Title: Basic Epidemiology for Community Health Assessment
1Basic Epidemiology for Community Health Assessment
Nelson Adekoya, DrPH Centers for Disease Control
and Prevention
2 Outline
- Definitions
- Fundamentals of Epidemiology
- Data
- Death Certificate
- Determine the Leading Causes of Death
- Data Presentation Tips
- Questions Self Quiz
2
3- Define Health
- Define Public Health
- Define Epidemiology
- What are the goals of Public Health?
-
3
4- Public health is the science of preventing
diseases, prolonging life, and promoting health
thru organized community effort
4
5- Goals of Public Health?
- Prevent or control disease, disability and injury
- Improve quality of life for residents of state or
community
5
6- Define Epidemiology (write down your definition,
check against definition in Part 2)
6
7Part I
Epidemiology and Data are inseparable. So, why do
we need data? ..write down your answers
7
8- Why are Data Needed?
- to determine major health problems (needs
assessment, program development) - to identify where to focus efforts and resources
(asset mapping) - to determine progress in solving health problems
(measuring health indicators, outcomes, or
Healthy People Objectives) - to conduct research and grant applications
8
9Succinctly, data are needed ? to assess the
health of a community or population ? to search
for causes of disease, injury and disability ?
to plan programs to meet community needs and ?
to measure progress in prevention and control
efforts.
9
10- According to the National Center of Vital Health
Statistics -
- Data is required for a process that involves
the community in identifying problems, setting
priorities, developing an action plan, measuring
progress, deciding whether the actions are
effective, modifying the actions if necessary,
and reevaluating the community's problems and
priorities.
10
11Types of Data Needed
- Depend on
- What is the program of interest?
- What is the focus of the program?
- What is the purpose of the program?
-
-
11
12- Primary data (data collected directly by the
organization). - Secondary data (data collected by someone outside
their own program or agency, to measure the
outcomes of interest). -
12
13Locating and Accessing Secondary Data
- Online Secondary Data access available by such
links from the New Hampshire Health Data
Inventory (HDI) at www.nhhealthdata.org - Some web sites provide data tables that can be
used to perform calculations or create charts. -
- Other web sites allow users to obtain raw data
files, which can be used to create aggregate
tables, generate statistics, and perform
calculations.
13
14Web Sites for Secondary Data Sources
- CDC WONDER (http//wonder.cdc.gov/) has access
to a variety of public health information,
including links to environmental and
disease-specific data. - CDC WISQARS (http//www.cdc.gov/ncipc/wisqars/d
efault.htm) WISQARSTM (Web-based Injury
Statistics Query and Reporting System) is an
interactive database system that provides
customized reports of injury-related data. - US Census (www.census.gov) makes some of its
data about the US population available for
download.
14
15- What is NM website address to access health data?
15
16Importance of Data Quality
- Relevance
- Accuracy
- Timeliness
- Accessibility
- Interpretability
- Coherence
16
17Relevance
- The relevance of statistical information reflects
the degree to which it meets the real needs of
clients.
17
18Accuracy
- The accuracy of statistical information is the
degree to which the information correctly
describes the phenomena it was designed to
measure. - It may also be described in terms of the major
sources of error that potentially cause
inaccuracy (e.g., coverage, sampling,
non-response, response).
18
19Timeliness
- The timeliness of statistical information refers
to the delay between the reference point (or the
end of the reference period) to which the
information pertains, and the date on which the
information becomes available.
19
20Accessibility
- The accessibility of statistical information
refers to the ease with which it can be obtained
from the Agency.
20
21Interpretability
- The interpretability of statistical information
reflects the availability of the supplementary
information and metadata necessary to interpret
and use it appropriately. This information
normally includes the methodology of data
collection and processing, and indications or
measures of the accuracy of the statistical
information.
21
22Coherence
- The coherence of statistical information reflects
the degree to which it can be successfully
brought together with other statistical
information within a broad analytic framework and
over time.
22
23Other aspects of data quality to consider
- Able to drive decision-making and behavior
- Can the outcome be monitored over time?
23
24Fundamentals of Epidemiology
Part I1
24
25Definition of Epidemiology
- The study of the distribution and determinants
- of health-related states or events in
specified - populations in a specified time period, and
the - application of findings to control of health
- problems.
25
26Purpose of Epidemiology
? To provide a basis for developing disease
control and prevention measures for groups
at risk.
26
27Descriptive Epidemiology
- ? Examine the distribution of disease in a
population - and observe the basic features of its
distribution. - Answer questions about what, who, when and
- where people get ill, injured, or disabled.
27
28Analytic Epidemiology
- ? Test a hypothesis about the cause of disease by
- studying how exposures relate to the disease.
- Answer questions about how and why people get
- ill, injured, or disabled.
28
29Uses of Epidemiology
- ? Determine the primary agent or causative
factors - ? Determine the characteristics of the agent
- ? Define the mode of transmission, and
contributing factors - ? Identify geographic patterns
- ? Describe the natural course of disease,
disability, injury - and death
- ? Help planning and developing health services
and programs - ? Provide administrative and planning data
29
30Epidemiologists look For
- ? Person
- ? Time
- ? Place
- To answer questions about what, who, when and
where, how and why people get ill, injured, or
disabled.
30
3131
32 Place ?Geographic place ?Urban, suburban,
rural ?Climate ?Geology ?Population
density ?Economic development ?Cultural
norm ?Medical practice ?Nutritional practices
32
3334
3435
3536
3637
37DATA
Part III
38
38 ?Quantitative Data ?Qualitative Data
39
39- Quantitative Health DATA can focus on
- individuals, or
- entire populations.
40
40 Population-based Data versus
Individualized Data ?Example of
individualized data is a patients medical
record. ?Each record is devoted exclusively to
one person and contains information about
his or her unique illnesses, injuries,
behaviors, etc. ?The data are used primarily to
improve the health of that one individual.
41
41 Population-based Data
versus Individualized Data
(cont) ?In public health, our focus is primarily
on populations (e.g. communities, cities,
counties, states). ?Population-based data
tells us about the overall health of that
population.
42
42Major Types of Health Data available for
analysis ? Health outcome / Health Status
Data ? Risk factor Data ? Resource
Data ? Demographic Data
43
43 Quantitative DATA ?
Measurable and tangible ? Provides answer
regarding what, who, when, and where of
health-related events.
44
44 Simply, what we are doing in
Quantitative DATA are ? Counting of
people, behaviors, conditions, or other
discrete events ? Classifying those events into
categories ? Using math and statistics to
answer questions.
45
45 Quantitative DATA Examples
(cont) ?Using numbers of deaths to identify
leading causes of death (What) ?Using
numbers of smokers and nonsmokers by gender
to determine whether men are more likely to
smoke than women (Who) ?Keeping track of the
number of people with flu can identify the
beginning of the flu season (When)
46
46 Quantitative DATA Example
(cont) ?Comparing the proportion of women who
began prenatal care after the first
trimester in various counties will provide
an indication of where access to prenatal
services may be a problem.
47
47 Qualitative
DATA ?Qualitative data can be used to explain
the why and the how of health-related events.
?Qualitative data involve observing people in
selected places and listening to discover how
they feel and why they might feel that
way.
47
48 Examples of Qualitative DATA ? A
focus group of teenage girls could provide
valuable insights concerning why they do or
dont use contraceptives. ? A visit to a
local clinic might indicate how people might
feel as they enter the waiting area.
48
49What Analysis to Request for Quantitative Data?
- Measures of central tendency
-
- ? Mean is the arithmetic average of the values
in the data - ? Median is the middle value
- ? Mode is the most commonly occurring value
-
49
5050
51Death Certificate Data
Part IV
51
52Introduction to Death Certificate Data
Part IV Section One
52
53 - Primary Source of Death / Mortality DATA
- Death / mortality is one of the primary measures
- of a populations health.
- Death certificate is the primary source of death
or - mortality.
53
54What data are on a typical death certificate? ?
Information about the characteristics of the
decedent, ? Information about the circumstances
of death (e.g. time, date, and place), and ?
Specifics about the causes of death.
54
55What a typical death certificate
looks like (Figure 1 2)
55
56Information about the decedent includes ?Sex
(2), Age (5a) ?Birthplace (7) ?Marital Status
(10) ?Residence (13 a-f) ?Hispanic Origin (14)
and Race (15) ?Occupation (12a) and Education
(16).
56
57Information about the cause of death includes
? Date of Death (3) ? Place of Death (9a) ?
Immediate Cause and Underlying Cause of Death
(27, Part I) and Other Significant Conditions
(27, Part II) ? Manner of Death (29) and
additional details for deaths due to
accidents, suicide, or homicide (30 a-f).
57
58ICD and Diseases / Conditions
- At the state vital statistics office,
information from death - certificates is entered into electronic
records. - All of the diseases and conditions reported on
the death - certificate are translated from text into
medical codes - using the International Classification of
Diseases (ICD)
58
59- What are ICD codes ?
- The International Classification of Diseases
(ICD), published by the World Health
Organization (WHO), establishes a structure for
translating the entries on the death certificate
into a statistical classification. - From 1979 to 1998, death certificates were coded
- according to ICD-9. Beginning in 1999, death
certificates are being coded according to the
Tenth Revision (ICD-10) .
59
60Part IV Section Two
- How to Determine the Leading Causes of
- Death by analyzing death data from a death
- certificate
60
61 Death Data / Mortality DATA Outline ?
Death certificate (Figure 1 ) ? Data
collection based on a death certificate ?
Discuss limitations of those data
61
62USES of Deaths Data / Mortality Data ? Calculate
general death rates ? Age-specific death rates
? Cause-specific death rates ? Sex-specific
death rates ? Describe the difference between
death counts and death rates ? Identify
leading causes of death
62
63USES of Deaths Data / Mortality Data (cont) ?
Use rates to examine differences in causes of
death by sex ? Analyze trends in rates and
changes in underlying causes over time ?
Determine effective ways to present data
63
64STANDARD MORTALITY MEASURES
- What is a count?
- the most basic unit of data.
-
- ? the number of hospital visits, the number of
injuries, - the number of live-born twins, the number of
mothers who - deliver twins, the number of deaths, and
- the number of deaths due to AIDS, etc.
- ?Counts are also useful when comparing numbers
for the - same population group.
64
65- What are leading causes of death?
- Leading causes of death are diseases identified
as being of - public health importance based upon the
burden of the - disease within a population.
- The importance of each disease is ranked
relative to other - important diseases.
- A standard procedure for ranking leading causes
of death - was adopted by the National Center for
Health Statistics - decades ago in which eligible causes are
ranked according - to the number of deaths (not rates).
65
66Eligible Causes (ICD-9)
- The eligible causes include the 37 rankable
causes from - the List of 72 Selected Causes of Death
(those causes - marked by an asterisk on Figure 6), along
with HIV - infection (added with 1987 data) and
Alzheimers - Disease (added with 1994 data).
- Link to ICD-10 is provided below for revised
ranking http//www.cdc.gov/nchs/datawh/nchsdefs/co
drank.htm
66
67Counts and Leading Causes Of Death
- ? Counts are used to identify leading causes of
death. - ? The leading cause of death is the cause with
the greatest - number of deaths.
- ? Counts can be used to identify the leading
causes of death - in a single population, their value is
limited. - Counts do not help you compare the risk of death
in one - population with the risk in another
population.
67
68- Rate
- A rate is the most common way to measure the
occurrence - of an event in a population.
- ? The general formula for a rate
- Number of events occurring during a given
period x 100000 - Rate
- Population at risk during the
same time period
68
69 Three Consistent Characteristics of a RATE
? The counts in the numerator and denominator
should cover the same time period. ? The
persons who experienced the events in the
numerator should all be included in the
denominator. ? The persons in the denominator
should be at risk for the event in the
numerator. In other words, it should be possible
for them to experience the event.
69
70Proportion
- The number of observations with a given
characteristic (a) divided by the total number of
observations in a given group (a b) 26. That
is, proportion a/(ab).
70
71Ratio
- Ratio simply relates a figure to another. For
example, there are 36 females and 18 males in a
restaurant. The ratio of females to males is
3618 or 36/182.
71
72Adjusted Rate
- An expression of the predicted number of health
events within a standard population defined by
one or more variables not under study and used to
control for effects medicated by such variables.
72
73Specific Rate
- An expression of the observed number of health
events within a defined subgroup or stratum of
the population at risk within a predefined time
period (e.g., age-specific death rate of 1.2
deaths per 1,000 persons aged 10 to 19).
73
74Crude Rate
- An expression of the observed number of health
events per unit of the population at - risk in a defined time period (e.g., crude
mortality rate of 5.7 deaths per 100,000 - persons in 1985).
74
75What is a death rate?
- A death rate is a measure of the occurrence of
death - in a defined population during a specified
time interval.
Number of deaths during a
given time period Death rate
x 1,000,000
Number of people in the population
in which the deaths occurred
75
76What are some specific types of death rates? ?
The death rate discussed above is often called
the crude death rate. ? It measures the
frequency of deaths from all causes in an
entire population.
76
77What are some specific types of death
rates? Example Crude Death Rate The crude
death rate for the United States in 1990 would
be Number of deaths in the
U.S. in 1990
x
100,000 U.S.
population in 1990
77
78 Example Age-specific Death
Rate ? The death rate for a particular age
group. ? The death rate for older adults, age
65-80, in NM in 1983 would be
Number of deaths among 65-80 year olds in NM in
1983
x 100,000
Number of 65-80 year olds in NM, 1983
78
79- Sex-specific death rate
- The death rate for a particular sex, either
males or - females.
- Formula
-
- Number of deaths among males (or females)
- during a given time period
-
x 100,000 - Population of males (or
females) - during the time period
79
80- Example Sex-specific Death Rate
- The death rate for females in NM in 1991 would
be - Number of deaths among females
- in NM in 1991
-
x 100,000 - Number of females in NM, 1991
80
81- Cause-specific death rate
- The death rate from a specific cause for a
population. - The sum of all cause specific mortality rates for
a population equals the total mortality rate for
that population. - Formula
- Number of deaths from a
specific cause - during a
given time period -
x 100,000 - Population during the
time period
81
82- Example Cause-specific Death Rate
- The death rate from homicides in NM, 1990-1994
- would be
- Number of deaths from homicide
- in NM, 1990-1994
-
x 100,000 - Population in NM, 1990-1994
82
83- Example Age-sex-cause-specific Death Rate
- The death rate from homicides for 65-80 year old
females in NM, 1990-1994 would be - Number of deaths from homicide among 65-80
- year old females in NM, 1990-1994
-
x 100,000 - Number of 65-80 year old females
- in NM, 1990-1994
83
84- What happens when the numbers are small?
- Occasionally, your numerators will be so small
that the - resulting rates become unstable or
unreliable. - One rule of thumb is to have at least 20 deaths
in each - cause category that you are analyzing. You can
- accomplish this by combining several years of
data.
84
85- How are rates used to make comparisons?
- The real value of death (mortality) rates is that
they enable us to compare the risk of death
between different causes, different age/sex
groups, different time periods, etc.
85
86- How are rates used to make comparisons?
- Quite often, these comparisons are expressed in
terms of a rate ratio. - The formula for calculating a rate ratio
- X Y or X/Y
- where
- X death rate in one
population - Y death rate in another
population
86
87- Example Comparing Death Rates
- Suppose that in 1993 the overall death rate for
males, ages - 15-24 years, had been 141.8 per 100,000.
- Further suppose that the death rate for males,
ages 25-44, - that same year had been 258.3 per 100,000.
- ?Then the ratio of the death rate for younger
males to the - death rate for older males would be
- 141.8
258.3 0.55 - ?This means that the death rate for younger males
is half - the death rate for older males.
87
88- What are some common mistakes
- in calculating rates?
- When calculating a rate, always use the same
time - period in the numerator and denominator.
- When the numerator includes deaths for more
than one - year, the denominator must include the
population for - the same years.
- If the deaths in the numerator are added
together - for 5 years, the population in the
denominator must also - be added together for the same 5 years.
88
89- What are some common mistakes in
- calculating rates (cont)?
- Be sure to use the same population, age group,
and/or sex in both the numerator and denominator.
- When calculating cause-specific rates, the
denominator should include the entire population
while the numerator should include only deaths
due to one specific cause. - Be sure to indicate what scale was used usually
results are per 1,000 or per 100,000.
89
90- How are percents helpful?
- Use a percent () to describe the proportion of
deaths due to a specific cause (that is, those
deaths assigned a specific ICD code). - The formula for calculating this percent is
-
- Number of deaths from a specific
cause - during a given time
period -
x 100 - Number of deaths due to all
causes - during the time
period
90
91 Example Using
Percents Suppose that in a certain population
from 1992 to 1996, the number of deaths from
suicide was 525, and the total number of deaths
was 2,625. The percent of deaths due to suicide
would be calculated using the formula
525 2,625 0.20 This means
that 20 of the deaths from 1992 to 1996 were due
to suicide.
91
92How Should These Data Best be Presented?
- Deciding which results are most important to
present - Choosing the most appropriate format for
presenting those results.
92
93A Presentation on the Leading Causes
of Death
The results you present should answer ? What
are the leading causes of death? ? Do the
causes differ by age group? By sex? By race
or ethnic group? ? Are there any significant
trends over time? ? What can be learned from
comparisons with other states or with the
United States as a whole?
93
94What are some tips for presenting
quantitative data? (1/2)
- Develop clear messages.
- Limit your data points to those that are most
important. - Display data in colorful, interesting graphics.
- ? Make all of the graphics relate to the message.
94
95What are some tips for presenting
quantitative data? (2/2)
- ? Avoid too much data on one graph.
- Intersperse data with the human element to
- personalize the statistics.
- ? Keep the so what? in mind to relate all data
to your - main points.
95
96Are there any special rules for
preparing tables? (1/3)
- Effective tables have the following
characteristics - as simple as possible.
- self-explanatory.
- ? use a clear and concise title.
96
97Are there any special rules for
preparing tables? (2/3)
Effective tables have the following
characteristics ? have clear and concise
labels for each row and column, and include
the unit of measurement for the data (e.g.,
years, rate per 100,000).
97
98Are there any special rules for
preparing tables? (3/3)
- Effective tables have the following
characteristics - show totals for rows and columns.
- explain any codes, abbreviations, or symbols in a
footnote. - note the source of data in a footnote (if not
original data).
98
99What about charts? (1/2)
- Arrange the categories that define the bars in a
natural - order, such as alphabetically or by increasing
age, or in - an order that will produce increasing or
decreasing bar - lengths.
- Position the bars either vertically or
horizontally as you - prefer.
- ? Make all the bars the same width.
99
100What about charts? (2/2)
- Make the length of bars proportional to the
frequency - of the event.
- Leave a space between adjacent bars, to make the
bar - chart easier to read.
- Code different variables by differences in bar
color, - shading, cross-hatching, etc., and include a
legend that - interprets your code
100
101101
102102
103103
104104
105105
106Summary
106
107Framing epidemiologic questions?
- Know the elements of question
107
108Elements of the question
- Who what are the characteristics of the
population you want to know about? - Age
- Gender
- Race/ethnicity
108
109Elements of the question (cont.)
- What About what indicator or outcome are you
seeking information? - Behavior
- Health/illness - particular ICD-10 codes can
be found at - http//www3.who.int/icd/vol1htm2003/fr-icd.htm
- ICD-9-CM codes can be found at
- http//www.cdc.gov/nchs/icd9.htmRTF
- Injuries
- Chronic diseases
109
110Elements of the question (cont.)
- Where What areas are you interested in learning
about? - Geographic area (e.g. HSA, SAU, county)
- Know the town, or group of towns in the
- geographic area
- Residents v. occurrences
110
111Elements of the question (cont.)
- When What time period are you considering?
- Trends over time
- Is a certain time frame necessary (is the
- indicator changing)?
111
112Examples of Questions
- What is the rate of cardiovascular disease in
New Mexico for the most recent year for - which data is available? Five years ago? Ten
years ago? For ages 65? - What is the prevalence of diabetes in New
Mexico for different age groups?
112
113Release of PublicHealth Data
- Confidentiality
- Stability and
- Reliability
113
114End !
137