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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 community’s health status

– Deciding what’s the best way for providing health services

– Planning a public health program

– Evaluating a program’s 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.

CensusRegistration of Vital

EventsMorbidity Surveys

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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.

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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.

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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.

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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.

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Demographic Data:US National Death Index

Prepared by NCHS - a nationwide, computerized index of death records compiled from each state’s 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 Data:U.S. Morbidity Surveys

Morbidity data (i.e., prevalence of disease)– Communicable disease reports are shared

through CDC’s 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 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

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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 (a+b)/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 population’s 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 <28 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 <28 days=2,750; 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= 3,250+5,750/475,000+

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 (whatever’s 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 (whatever’s 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.