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A Brief Introduction to Epidemiology IV Overview of Vital Statistics

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Title: A Brief Introduction to Epidemiology IV Overview of Vital Statistics


1
A Brief Introduction to Epidemiology - IV (
Overview of Vital Statistics Demographic
Methods)
  • Betty C. Jung, RN, MPH, CHES

2
Learning Objectives
  • To understand the how vital statistics and
    demographic data are used in Public Health
  • To understand the measures of mortality,
    fertility, morbidity that are based on vital
    statistics
  • To understand the basis for Rate Adjustment

3
Performance Objectives
  • Basic understanding of how to use the most
    commonly available health statistics to quantify
    disease in Public Health Practice
  • Basic understanding of the most common vital
    statistical measures encountered in Practice

4
Introduction
  • Demographic data and vital statistics are useful
    tools in
  • Determining a communitys health status
  • Deciding whats the best way for providing health
    services
  • Planning a public health program
  • Evaluating a programs effectiveness

5
Demographic Data
  • Demographic data include those variables that
    describe the characteristics of a population
    (i.e., population size and how it changes over
    time)

6
Demographic Variables
  • Population composition include
  • Age
  • Sex
  • Income
  • Occupation
  • Health services use
  • Geographic location
  • Geographic density

7
Vital Statistics (Events)
  • Include
  • Births
  • Deaths
  • Marriages
  • Divorces

8
Sources of Vital Statistics Demographic Data
in the U.S.
  • Census
  • Registration of Vital Events
  • Morbidity Surveys

9
Demographic Data United States Census
  • The United States conducts a decennial census
    (every 10 years) since 1790. Each household and
    resident is enumerated (counted).
  • Person info sex,age,race,marital status, place
    of residence, and relationship to or position as
    head of household
  • A systematic sample of households provides
    income, housing, number of children born,
    education, employment status, means of
    transportation to work, and occupation.

10
Demographic Data United States Census
  • Census tables are published for the entire U.S.,
    each state, urbanized areas (Metropolitan
    Statistical Areas MSAs), counties, cities,
    neighborhoods (census tracts), and city blocks.

11
Demographic Data Annual Registration of Vital
Events
  • In the U.S., state laws require that all vital
    events be registered.
  • Birth certificates serve as proof of citizenship,
    age, birthplace and parentage.
  • Death Certificates - required as burial documents
    and in settlement of estates and insurance claims.

12
Demographic Data US Vital Statistics Data
  • Vital Statistics of the United States - annual -
    detailed tables of vital events by various
    demographic characteristics and major geographic
    subdivision. Data on marriages and divorces are
    collected and published in a separate volume.

13
Demographic Data US National Death Index
  • Prepared by NCHS - a nationwide, computerized
    index of death records compiled from each states
    vital statistics offices.
  • Allows researchers to decide if persons in their
    studies have died. Includes death certificate
    number, state person died in and date of death.

14
Demographic Data U.S. Morbidity Surveys
  • Morbidity data (i.e., prevalence of disease)
  • Communicable disease reports are shared through
    CDCs Morbidity and Mortality Weekly Reports
    (MMWR)
  • More serious diseases are well reported (i.e.,
    cholera,plague,yellow fever, rabies, paralytic
    polio)

15
Demographic Data U.S. Sources of Morbidity
Data
  • Reportable diseases
  • National Health Survey
  • Hospital records data
  • Industrial hygiene records
  • School health records
  • Medical care subgroups (i.e.,prepaid health
    insurance plans)
  • Chronic Disease Registries (i.e., tumor
    registries)
  • Insurance industry data

16
Vital Statistics Rates, Ratios, and Proportions
  • Three rates used in vital statistics
  • Crude rates - computed for an entire population
  • Specific rates - consider differences among
    subgroups, computed by age, race, sex or other
    variables.
  • Adjusted (standardized) rates - to make valid
    summary comparisons between two or more groups
    with different age (or other) distributions.

17
Measures of Mortality
  • Each rate is a measure of the relative frequency
    of deaths that occurred in a given population
    over a specific time period (time at risk).
  • Population size is usually defined as the
    population at midyear (July 1).
  • These measures estimate the population at risk
    (ab)/time(t) of one year. If this convention
    cannot be met, then the calculation should really
    be considered a proportion rather than a rate.

18
Measure of Mortality Annual Crude Death Rate
  • Universally used as generalized indicator of a
    populations health.
  • May not be truly reflective without accounting
    for age, race, or sex.
  • Example
  • State, Yr - population 5000 deaths 25
  • Crude Death Rate 25/5000 x 1000
  • 5 deaths per 1000 per year

19
Measure of Mortality Age-Specific Death Rate
  • Defined as the number of deaths in a specific age
    group in a calendar year, divided by the
    population of the same age group on July 1 of
    that year, the quotient multiplied by 1000.
  • Example
  • Country, Yr - age group 25-34 yrs population
    5,000,000 deaths 200,000
  • Age-specific death rate 200,000/5,000,000 x
    1000
  • 40 deaths per 1000 population per year for
    age group 25-34

20
Measure of Mortality Cause-Specific Death
Rate
  • Defined as the number of deaths assigned to a
    specific cause in a calendar year, divided by the
    population on July of that year, the quotient
    multiplied by 100,000
  • Example
  • Country, Yr - cause accidents population
    5,000,000 deaths 4,000
  • Cause-specific death rate 4,000/5,000,000 x
    100,000
  • 80 accidental deaths per 100,000 population
    per year

21
Measure of Mortality Proportional Mortality
Ratio
  • Defined as the number of deaths assigned to a
    specific cause in a calendar year, divided by the
    total number of deaths in that year, the quotient
    multiplied by 100
  • Example
  • Country, Yr - total deaths from all causes
    1,500,000 deaths from cancer 675,000
  • Proportional mortality ratio 675,000/1,500,000
    x 100
  • 45 of total deaths per year from cancer

22
Measure of Mortality Infant Mortality Rate
  • Defined as the number of deaths of persons age
    0-1 in a calendar year, divided by the number of
    live births in that year, quotient multiplied by
    1000
  • Example
  • State, Yr - live births 325,000 infant deaths
    1,750
  • Infant mortality 1,750/325,000 x 1000
  • 5.4 infant deaths per 1000 live births per year

23
Measure of Mortality Maternal Mortality Ratio
  • Defined as the number of deaths assigned to
    puerperal causes (i.e., childbearing) in a
    calendar year divided by the number of live
    births in that year, the quotient multiplied by
    100,000.
  • Example
  • Country, Yr - deaths due to puerperal causes
    275 live births 1,750,000.
  • Maternal mortality ratio 275/1,750,000 x 100,000
  • 15.71 maternal deaths per 100,000 live births
    per year

24
Measure of Mortality Neonatal Mortality
Proportion
  • Defined as the number of deaths of neonates
    (infants divided by number of live births in that year,
    the quotient multiplied by 1000
  • Example
  • State, Yr - deaths at births 325,000
  • Neonatal mortality proportion 2,750/325,000 x
    1000
  • 8.5 neonatal deaths per 1000 live births

25
Measure of Mortality Fetal Death Ratio
  • Defined as the number of fetal deaths in a
    calendar years, divided by the number of live
    deaths in that year, the quotient multiplied by
    1000.
  • Example
  • State, Yr - fetal deaths 2,450 live births
    525,000
  • Fetal death ratio 2,450/525,000 x 1000
  • 4.7 fetal deaths per 1000 live births

26
Measure of Mortality Perinatal Mortality
Proportion
  • Defined as the number of fetal plus neonatal
    deaths, divided by the number of live births plus
    fetal deaths, the quotient multiplied by 1000
  • Example
  • State, Yr - fetal deaths 3,250 neonatal deaths
    5,750
  • live births 475,000
  • Perinatal mortality proportion
    3,2505,750/475,000
  • 3,250 x 1000
  • 18.8 perinatal deaths per 1000 fetal deaths
    plus live births

27
Measure of Fertility Crude Birthrate
  • Defined as the number of live births in a
    calendar year, divided by the population at July
    1 of that year, the quotient multiplied by 1000
  • Example
  • State, Yr - live births 250,000 population
    30,000,000
  • Crude birthrate 250,000/30,000,000 x 1000
  • 8.3 live births per 1000 population per year

28
Measure of Fertility General Fertility Rate
  • Defined as the number of live births in a
    calendar year, divided by the number of women
    ages 15-44 at midyear, quotient multiplied by
    1000
  • Example
  • Country, Yr - live births 7,500,000 number of
    women ages 15-44 35,000,000
  • General fertility rate 7,500,000/35,000,000 x
    1000
  • 214.3 live births per 1000 women ages 15-44
    per year

29
Measure of Morbidity Incidence Rate
  • Defined as the number of newly reported cases of
    a given disease in a calendar year, divided by
    the population on July 1 of that year, the
    quotient multiplied by either 1000, 100,000, or
    1,000,000 (whatevers convenient).
  • Example
  • State, Yr - new cases of AIDS reported 5,250
    population 35,000,000
  • Incidence rate 5,250/35,000,000 x 100,000
  • 15 new AIDS cases per 100,000

30
Measure of Morbidity Prevalence Proportion
  • Defined as the number of existing cases of a
    given disease at a given time, divided by the
    population at that time, the quotient multiplied
    by 1000, 100,000, or 1,000,000 (whatevers
    convenient)
  • Example
  • Country, Yr - number of men alive with AIDS
    3,750 population 15,000,000 men
  • Prevalence proportion 3,750/15,000,000 x 100,000
  • 25 AIDS cases per 100,000 men

31
Measure of Morbidity Case-Fatality Proportion
  • Defined as the number of deaths assigned to a
    given cause in a certain period, divided by
    number of cases of the disease reported during
    the same period, the quotient multiplied by 100.
  • Example
  • Country, Yr - report number of male AIDS cases
    45,000 deaths from the disease 37,000.
  • Case-fatality proportion 37,000/45,000 x 100
  • 82.2 mortality among reported cases of AIDS

32
Adjustment of Rates (or, Rate Adjustment)
  • Adjusting, or standardizing, rates is used to
    make valid comparisons between populations that
    may differ in some significant way (i.e., age
    distribution).
  • Standardized rates have no meaning in isolation,
    since adjusted rates are artificial.
  • Depending on type of data - there are two methods
    to adjust rates - direct (preferred) and
    indirect.
  • The numerical values of the adjusted rates depend
    on the choice of the standard population.
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