<!e$ pop#"ato!

@ aser to perorm tha! st#$esthat re>#re o""o-#p (he!cere"ate" !e:pe!se)

@ Ca! ea"#ate m#"tp"e rs; (a!$protecte) actors a!$ hea"th

o#tcomes at the same po!t !

Stre!*ths/@ Aa $e!t *ro#ps o perso!s

at h*h or "o rs; o $sease

@ Ca! e #se$ to *e!eratehpotheses ao#t assocato!setee! pre$cte actors a!$$sease o#tcomes

Cross-Secto!a" St#$es'mtato!s/

@ ,rea"e!t rather tha! !c$e!t(!e) cases are #se$ B thee:pos#re co#"$ e assocate$ th

s#ra" ater $sease occ#rre!cerather tha! $ee"opme!to the $sease

@ Tempora" se>#e!ce etee!e:pos#re a!$ $seaseca!!ot e esta"she$

Cross-Secto!a" St#$

Dsa$a!ta*es/

@ EChc;e! or e**F $"emma B $o!ot ;!o hether the e:pos#re

prece$e$ $sease or as aco!se>#e!ce o $sease$ee"opme!t

Cross-Secto!a" St#$

6$a!ta*es/

@ #c; eas a!$ cheap

@ Ca! st#$ m#"tp"e e:pos#res a!$$sease o#tcomes sm#"ta!eo#s"

@ Goo$ or $escr!* thema*!t#$e a!$ $str#to! ohea"th pro"ems

Cross-secto!a" St#$es

• te! #se$ to st#$ co!$to!s that arere"ate" re>#e!t th "o!* $#rato! oe:presso! (!o!ata" chro!c co!$to!s)

• .t meas#res prea"e!ce !ot !c$e!ce o

$sease• :amp"e/ comm#!t s#res

• %ot s#ta"e or st#$!* rare or h*h" ata"$seases or a $sease th short $#rato! oe:presso!

Cross-secto!a" st#$es• Dsa$a!ta*es

• ea;est oserato!a" $es*!(t meas#res prea"e!ce !ot !c$e!ce

o $sease) ,rea"e!t cases are s#rors• The tempora" se>#e!ce o e:pos#re a!$eHect ma e $Ic#"t or mposs"e to

$eterm!e• 7s#a"" $o!Jt ;!o he! $sease occ#rre$• Rare ee!ts a pro"em #c;" emer*!*$seases a pro"em

%ato!a" S#res

•6 "ar*e set o !ato!a"ep$emo"o*ca" s#res areco!$#cte$ the %ato!a"Ce!ter or ea"th Statstcs(%CS) --- the Ke$era"Goer!me!tJs pr!cpa" ta" a!$hea"th statstcs a*e!c

@ The %CS s part o the Ce!teror Dsease Co!tro" a!$

,ree!to! (CDC) B #!$er the

%ato!a" S#res

•%ato!a" ea"th .!tere S#re(%.S),r!cpa" so#rce o !ormato! o!the hea"th o the c"a! !o!-!stt#to!a"Le$ ho#seho"$pop#"ato! o the 7S

@ %ato!a" ea"th a!$ %#trto!:am!ato! S#re (%6%S)Co""ects !ormato! ao#t the

hea"th a!$ $et o peop"e ! the

%ato!a" S#res

• %ato!a" ea"th Care S#re(%CS)Co""ects a $e ra!*e o $ata

o! hea"th care #se mpact ome$ca" tech!o"o* a!$ >#a"to care pro$e$

@ %ato!a" .mm#!Lato! S#re(%.S)Co""ects !ormato! o! the

mm#!Lato! coera*e a!$

%ato!a" S#res

• %ato!a" S#re o Kam" Groth(%SKG)Co""ects $ata o! actors aHect!*

pre*!a!c a!$ ome!Js hea"th !the 7S

@ %ato!a" Aorta"t Ko""oac;S#re (%AKS)6**re*ate samp"e o $eathcert<cates across the 7S or

tar ete$ research p#rposes

%ato!a" S#res• %ato!a" Aater!a" a!$ .!a!t

ea"th S#re (%A.S)Co""ects $ata o! st#$ actorsre"ate$ to "o rthe*ht

st""rth !a!t ""!ess a!$!a!t $eath

@ ehaora" Rs; Kactor

S#re""a!ce SstemCo""ects $ata o! prea"e!ce operso!a" hea"th ehaors

amo!* a$#"ts assocate$ th

%ato!a" S#res&,ro*rams

• o#th Rs; ehaorS#re""a!ce SstemCo""ects $ata to mo!tor

prea"e!ce o ehaors !o#ths that res#"ts ! s*!<ca!tmorta"t mor$t $sa"ta!$ soca" pro"ems

@ %ato!a" ,ro*ram o Ca!cerRe*stres (%,CR)

@ S#re""a!ce p$emo"o* a!$

!$ Res#"ts (SR) ,ro*ram

ther So#rces o %ato!a" Data

• %ato!a" Mta" Statstcs Sstem--- rth $ata--- Aorta"t $ata

--- Keta" $eath $ata--- Aarra*es a!$$orces

--- '!;e$ rths&!a!t$eaths--- %ato!a" $eath !$e:

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