i. sejarah epidemiology

27
EPIDEMIOLOGY 1 Oleh : NANIK SETIJOWATI

Upload: nicola

Post on 23-Feb-2016

31 views

Category:

Documents


0 download

DESCRIPTION

I. SEJARAH EPIDEMIOLOGY. Circa 400 B.C . Hippocrates attempted to explain disease occurrence from a rational rather than a supernatural viewpoint. “ On Airs, Waters, and Places,” Hippocrates suggested that environmental and host factors such as behaviors might influence - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: I. SEJARAH EPIDEMIOLOGY

EPIDEMIOLOGY 1

Oleh :NANIK SETIJOWATI

Page 2: I. SEJARAH EPIDEMIOLOGY

I. SEJARAH EPIDEMIOLOGY

Circa 400 B.C. Hippocrates attempted to explain

disease occurrence from a rational rather than a supernatural viewpoint.

“On Airs, Waters, and Places,” Hippocrates suggested that environmental and host factors such as behaviors might influence

the development of disease.

Page 3: I. SEJARAH EPIDEMIOLOGY

Con’t..SEJARAH EPIDEMIOLOGY TAHUN 1662 John Graunt, a London haberdasher and

councilman who published a landmark analysis of mortality data in 1662. This

publication was the first to quantify patterns of birth, death, and disease occurrence, noting

disparities between males and females, high infant mortality, urban/rural differences, and seasonal variations.

Page 4: I. SEJARAH EPIDEMIOLOGY

Con’t..SEJARAH EPIDEMIOLOGY TAHUN 1800 William Farr built upon Graunt’s work by systematically collecting and analyzing

Britain’s mortality statistics. The father of modern vital statistics and surveillance, developed many of the

basic practices used today in vital statistics and disease classification. He concentrated his efforts on collecting

vital statistics, assembling and evaluating

those data, and reporting to responsible health authorities and the general public.

Page 5: I. SEJARAH EPIDEMIOLOGY

Con’t..SEJARAH EPIDEMIOLOGY

TAHUN 1854 In the mid-1800s, an anesthesiologist named

John Snow was conducting a series of investigations in London that warrant his being considered the “father of field epidemiology.”

Twenty years before the development of the microscope, Snow conducted studies of cholera outbreaks both to discover the cause of disease and to prevent its recurrence.

Because his work illustrates the classic sequence from descriptive epidemiology to hypothesis

generation to hypothesis testing (analytic epidemiology)

Page 6: I. SEJARAH EPIDEMIOLOGY
Page 7: I. SEJARAH EPIDEMIOLOGY

Con’t..SEJARAH EPIDEMIOLOGY

19 th and 20 th centuries In the mid- and late-1800s, epidemiological

methods began to be applied in the investigation of disease occurrence. Then Epidemiology has been

applied to the entire range of health-related outcomes, behaviors, and even knowledge and attitudes.

In the The studies by Doll and Hill linking lung cancer to smoking.

Page 8: I. SEJARAH EPIDEMIOLOGY

Epidemiology :

is the study (scientific, systematic, data-driven) of the distribution (frequency, pattern) and determinants (causes, risk factors) of healthrelated states and events (not just diseases) in specified populations (patient is community, individuals viewed collectively), and the application of (since epidemiology is a discipline within public health) this study to the control of health problems.

Page 9: I. SEJARAH EPIDEMIOLOGY

EPIDEMIOLOGY

Definisi : Ilmu yang mempelajari

frekuensi dan distribusi penyakit/

kejadian berdasarkan orang,

tempat dan waktu Ada 2 pembagian :

1.Deskriptif2.Analitik

Page 10: I. SEJARAH EPIDEMIOLOGY

EPIDEMIOLOGY DESKRIPTIF

Mempelajari Karakteristik kejadian kesehatan berdasarkan :

1. Orang : - KARAKTERISTIK MENETAP (USIA, SEX, RAS, DLL).

- KARAKTERISTIK YANG DIDAPAT (KEKEBALAN, STATUS

PERNIKAHAN, DLL). - AKTIVITAS (PEKERJAAN,

AKTIVITAS WAKTU SENGGANG,

PENGGUNAAN OBAT/ROKOK/MINUMAN, DLL). - KONDISI DIMANA MEREKA HIDUP

(ST. SOSEK, PELAYANAN KESEHATAN,

DLL).

2. Tempat : - KEADAAN GEOGRAFIS -BATAS ADMINISTRATIF / POLITIK

3. Waktu : - SEASONALITY

- DAY OF WEEK & TIME OF DAY ** - EPIDEMIC PERIOD - SECULAR (LONG-TERM) TRENDS

Page 11: I. SEJARAH EPIDEMIOLOGY

CONT’…EPIDEMIOLOGY DESKRIPTIF

Statistik yang biasa dipakai adalah : statistik deskriptif.

Statistik deskriptif menghitung: frekuensi, terdiri dari:

1. Presentile (kuartil, cut point), 2. Central tendency (mean, median , modus) 3. Dispersion (SD, Variance, range, minimum, maximum, SE mean) 4. Distribusi (Skewness, Kurtosis)

Page 12: I. SEJARAH EPIDEMIOLOGY

EPIDEMIOLOGY ANALITIKUntuk mengetahui hubungan

antara exposure (cause) dan outcome (efek) serta untuk menguji hipotesa tentang hubungan kausal.

Biasanya ditandai dengan pertanyaan why atau how

Ada 2 yang dipelajari : 1. observasional 2. Experimental

Page 13: I. SEJARAH EPIDEMIOLOGY

CONT’…EPIDEMIOLOGY ANALITIK

1. OBSERVASIONAL : a. Crossectional b. Case control c. Cohort

2. EKSPERIMENTAL : a. Kuasi ekperimental b. True eksperimental

Page 14: I. SEJARAH EPIDEMIOLOGY

DASAR-DASAR STATISTIK

Page 15: I. SEJARAH EPIDEMIOLOGY

Jump to first page

HUBUNGAN ANTAR VARIABELBagaimana membuktikannya ?

KONSEP DASAR : Bila sebuah variabel X memiliki hubungan atau

ke-terkaitan dengan variabel Y, maka setiap perubahan nilai X akan segera diikuti oleh perubahan pada nilai Y.

Variabel X = Independent; Y= Dependent If X(X1,X2 .. Xn) Y (Y1, Y2 .. Yn), then:

X1 X2 Y1 Y2; Xn-1 Xn Yn-1 Yn Distribution of Y values of X1 X2 .. Xn

Page 16: I. SEJARAH EPIDEMIOLOGY

Jump to first page

CONTOH-1 Jenis Kelamin berpengaruh terhadap resiko

Incidence Osteoporosis pada lansia Bila benar, seharusnya :

Incidence Osteoporosis penduduk lansia laki-laki berbeda secara nyata dibanding incidence osteoporosis pada penduduk lansia perempuan.

osteoporsehat

OSTEOPNORMAL

LAKI-LAKI PEREMPUAN

Page 17: I. SEJARAH EPIDEMIOLOGY

Jump to first page

CONTOH-2 Tingkat pendidikan ibu berpengaruh terhadap

paritas anak ibu usia menopause. Bila benar, seharusnya :

Rata-rata jumlah anak ibu-ibu pendidikan SD Ibu berpendidikan SLTP Ibu berpendidikan SLTA+

00,5

11,5

22,5

33,5

44,5

RATA2 PARITAS

SDSLTPSLTA+

Page 18: I. SEJARAH EPIDEMIOLOGY

Jump to first page

CONTOH-3 Tingkat paritas ibu berpengaruh terhadap

tingkat kematian bayi (IMR) Bila benar, seharusnya :

Semakin tinggi rata-rata paritas ibu usia 45+ maka IMR juga semakin tinggi

0255075

100125150175200

0 2 4 6 8 10

PARITAS

IMR

GARISREGRESI

Page 19: I. SEJARAH EPIDEMIOLOGY

Jump to first page

CARA MEMBUKTIKAN HUBUNGANANTAR 2 VARIABEL (BIVARIAT)

Membandingkan distribusi variabel dependen (Y) pada setiap nilai variabel independen (X) Beda Proporsi (X & Y berskala nominal) Beda Rerata (Mean) (X nominal, Y Interval)

Menghitung Koefisien Korelasi dan regresi setelah memperhatikan pola hubungan pada Scatter Plot Diagram

Page 20: I. SEJARAH EPIDEMIOLOGY

Jump to first page

JENIS-JENIS KORELASI ?

010203040

0 2 4 6 8

X

Y

r + positip

010203040

0 2 4 6 8

X

Y

r - negatip

010203040

0 2 4 6 8

X

Y

r=O, no correlation

Page 21: I. SEJARAH EPIDEMIOLOGY

Jump to first page

BESARAN KOEFISIEN KORELASI

0

20

40

60

0 2 4 6 8 10

r = 0.7

0

20

40

60

0 2 4 6 8 10

r = - 1.0

0

20

40

60

0 2 4 6 8 10

r= -0.3

Page 22: I. SEJARAH EPIDEMIOLOGY

Jump to first page

MAKNAKOEFISIEN KORELASI

Hubungan nyaris SEMPURNA LINIER (r = +1.0 atau r = -1.0)

Hubungan nyaris TAK ADA (r = 0.0) Hubungan kuat ( 0.7 r 0.9) Hubungan sedang (0.4 r 0.6) Hubungan lemah (0.1 r 0.3)

Page 23: I. SEJARAH EPIDEMIOLOGY

Jump to first page

Apakah setiap ada hubungan/asosiasi merupakan

sebab-akibat ?

Antar dua variabel bisa : Tidak ada hubungan (asosiasi) Ada Hubungan (Asosiasi)

Hubungan Palsu (spurious association) Hubungan Kebetulan (accidental

association) Hubungan kausal (causal association)

Page 24: I. SEJARAH EPIDEMIOLOGY

Jump to first page

5 - SYARATHUBUNGAN KAUSAL

· Statistical Association· Temporal Association

· Scientific Plausibility·Repeatability (Consistency)

·Universality

Page 25: I. SEJARAH EPIDEMIOLOGY

Jump to first page

Bisakah variabel dependen dipengaruhi

lebih dari 1 var Independen ?

Kausa tunggal, efek tunggal Kena api, Kulit melepuh

Kausa tunggal, efek ganda (multiefek) Jatuh dari pohon, fraktur kaki, kulit lecet, comotio

cerebri Multi kausa, efek tunggal

Jenis Kelamin & Usia, osteoporosis Multi kausa, multi efek

Miskin, kumuh, tak sekolah, TBC paru, kurang gizi

Page 26: I. SEJARAH EPIDEMIOLOGY

Jump to first page

RINGKASAN Variabel kependudukan sangat terkait erat de

ngan variabel kesehatan masyarakat; Hubungan dua variabel dapat dibuktikan mela

lui : Beda distribusi atau Koefisien Korelasi, baik secara tabular atau grafis;

Hubungan 2 variabel : +, -, 0 Hubungan antar variabel tidak selalu hubungan

kausal; Ada 5 Syarat dikatakan sebagai Hubungan

Kausal

Page 27: I. SEJARAH EPIDEMIOLOGY

Jump to first page

WASSALAM