A Brief Introduction to Epidemiology - IV ( Overview of Vital Statistics

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A Brief Introduction to Epidemiology - IV (
Overview of Vital Statistics Demographic
Methods)

• Betty C. Jung, RN, MPH, CHES

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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

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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

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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

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Demographic Data

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

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Demographic Variables

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

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Vital Statistics (Events)

• Include
• Births
• Deaths
• Marriages
• Divorces

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Sources of Vital Statistics Demographic Data
in the U.S.

• Census
• Registration of Vital Events
• Morbidity Surveys

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Demographic DataUnited 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.

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Demographic DataUnited 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.

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Demographic DataAnnual 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.

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Demographic DataUS 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.

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Demographic DataUS 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.

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Demographic DataU.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)

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Demographic DataU.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

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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.

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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.

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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

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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

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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

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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

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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

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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

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Measure of Mortality Neonatal Mortality
Proportion

• Defined as the number of deaths of neonates
  (infants lt28 days of age) in a calendar year,
  divided by number of live births in that year,
  the quotient multiplied by 1000
• Example
• State, Yr - deaths at lt28 days2,750 live
  births 325,000
• Neonatal mortality proportion 2,750/325,000 x
  1000
• 8.5 neonatal deaths per 1000 live births

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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

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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

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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

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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

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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

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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

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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

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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.