Assessment of population health -descriptive epidemiology

Małgorzata Kowalska

Department of Epidemiology

Katowice 2015

Definition of epidemiology

„The study of the distribution and determinants of health related states and events in populations and the application of this study to control of health problems.”

Last J.M: A Dictionary of Epidemiology. Oxford 2001.

Health assessment approach inepidemiologic studies

Health (measures of respiratory, cardiovascular, urogenital, etc. function; life

expectancy) - positive measures

Disease (recovery, impairment, disability, handicap, incidence, morbidity, death) –

negative measures

Health assessment

Descriptive epidemiology –the first step in epidemiology

We must know: where to look, what to control for and be able to formulate hypothesis compatible with laboratory evidences

The three essencial characteristics of disease we look for descriptive epidemiology – the basic triad

The basic triad of descriptive epidemiology

Who got a disease?

When did a person get a disease?

Where did a person get a disease?

Person

• age

• gender

• ethnicity

• marital status

• occupation

• socio-economic status

• behavior

Person

single

married

widowhood

divorced

separated30

35

40

45

50

55

60

65

En

vir

on

men

tal d

om

ain

QO

L

higher educationvocational education

secondary educationprimary education

42

44

46

48

50

52

54

56

58

60

62

64

En

vir

on

men

tal

dom

ain

QO

L35.9%

21.6%

44.1%

28.3%

69.9%66.5%

0

10

20

30

40

50

60

70

80

female male single married higher lower

gender marital status level of education

Frequency of negative feelings (including depression)

Kowalska 2011

Time

• changing or stable

• short-term changes (daily, hour’s)

• seasonal variation

• other cyclic or secular changes

Time

24-hour average number of death and season in the period 2001-2002, Silesia region

CVD RD sudenwinter spring summer fall

season

0

5

10

15

20

25

30

35

aver

age

daily

cou

nt o

f dea

th

new cases of pertussis per 100,000 population

HFA dB

Place• country

• province

• city

• village

• communicity

Environmental health inequalities in Europe. WHO 2012

Sources of information abouthealth status of population

• scientific research

• the aim of study and budgetprimary

• medical statistics

• the aim of study and budget, avaibility of datasecondary

Measuring frequency of diseases

• Incidence – is a measure of probability of new cases of a disease in a population at risk over the period

• Prevalence – shows a proportion of individuals in a given population who had a disease at the particular time

• International Classification of Diseases ICD-10

www.who.int

Health for All Database

Measuring frequency of diseases

• Incidence

• Prevalence

according to L. Gordis, 2004

1

2

34

5

Factors increasing the prevalence rate

Prevalence = incidence x duration of disease

• Long duration of the disease

• Prolongation of life span among cases

• Increase in number of new cases

• Inflow of cases into the area

• Outflow of health people from the area

• Inflow of susceptible subjects or those being more liable to become ill (e.g. retired, with heavy past exposure, older people)

Mortality and fatality

• Crude death rate

x k

• Specific death rates

- for specified age of population

- for gender (males or females)

- for cause (cardiovascular diseases)

• Fatality (% of deaths in patients)

Number of deaths in a given period of time

Persons at risk of dying in the same time

Underlying cause of death = disease or injury that initiated theevents reasulting in deaths

Immediate cause of death = finaldisease or condition resulting indeath

Death certificates

1• Death status

2• Cause of death

3• Identity of examined person •Underlying cause of death

•Secondary cause of death

•Immediate cause of death

Cause-effect chain leading to death

Mortality

• Standardized mortality ratio (SMR or SDR)

This is special type of risk ratio, in which the observed mortality pattern in a group of people is compared with would have been expected if the age – specific mortality rates had been the same as in a reference population.

The European and the worldstandard population structure

Lp. Age in years European standardWorld standard

1 0 1600 2400

2 1 – 4 6400 9600

3 5 – 9 7000 10000

4 10 – 14 7000 9000

5 15 – 19 7000 9000

6 20 – 24 7000 8000

7 25 – 29 7000 8000

8 30 – 34 7000 6000

9 35 – 39 7000 6000

10 40 – 44 7000 6000

11 45 – 49 7000 6000

12 50 – 54 7000 5000

13 55 – 59 6000 4000

14 60 – 64 5000 4000

15 65 – 69 4000 3000

16 70 – 74 3000 2000

17 75 - 79 2000 1000

18 80 – 84 1000 500

19 85+ 1000 500

Total 100000 100000

Population – age pyramids

Incidence & mortality – malignant neoplasmas, Poland 2005

Crude Standardized

Incidence Incidence

Male 346.6 253.6

Female 313.1 191.8

Total 329.3 214.5

Deaths Deaths

Male 276.5 197.5

Female 199.7 105.4

Total 236.9 143.0

Didkowska et al. Nowotwory złośliwe w Polsce w 2005r.

Centrum Onkologii, Warszawa 2007

Demography

• Fertility rate – number of live births per 1000 women ages 15-49 in a given year

Number of births

Number of women ages 15-49 x 1000

Yemen (1990) -238 per 1000

Czech Republic (1996) – 34 per 1000

World

0,6

0,9

1,8

2,0 2,0

1,3

0

1

2

3

1950-1955 1970-1975 1990-1995 2010-2015 2030-2035 2045-2050

Billio

ns

0

1

2

3

4

5

6

Ch

ild

ren

pe

r w

om

an

Women 15 to 49 Average number of children per woman

Source: United Nations, World Population Prospects: The 2004 Revision (medium scenario), 2005.

Number of women in their childbearingand fertility

Demography

• Infant mortality rate – number of deaths of infants under age 1 per 1000 live births in a given year

Number of deaths of infants age <1

Total live births in a given year x 1000

Demography

• Life expectancy – an estimate of the average number of additional years a person could expect to live if the age-specific death rates for a given year prevailed for the rest of his or her life

Life Expectancy at Birth, in Years

49

6772

76

6565

7780 82

75

Africa Asia Latin America

and the

Caribbean

More Developed

Regions

World

2000-2005 2045-2050

Source: United Nations, World Population Prospects: The 2004 Revision (medium scenario), 2005.

Poland 2010

F 80.6 year M 72.1 year

New coception of measurement

DALY /Disability Adjusted Life Years/ lata życia skorygowane niesprawnością

QALY /Quality Adjusted Life Years/ lata życia skorygowane jakością

DALE /Disability Adjusted Life Expectancy/ oczekiwana długość życia skorygowana niesprawnością

PYLL /Potential Years of Life Lost/ potencjalne utracone lata

życia

PEYLL /Period Expected Years of Life Lost/ okres utraconych oczekiwanych lat życia

HALE /Healthy Life Expectancy/ przewidywana liczba lat w zdrowiu

Ilkka Vohlonen /SPb 11 Dec 2007/ PYLL (E)

70 years

Standard-life to which all preventable deaths are reflected

A = Ivan died of coronary heart attack at age of 55 years

Ivan’s PYLL = 70 -55 = 15 years

B = Anna died of alcohol poisoning at age of 28 years

Anna’s PYLL = 70 – 28 = 42 years

C = Pelagiya died of stroke at age of 71 years

Pelagiya’s PYLL = 70 – 71 = 0 years

Starting point: simple calculation

Disability adjusted life years

according to CDC data

Demography

• Migration rate – shows effect of immigration & emigration on an area’s population, expressed as increase (+) or decrease (-) per 1000 population

Nb. of immigrants – Nb. of emigrants

Total populationx 1000

Sweden (1996) 0,7 person /1000 population

Romania (1996) -0,9 person/1000 population

According to International Organization for Migration, www.iom.int

Demography

• Race, ethnicity, language group

• Households (dormitories, prisons) and families (number of married couple, single-parent families)

• Urbanization and distribution (percent urban, population density)

total population (nb of person)

total land area (km2)

The main objective of the descriptiveepidemiology

• estimate the prevelance, incidence or mortality rates in various populations and their subgroups

• Time-related description of diseases

• no available description of relationships between exposure and potential health effects

Model of the descriptive study

Population Disease Exposure

N person n/N no available

we know who have a problem, when and where but we don’t know why people are sick

Objection

• use available routinely collected data

• deficiency of standardised data

• possibility of mistake in conclusions

• unsufficient to recognize real health effects, because of n.a. data of exposure

Social and environmental context –specific for the regions

• Biological, chemical and physical structure of natural environment

• Social status determines nutrition habits, life style and sanitary conditions in a given area

Migrants in epidemiologic analysis

Why the frecquency of gastric cancer and mortality from cancer are higher in first generation of migrants from Japan than in rest population in USA?

• environmental factors?

• different life style?

• genetic background?

Evidences

The second generation of Japanase migrants to the USA is becoming similar to the local populations in terms of disease incidence rates.

Genetic factors do not explain the differences observed across the countries.

Human Development Index

HALE (1/3)

GDP (1/3)

Educational

Level

(1/3)

HDI

• Low : 0 – 0,499

• Medium: 0,500 – 0,799

• High: 0,800 – 0,899

• Very high: 0,900 +

Human Development Index

2009

Analytic epidemiology– basic triad

AGENT

HOST

ENVIRONMENT

Bibliography

Available

http://apps.who.int/iris/bitstream/10665/43541/1/9241547073_eng.pdf