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Assessment of population health -descriptive epidemiology
Małgorzata Kowalska
Department of Epidemiology
Katowice 2015
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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.
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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
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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
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The basic triad of descriptive epidemiology
Who got a disease?
When did a person get a disease?
Where did a person get a disease?
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Person
• age
• gender
• ethnicity
• marital status
• occupation
• socio-economic status
• behavior
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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
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Time
• changing or stable
• short-term changes (daily, hour’s)
• seasonal variation
• other cyclic or secular changes
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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
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Place• country
• province
• city
• village
• communicity
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Environmental health inequalities in Europe. WHO 2012
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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
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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
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www.who.int
Health for All Database
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Measuring frequency of diseases
• Incidence
• Prevalence
according to L. Gordis, 2004
1
2
34
5
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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)
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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
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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
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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.
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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
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Population – age pyramids
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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
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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
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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
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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
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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
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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
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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
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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
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Disability adjusted life years
according to CDC data
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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
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According to International Organization for Migration, www.iom.int
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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)
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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
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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
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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
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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
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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?
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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.
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Human Development Index
HALE (1/3)
GDP (1/3)
Educational
Level
(1/3)
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HDI
• Low : 0 – 0,499
• Medium: 0,500 – 0,799
• High: 0,800 – 0,899
• Very high: 0,900 +
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Human Development Index
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2009
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Analytic epidemiology– basic triad
AGENT
HOST
ENVIRONMENT
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Bibliography
Available
http://apps.who.int/iris/bitstream/10665/43541/1/9241547073_eng.pdf