Epidemiologic and Research Applications.
Epidemiology,
Demography - Applications in Community
Health Nursing.
After studying this chapter, you should be able to:
- Interpret and use basic epidemiologic, demographic, and statistical
measures of community health.
- Apply principles of epidemiology and demography to the practice of
community health.
Introduction
Epidemiology and demography
are sciences for studying population health. To promote, restore, and maintain
the health of populations, the community health professional integrates and
applies concepts from these fields. Use of the epidemiologic process can
significantly enhance community health practice, providing both a body of knowledge
and a methodology for investigating health problems and evaluating health
services. This chapter introduces epidemiologic and demographic concepts that
are essential for the practice of community health nursing.
Epidemiology
The term epidemiology originates from the Greek terms logos (study), demos
(people), and epi (upon)—literally, “the study of what is upon the people.†The
focus of study is disease occurrence among population groups; therefore,
epidemiology is referred to as population medicine. Population in this context
refers to people with a common characteristic such as gender, age, and place of
residence. Although epidemiologic investigations examine conditions in
population groups, it is important to remember that a population consists of
individuals, each of whom is a person with a particular condition.
Epidemiology is the study of
the distribution and determinants of health-related states or events in
specified populations and the application of this study to control health
problems. Epidemiology is a quantitative discipline based on principles of
statistics and research methodologies. Epidemiologic studies have made a
significant contribution to the identification of risk factors, such as smoking
and lung cancer. In addition, epidemiologic studies identify modifiable risk
factors for heart disease resulting in lifestyle changes for individuals along
with changes in public health policy. Thus, epidemiologic research methods are
a powerful tool for investigating health-related events.
Early epidemiologic studies
were concerned chiefly with the control of epidemics (an outbreak of an illness
beyond the levels expected in a population). John Snow's study of a cholera
epidemic in
Many epidemiologic studies
have a disease morbidity/mortality focus; however, the dimensions of health and
well-being extend beyond these components. Epidemiology as practiced today has
expanded its scope to include investigation of lifestyles, health-promotion
strategies, injury, environmental conditions, and other factors that influence health.
Public health practitioners use the knowledge gained from the epidemiologic
process to guide decision-making and aid in developing and evaluating
interventions for health promotion and disease prevention. The epidemiologic
process is analogous to the nursing process in that critical analysis is
required to gain further insight into public and community health issues.
Descriptive Epidemiology 
Descriptive epidemiology
focuses on the distribution of frequencies and patterns of health events with
groups in a population. Descriptive studies examine disease patterns and other
health-related phenomena according to “person†(who is affected?), “place†(where were they affected?), and “time†(when were they affected?). Descriptive statistics provide data,
information, and insight into the characteristics present in a group or
population with a disease or the absence of disease in unaffected groups or
populations. The question addressed is, “Are there
characteristics present in the affected population that are not present in the
unaffected population?†For example, why are breast
cancer rates lower in women who have had children and breast-fed them than in
women who have not had children? Descriptive statistics provide epidemiologic
studies with data to develop rates, ratios, and proportions of morbidity and
mortality statistics for use in public health and vital statistics. Data from
descriptive studies suggest hypotheses for further testing and
usually involve some form of quantification and statistical analysis.
Descriptive studies generally precede analytic studies.
Analytic
Epidemiology
In contrast to descriptive
epidemiology, analytic epidemiology seeks to identify associations between a
particular disease or health problem and its etiology.
Analytic studies are directed toward finding answers to the “how†and “why†of health and disease to determine causality. Analytic studies are
concerned with the determinants of disease and seek to identify the causes of
the problem. They test hypotheses or seek to answer specific questions and can
be retrospective or prospective in design.
Demography
Demography
(literally, ‘writing about the people’ from the Greek demos
[people] and graphos
[writing]) is the statistical study of human populations with reference to size
and density, distribution, and vital statistics. Demographic statistics provide
information about significant characteristics of a population that influence
community needs and the delivery of health care services. Demographic studies
(that is, demographic research) provide descriptions and comparisons of
populations according to the characteristics of age; race; sex; socioeconomic
status; geographic distribution; and birth, death, marriage, and divorce
patterns. Demographic studies often have health implications that may or may
not be addressed by the investigators. The census of the
Levels of Prevention in
Community Health Practice
The
concept of prevention is a key component of modern community health practice.
In popular terminology, prevention means inhibiting the development of disease
before it occurs. For the community health practitioner, three levels of prevention—primary, secondary, and tertiary—guide
practice.
Primary prevention applied to a
generally healthy population precedes disease or dysfunction. Primary
prevention is divided into two component areas: 1) general health promotion
such as nutrition, hygiene, exercise, and environmental protection; and 2)
specific health promotion, which includes immunizations and the wearing of
protective devices to prevent injuries. If a disease is environmentally
induced, primary prevention can prevent a person's exposure to the environmental
factor involved and thereby prevent development of the disease. Prevention is
difficult to measure and demonstrate empirically; however, it is less costly
both in terms of human suffering and in terms of economic savings than crisis
intervention and treating disease and conditions after they have occurred.
Secondary prevention is
the early detection and treatment of adverse health conditions. The goal of
this level of prevention is to detect and treat a problem at the earliest
possible stage when disease or impairment already exists. Secondary prevention
may result in the cure of illnesses that would be incurable at later stages,
the prevention of complications and disability, and confinement of the spread
of communicable diseases. Examples of secondary prevention include the Pap
smear for cervical cancer, audiometric testing for hearing impairment, skin
test for tuberculosis, and phenylalanine test for phenylketonuria
in infancy. On a community basis, early treatment of people with infectious
disease, such as a sexually transmitted disease (STD), may protect others from
acquiring infection and thus provides secondary prevention for infected people
and primary prevention for their potential contacts.
Tertiary prevention is employed
after diseases or events have already resulted in damage to people. The purpose
of tertiary prevention is to limit disability and to rehabilitate or restore
the affected people to their maximum possible capacities. Examples of tertiary
prevention include provision of “meals on wheels†for the homebound, physical therapy services for
stroke victims, halfway houses for recovering alcoholics, fitness programs for
heart attack victims, and mental health counseling for rape victims.
The
goal of intervention at each of the three levels is to prevent the progression
process. To plan appropriate methods of primary, secondary, and tertiary
prevention, the community health nurse must initially assess the current health
status of the community.
Descriptive Measures of
Health
Demographic Measures
Certain
human characteristics, or demographics, may be associated with wellness or
illness. Age, race, sex, ethnicity, income, and educational level are important
demographics that may affect health outcomes. For example, men are more likely than
women to develop certain heart diseases, and African Americans are more likely
than Caucasians to have low-birthweight infants. To
plan for the health of a community, the nurse must be familiar with the
demographic characteristics of the community and with the health problems
associated with those characteristics.
Morbidity and Mortality
Although
the discipline of epidemiology encompasses both wellness and illness states,
wellness is difficult to measure. Therefore, many measures of “health†are expressed in terms of morbidity (illness)
and mortality (death). An excellent source of morbidity and mortality data, by
state and for select cities, is the Centers for Disease Control and Prevention,
Morbidity and Mortality Weekly Report (http://www.cdc.gov/mmwr).
Incidence
The
incidence of any health or disease condition refers to the number of people in
a population who develop the condition during a specified period of time.Incidence rates measure the rate at
which people without a disease develop the disease during a specific period of
time (i.e., the number of new cases of a disease in a population over a period
of time). Mathematically, incidence rate over a period of time is expressed as:
Number of new cases of disease
―――――――――――――――――×100,000
Total population
at risk
Incidence
is particularly important for analytic epidemiologic research because it allows
the estimation of risk necessary to assess causal association (relative risk).
The calculation of incidence generally requires that a defined population
initially free of the disease in question must be followed over a period of
time in what is called a prospective (forward-looking) study.
Prevalence
The
prevalence of a disease or condition refers to the total number of people in
the population who have the condition at a particular time. Thus, prevalence
may be calculated in a “one-shot†cross-sectional
(“slice of timeâ€) or
retrospective (backward looking) study. Mathematically, prevalence is expressed
as:
Number of existing cases diseases
―――――――――――――――
×100,000
Number in
Total population
Prevalence,
therefore, examines the extent of morbidity in a community and is influenced by
the rate of new cases, the number of existing cases, effective new treatment
modalities, and deaths. It can be classified as period prevalence (existence
during a period of time) or point prevalence (a specific point in time).
Understanding Incidence and Prevalence
Measures
of incidence and prevalence provide different information and have distinct implications.
To understand the relationship between incidence and prevalence, consider the
number of passengers on a train. The number of passengers represents prevalence
(existing disease, old and new cases); the number of boarding passengers
represents incidence (new cases of disease); and passengers who get off the
train represent individuals who either recover or die. Both the number of new
cases entering and the number of individuals with disease who leave either
through death or through recovery from the illness influence prevalence. The
number of passengers on board will increase if the number of boarding
passengers (new cases) is high; if the number of passengers exiting is low
(fewer deaths or increased survival rate due to new treatment); or both occur.
Conversely, prevalence will decrease when the number of new cases is low or
when individuals die or persons are cured of disease or both.
Consider
another example. You read about an increase in the prevalence of cancer; this
increase may mean that there are a higher number of people with cancer in the population. This higher number may be due to more new
cases (in other words, increased incidence) or because people with cancer are
living longer. In either case, the community may need to allocate additional
resources toward cancer. Incidence and prevalence rates are useful tools in
identifying health disparities along with tracking the frequency of diseases.
Ratios, Proportions, and Rates
In
epidemiologic studies, data and statistics make comparison possible among
populations. Therefore, it is necessary to convert raw data into ratios,
proportions, and rates to provide a more valid description of health problems.
A ratio is simply one number divided by another in
which there is no specified relationship between the numerator and denominator.
For example, of 1,000 motorcycle fatalities, 950 are male and 50 are female.
The sex ratio is the number of males compared to number of females (950/50 or
19 males to 1 female).
In
contrast, a proportion
is one number divided by another in which the numerator is a subset of the
denominator (i.e., is included in the denominator) and is expressed as a
percentage. Using the same data, you can calculate the proportion of males to
females. Of 1,000 motorcycle fatalities, 950 are male and 50 are female. What
percentage of fatalities is male? A proportion is expressed by the formula X/(X
+ Y); thus the percentage of males to females would be 950/1,000 multiplied by
100, which equals 95%. Neither ratio nor proportion has a population base or
specific unit of time.
Because
epidemiology is the study of population health, statistical measures must
relate the occurrence of a health condition to the population base. To assess
the probability that one group is at higher risk than another, rates are
calculated. Rates measure the amount of disease,
injury, disability, or death within a unit of the population and within a unit
of time. Rates express a mathematical relationship in which the numerator relates to the number of persons experiencing the
condition, and the denominator expresses the
population at risk or the total number of persons who have the possibility of
experiencing the condition. Rates improve the ability to make comparisons
because they reduce the standard of comparison to a common denominator, the
unit size of the population.
Do
not confuse rates with other proportions that do not use the population at risk
as the denominator. For example, the death rate from cancer is not the same as
the proportion of deaths from cancer. In each, the numerator is the number of
deaths from cancer. However, the denominator differs. In the death rate, the
denominator represents all people at risk of dying from cancer. Therefore, the
cancer death rate is an expression of the risk of dying from cancer. In the
proportion of deaths, also called proportionate mortality rate (PMR), the
denominator is the total number of deaths from all causes. Mathematically, the
PMR is expressed as:
Number or deaths due to a specific
cause
------------------------------------------------------- ×100
Total
number of deaths from all causes
Therefore,
the proportionate cancer mortality simply describes the proportion of deaths
attributable to cancer. For example, if the PMR of heart disease is 37%, this
indicates that 37% of all deaths, regardless of age, sex, or race, are related
to diseases of the heart. However, this statistic provides no indication of the
actual rate involved.
Calculation of
Epidemiologic Rates
Rates are calculated by the
formula:
Number of people experiencing condition
---------------------------------------------------------------
×Κ
population at
risk for experiencing condition
K is a constant (usually 1,000
or 100,000) that allows the ratio, which may be a very small number, to be
expressed in a meaningful way. The concept of rates can be understood more
easily by applying this formula to the calculation of the infant mortality
rate, which estimates an infant's risk of dying during the first year of life.
Example of a Rate: The Infant
Mortality Rate
The infant mortality rate
(IMR) is usually calculated on a calendar-year basis. The number of infant
deaths (deaths before the age of 1 year) during the year is divided by the
number of live births (infants born alive) during the year. The numerator
represents the number of infants experiencing the “condition†of dying in the first year of
life, and the denominator represents the population of infants at risk for
dying in the year.
If within a given year 34,400
infant deaths and 4,084,000 live births were reported for the
34,400
―――― ×1,000 = 8,4
infant deaths per live births
4,084,000
Interpretation of
Rates
Rates enable researchers to
compare different populations in terms of health problems or conditions. To
assess if one community is at greater or lesser risk for the problems or
conditions, compare the rates for the community with rates from similar
communities, from the state, or from the
Caution is required in
interpreting rates. Like most statistical measures, rates are less reliable
when based on small numbers. This is important when assessing relatively
infrequent events or conditions, or communities with small populations.
The majority of rates are
based on data from a calendar year, which may also present some difficulties.
Populations may increase or decrease during a calendar year. To adjust for
population changes over the year, the midyear population estimate is generally
used because the population at risk cannot be determined accurately. A study
that follows a cohort, or specified group, forward in time can help overcome
the limitations of the conventionally calculated calendar-year rate.
Commonly Used Rates
Crude, Specific, and
Adjusted Rates
The basic concept of a rate
can be broken down into three categories: crude, specific, and adjusted. Rates
computed for a population as a whole are crude rates. When calculating deaths
in the total population, irrespective of age, the rate obtained is the crude
mortality rate or crude death rate. With the crude mortality rate, there is no
allowance for the age distribution of the population or comparisons between
populations with different age groups.
Subgroups of a population may
have differences not revealed by the crude rates. Rates calculated for
subgroups are specific rates. Specific rates relate to demographic factors such
as age, race, and gender, or they may refer to the entire population but be
specific for some single cause of death or illness. For example, to eliminate
the effects of different age structures in the population of comparison, the
age-specific death rate would be appropriate. Mortality rates for specific
diseases such as heart disease relate to a specific cause of death, any
subgroup or any age, race, gender, religion, or for an entire population.
Information gained from specific rates can aid in identification of groups at
increased risk within the population and facilitate comparisons between
populations that have different demographic compositions.
In comparing populations with
different distributions of a factor known to affect the health condition of
interest, the use of adjusted rates may be appropriate. An adjusted rate is a
summary measure in which statistical procedures remove the effect of
differences in the composition of the various populations. In essence,
adjustment produces an estimate of what the crude rate would be if the
populations were identical in respect to the adjusted factor. Rates are
adjusted for age, race, sex, or any factor or combination of factors suspected
of affecting the rate. Adjusted rates are helpful in making community
comparisons, but they are imaginary: caution is necessary when interpreting.
Commonly Used Rates
Measures of Natality:
Number of
live births during time interval
Crude
birth rate =
---------------------------------------------------- × 1,000
Estimated
midinterval population
Number of live
births during time interval
Fertility rate =
-------------------------------------------------------------- × 1,000
Number of women
aged 15-44 age midinterval
Measures
of Morbidity
and Mortality:
Number of new cases of specified health
conditions
during time interval
Incidence
rate = ----------------------------------------------------×1,000
Estimated midinterval
population at risk
Number
of deaths of infants aged < 1year
during time interval
Infant mortality rate =
------------------------------------------------------------- × 1,000
Total live births during time interval
Number of deaths of infant aged < 28 days
during time interval
Neonatal
mortality rate =
---------------------------------------------------------- × 1,000
Total live births during time interval
Number of deaths of infants aged _ 28
days but < 1 year during time interval
Postneonatal mortality rate =
-------------------------------------------------- × 1,000
Total live births during time interval
Number of deaths from puerperal causes
during one year
Maternal
mortality rate =
----------------------------------------------------- ×100,000
Number of live births during same year
Analytic Measures of
Health
As discussed previously, rates
describe and compare the risks of dying, becoming ill, or developing other
health conditions. In epidemiologic studies, it is also desirable to determine
if health conditions are associated with, or related to, other factors. The
research findings may provide the theoretical foundation by which preventive
actions are identified (e.g., the linking of air pollution to health problems
has led to environmental controls). To investigate potential relationships
between health conditions and other factors, analytic measures of community
health are required. In this section, three analytic measures are discussed:
relative risk, odds ratio, and attributable risk.
Relative Risk
To determine if a relationship
or association exists between a health condition and a suspected factor, it is
necessary to compare the risk of developing the health condition for the
population exposed to the factor with the risk for the population not exposed
to the factor. The relative risk (RR) expresses the risk ratio of the incidence
rate of those exposed (e.g., smokers) and those not exposed to the suspected
factor (e.g., nonsmokers). The relative risk
indicates the benefit that might accrue to the client if the risk factor is
removed. In this situation, calculation of the relative risk illustrates to the
clinician how much the risk for the smoker increases compared with nonsmokers. The relative risk only applies to studies that
determine incidence (prospective data). Relative risk is used to make causal
inferences. Relative risk can be calculated as follows:
Incidence rate among those exposed
RR = ---------------------------------------------------
Incidence rate among those not exposed
The relative risk indicates
whether the rate in the exposed population is higher than the rate in the
non-exposed population and, if so, how many times higher. A high relative risk
in the exposed population suggests that the factor is a risk factor in the development
of the health condition. Relative risk does not indicate that someone with the
factor will develop the disease. It is important to note that risk estimates
are probability statements; therefore, 1) all those exposed to the factor do
not develop the disease but merely have an increased probability of doing so;
and 2) some people who have not been exposed to the factor will develop the
disease. If the relative risk associated with the presence of the factor is 10,
this merely means that the probability for the disease is 10 times greater in
someone with the factor than in someone without the factor. A relative risk
less than 1 indicates a protective factor. For example, the relative risk of
postmenopausal breast cancer among women who breastfed is 0.87 lower than those
who did not report breastfeeding, indicating a protective effect associated
with breastfeeding.
Internal and
External Risk Factors
The concept of relative risk
applies when one group of people clearly is exposed and another is not exposed
to an external agent such as a virus, cigarette smoke, or an industrial
pollutant. However, it may be confusing to see relative risks applied to internal
factors such as age, race, or sex. Nevertheless, as can be seen in the
following example, people also are “exposed†to intrinsic factors that may carry as much risk as extrinsic ones.
Relative Risk: Homicide
Sinauer and associates (1999) studied
female homicide (termed femicide) over a 5-year
period in
19,5per 100,000
RR = ---------------------- = 3,61
5,4 per 100,000
In other words, the risk of
dying from homicide was three and one half times greater for black women than
for white women. Clearly, race is a risk factor. Race cannot be altered, but
the information provided by this analysis can be used to plan protective
services for the population at greatest risk.
Odds Ratio
Calculation of the relative
risk is straightforward when incidence rates are available. Unfortunately, not
all studies are prospective as is required for the computation of incidence
rates. In a retrospective study, the relative risk is approximated by the odds
ratio.
As shown in Table 2-1, the
odds ratio is a simple mathematical ratio of the odds in favor
of having a specific health condition when the suspected factor is present and
the odds in favor of having the condition when the
factor is absent. The odds of having the condition when the suspected factor is
present are represented by a/b in the table. The odds of having the condition
when not exposed to the factor are c/d. The odds ratio
is thus:
a/b ad
―― =
――
c/d bc
|
Crosstabulation for Calculation
of Odds Ratio |
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An example frequently cited in
epidemiologic literature is that of toxic shock syndrome (TSS). When TSS, a
severe illness involving high fever, vomiting, diarrhea,
rash, and hypotension or shock, first occurred, it was neither practical nor
ethical to consider cases only on a prospective basis. Therefore, existing
cases were compared retrospectively with non-cases, or controls. Early studies
noted an association between TSS and tampon use and suggested that users of a
specific brand of super-absorbent tampon might be at especially high risk. To
clarify the issue, researchers analyzed data from TSS cases and controls, all
of whom used tampons. TSS data in Table 2-2 can be used to calculate the odds
ratio for users of the specific brand of tampon.
ad 30(84)
odds ratio = ―― = --------- = 7
bc 30
(12)
An odds ratio of 1.0 implies
that the odds of exposure are equal and suggest that a particular exposure is
not a risk factor for the disease of study. Users of the specific brand of
tampons were seven times more likely to develop TSS than were tampon users of
other brands. Based on the results of studies, the brand (Rely) was removed
from the market.
Relative Risk and
Odds Ratio: Caution in Interpretation
A high odds ratio or relative
risk must be regarded with appropriate concern; however, the finding should not
obscure the potential involvement of other factors. As
illustrated in Table 2-2, 12 people in the sample had TSS although they did not
use the specific brand of tampon. In other words, this product was not the sole
cause of TSS. Subsequent research showed that certain super-absorbent materials
in tampons or certain aspects of tampon use foster growth of Staphylococcus aureus, the probable causal organism in TSS (Centers for Disease Control [CDC], 1983, 1981, 1980; Davis,
Chesney, Ward, LaVenture,
& the Investigation and Laboratory Team, 1980).
|
Table 2-2 Toxic Shock
Syndrome Cases Among 156 Tampon Users |
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Attributable Risk and Attributable Risk Percentage
Another measure of risk is attributable risk (AR), which measures the difference
between the incidence rates for those exposed and those not exposed to the risk
factor. The measure estimates the excess risk attributable to exposure to the
risk factor. It shows the potential reduction in the overall incidence rate if
the factor is eliminated. The AR is calculated by subtracting the incidence
among those unexposed to a risk factor (nonsmokers)
from those who were exposed (smokers):
AR = incidence rate in exposed
group minus incidence rate in nonexposed group
AR usually is further
quantified into attributable risk percentage
Epidemiologic
Approaches to Community Health Research
Epidemiologic models guide
investigators in examining the determinants of population health. This section
describes three models and explains how each might guide the approach to the
same problem.
Application of each model is
illustrated using the problem of an increase in the infant mortality rate in a
hypothetical community. The infant mortality rate is a particularly important
health index that health professionals should understand even if their main
concern is not maternal or child health. Because infant mortality is influenced
by a variety of biologic and environmental factors affecting the infant and
mother, the infant mortality rate is both a direct measure of infant health and
an indirect measure of community health as a whole.
The Epidemiologic
Triangle
![[epidemiology_clip_image002_0000.jpg]](02%20Epidemiologic%20and%20Research%20Applications.files/image019.jpg)
The
epidemiologic triangle or agent–host–environment model is a traditional view of health and disease, developed
when epidemiology was concerned chiefly with communicable
disease. The
model, however, is applicable to other health conditions. In the model, the
agent is an organism capable of causing disease. The host is the population at
risk for developing the disease. The environment is a combination of physical,
biologic, and social factors that surround and influence both the agent and the
host. The epidemiologic triangle is used to analyze the role and
interrelatedness of each of the factors (i.e., the influence, reactivity, and
effect each factor has on the other two). According to this model, the agent,
host, and environment can coexist. Disease and injury occur only when there is
an interaction or altered equilibrium between them.
Figure 2-1 shows the triangle
in its normal state of equilibrium. Equilibrium does not signify optimum health
but simply the usual pattern of illness and health in a population. Any change
in one of the factors (agent, host, or environment) will result in
disequilibrium—in other words, a change in
the usual pattern.
How could this model guide the
investigation of increased infant mortality? To understand this, one must
consider the three facets of the model.
Agent
If one thinks of the
epidemiologic triangle model from an infectious disease perspective, it might
appear that the investigation should focus on types of infections as agents
that cause infant deaths. However, major causes of infant mortality in the
Host
The characteristics of the
host (the infant population) will be the second area of assessment. This
assessment involves examining infant birth and death patterns in terms
of age, ethnicity, sex, and birth weight. These characteristics have been shown
to be important risk factors for infant mortality. By studying these factors,
it may be possible to identify groups of infants who are at particularly
increased risk of dying.
Environment
Lastly, the environment is
assessed. The mother is a significant part of the infant's prenatal and
postnatal environment. Therefore, the investigators will analyze birth and
infant mortality patterns according to factors such as maternal age, ethnicity,
parity (number of previous live births), prenatal care, and education or
socioeconomic status. Analysis of these factors, which are also related to
infant mortality, will help provide further identification of at-risk groups.
Other conditions in the environment also need to be considered. For instance,
has migration into the community from other areas increased? Has adult
morbidity or mortality, particularly among pregnant women, increased? Have
there been changes in health services, policies, personnel, funding, or other
factors that could affect infant health?
Practical
Application
The analysis of these three
areas ‘the agent, host, and environment’ should provide information regarding
groups at risk for increased infant mortality and a means of reducing a risk
factor. Thus, the epidemiologic triangle, although it was designed with a
communicable disease orientation, can provide a useful guide for studying the
multifaceted problem of infant mortality, along with other health problems.
The Person – Place -
Time Model
In an epidemiologic study,
variables can be considered in terms of person (who is affected), place (where
affected), and time (when affected) relationships. The person – place – time model examines the
characteristics of the people affected (the host in the triangle model), the
place (environment) or location, and the time period involved (which could
relate to the agent, host, or environment). In studying infant mortality
according to this model, infant and maternal factors are considered traits of “person.†Aspects of “place†are such factors as whether
the community is rural or urban and affluent or poor. Aspects of “time†include seasonal or age-specific patterns or
trends in mortality.
The Web of Causation
The web of causation (MacMahon & Pugh, 1970) views a health condition as the
result not of individual factors but of complex interrelationships of numerous
factors interacting to increase or decrease the risk of disease. The essence of
this concept is the multifactorial nature in that a
number of interrelated variables are almost always involved in the cause of a
particular outcome. The web of causation attempts to identify all the possible
influences on the health and illness processes. Creating the
web identifies the most direct causes of conditions, factors contributing to
those causes, factors influencing each of these factors, and so on.
Synergism and
Factors in the Web
Central to the web of
causation model is the concept of synergism, wherein the whole is more than the
sum of its separate parts. For example, the effects of a Shigella
infection of the infant, combined with the effects of poverty, youth, and low
educational level of the mother, are more deleterious to infant health than the
sum of the effects of the individual risk factors.
Use of the web of causation
may result in a more expansive study of infant mortality than one guided by
other models. Ideally, investigators using this model first identify all factors
related to infant mortality. Next, they identify factors that are related to
each of these factors. These two comprehensive steps provide the outline for
the web of causation for infant mortality. Finally, the investigators examine
the relationships among all the identified components of the web and attempt to
determine the most feasible point of intervention to improve infant mortality
in the community. Figure 2-2 depicts a web of causation for infant mortality.
Practical
Application
This multifaceted approach
taken in the web of causation model addresses the concept of causation in a
manner consistent with current knowledge of human health. However, it may be
overwhelming to carry out in everyday practice. In fact, it is more common to
examine only a portion of the web, acknowledging that other relationships
exist. Thorough examination of one portion of the web may provide sufficient
information for initiation of useful actions to improve community health.
Models: Guides to
Investigation and Practice
In this section, three models,
each providing a slightly different approach to a community health problem,
were discussed. As you continue to study community health, you will find other
models that can guide your practice. There is no one “correct†model; as you gain
experience, you will be able to choose or adapt those that are most appropriate
for your work
Epidemiology Applications in Community Health Nursing.
Environmental
Health
After studying this chapter,
you should be able to:
·
Identify basic
concepts of Epidemiology
·
Describe methodology
data, morbidity, mortality
·
Common
epidemiological study designs
·
Agent, Host,
Environment triad
·
The Role of the
Community Health Nurse
A question frequently asked
is, "What is epidemiology"? There are many different definitions of
the term. In the main, people attempting to define epidemiology have normally
done so in the context of their own particular interests or needs. A useful
general definition is that given by Schwabeet al
(1977), which defines epidemiology as the study of disease in populations. It
thus differs from the more conventional medical approaches to the study of
disease that is normally concerned with the study of disease processes in
affected individuals. While the objective of the latter is to find cures for
diseases in individuals already affected, epidemiology is basically concerned
with the reasons why those individuals became diseased in the first place.
Inherent in the
epidemiological approach is the belief that the frequency of occurrence of a
disease in a population is governed by the interaction of a large number of
different factors or determinants. The epidemiologist believes that by studying
these interactions it may become possible to manipulate some of the
determinants involved, and so reduce the frequency with which the disease in
question occurs m a population.
At this stage it is necessary
to ascertain what is meant by the terms population and determinant.
A population can be defined as
the complete collection of individuals that have some particular
characteristic(s) in common. Depending on the characteristic(s) being
considered, a population can be very large or very small. For example, one may
wish to study a particular disease in a particular cattle population in a
particular country. That cattle population could consist of:
All the cattle in
the country
or All the
dairy cattle in the country or
All
the dairy cattle of a certain breed in the country etc.
Another term often used in
epidemiological studies is population at risk. This is usually a subset of the
original, defined population and comprises the total number of individuals in
that original population that are considered capable of acquiring the
particular disease or disease characteristic being studied.
For instance, we might be
interested in studying the frequency with which abortion occurs in a population
of dairy cattle of a certain breed in a certain country. The population at risk
would not be all the individual animals of that particular dairy breed in that
country, since this would include males, steers and immature females, all of
which would not or could not be pregnant and therefore could not abort! It
would consist of female cattle of that breed which were of breeding age.
However, if the characteristic being studied was infection by one of the
infectious agents that can cause abortion, such as Brucella
abortus, the population at risk would have to
include all calves, adult males, steers and immature females of the particular
breed in question, since all these individuals could potentially become
infected with this organism?
A determinant
is any factor or variable that can affect the frequency with which a
disease occurs in a population. Determinants can be broadly classified as being
either intrinsic or extrinsic in nature. Intrinsic determinants are physical or
physiological characteristics of the host or disease agent (or intermediate
host or vector, if present) which are generally determined genetically.
Extrinsic determinants are normally associated with some form of environmental
influence on the host or disease agent (or intermediate host or vector, if
present). They may also include interventions made by man into the disease
process by the use of drugs, vaccines, dips, movement controls and quarantines.
The role of determinants in the disease process is discussed in more detail
later on in this chapter.
Since the determinants of
disease are often varied, the epidemiologist may have to draw on a number of
different scientific disciplines and techniques if he is to study them. The
epidemiological approach is, therefore, a holistic one and the "art"
of epidemiology lies in the ability of the epidemiologist to coordinate the use
of such disciplines and techniques in a disease investigation,
and to produce from the results generated a composite and comprehensive picture
of how a particular disease maintains itself in nature.
If we accept the premise that
the frequency with which a disease occurs in a population is governed by a
large number of determinants, it would be expected that some of these,
particularly the extrinsic ones, would vary in space and time. It follows,
therefore, that disease is a dynamic process. The type and pattern of diseases
in livestock differ from country to country, area to area, species to species
and production system to production system. Furthermore, the range and
importance of the disease problems encountered may change dramatically over
time within the criteria mentioned. The effective control of disease depends as
much on a thorough understanding of the many complex factors that govern the
changes taking place in a disease process as it does on the provision of
veterinary inputs such as drugs, vaccines and dips.
Intrinsic determinants
of disease
Disease agents as
determinants of disease
Agents associated with disease
can be categorized into two broad groups:
· "Living" agents, such as viruses,
bacteria, rickettsia, protozoa, helminths,
arthropods etc.
· "Non-living" agents, such as heat and
cold, water, nutrients, toxic substances etc.
Since infectious diseases of
livestock are generally regarded as being of prime importance in
In instances of infectious
disease, the presence or absence of the aetiological agent is the main
determining factor in the epidemiology of the disease. Obviously, disease
cannot occur in the absence of the agent, but, conversely, disease need not
always result from the presence of the agent. This leads us to the important
epidemiological distinction between infection and disease.
· Infection can be defined as the invasion of a living organism,
the host, by another living organism, the agent.
· Disease
can be
defined as a derangement in the function of the whole body of the host or any
of its parts.
Infectivity,
virulence and pathogenicity
Whether infection takes place
or not may depend on a whole range of determinants, both intrinsic and
extrinsic, which affect the host and the agent (and the intermediate host or
the vector, if present).
Infectivity
is a measure of the ability of a disease agent to establish
itself in the host. This term can be used qualitatively, when an agent is
referred to as being of low, medium or high infectivity, or quantitatively.
Attempts to quantify infectivity normally involve the use of a statistic known
as ID50. This refers to the individual dose or numbers of the agent
required to infect 50% of a specified population of susceptible animals under
controlled environmental condition.
Having become infected, the
host may or may not become diseased, and this is again determined by a range of
intrinsic and extrinsic determinants affecting the agent and the host. Two
terms - virulence and pathogenicity - are often used
to describe the ability of the agent to cause disease.
Virulence
can be defined as a measure of
the severity of a disease caused by a specified agent. In its strict sense,
virulence is a laboratory term and is used to measure the varying ability of
disease agents to produce disease under controlled conditions. It is often
quantified by a statistic known as LD50 which refers to the
individual dose or numbers of the agent which will kill 50% of a specified
population of susceptible animals under controlled environmental conditions.
Pathogenicity
Is an epidemiological term
used to describe the ability of a particular disease agent of known virulence
to produce disease in a range of hosts under a range of environmental conditions?
Host/agent
relationships
The relationships between
infection and disease are frequently dynamic in nature. They centre on the
"balance" that can be achieved between the resistance mechanism of
the host and the infectivity and virulence of the agent. Disease outbreaks
caused by the introduction of an agent into a susceptible host population which
has not been previously exposed to that agent normally result in a disease of
high pathogenicity with commensurate severe losses in
the host population. Such a process is actually detrimental to the agent's
survival, since by killing off the host population it adversely affects both
its ability to reproduce and its chances of gaining access to new susceptible
hosts. An agent can therefore improve its chances of survival by increasing its
infectivity and decreasing its pathogenicity, and
some agents have a natural tendency to do this under certain circumstances.
Since a commensal
or parasitic relationship confers no benefits to the hosts, they tend to
develop means of resisting infection by disease agents. While the agents, in
order to survive, develop methods of circumventing the hosts' defences. Disease
agents normally have much shorter generation intervals and can multiply much
more rapidly than their hosts, and therefore tend to evolve much quicker. This
rapid evolution usually enables the agents to keep comfortably ahead of the
hosts' defence mechanisms. There are many mechanisms by which infectious agents
can avoid or overcome the defences of the host. The two mechanisms whose
consequences are of particular importance in the field of livestock disease
control are the carrier state and antigenic variation.
Creation
of the carrier state.
The term "carrier"
is used to describe an individual that is infected by a disease agent and is
capable of disseminating that disease agent but shows no sign of clinical
disease. Three types of carrier state are recognised:
· The true carrier, which is an infected individual capable of
disseminating the infectious agent but which never exhibits clinical signs of
disease. True carriers occur in various diseases, including salmonellosis.
· The incubatory carrier, which is an infected individual
capable of disseminating the infectious agent while the disease is still in the
incubatory stage. In foot-and-mouth disease, for instance, infected animals are
most infectious 12 to 24 hours before the clinical signs of the disease appear.
· The convalescent carrier, which is an individual that
continues to disseminate the infectious agent after the clinical signs of the
disease have disappeared. Convalescent carriers occur in such diseases as
contagious bovine pleuropneumonia.
Antigenic
variation. Some species of disease agent seek to evade the
hosts' defence mechanisms by altering their antigenic characteristics. The most
extreme case of antigenic variation occurs in trypanosomiasis,
where infection in the host usually takes the form of a series of parasitaemias each one of which involves a form of
trypanosome antigenically different from the
preceding one. This type of antigenic variation occurs during the course of a
single infection.
Another type of antigenic
variation occurs in certain agents, such as the foot-and-mouth disease virus,
that are highly infectious in nature and that depend for their survival on a
continuous cycling through host populations of relatively long-lived animals.
The ability to reinfect the same host at a later date
is obviously desirable for the agent's survival, and this is dependent on the
generation of a relatively short-lived immunity combined with the ability of
the agent to undergo antigenic variation during its passage through the host
population. In such circumstances there is a strong selection pressure for
antigenic variants. The two main types of variation are:
· Antigenic drift, which involves only minor changes in antigenicity, so that hosts previously infected with the
agent retain a certain degree of immunity to the drifted strain.
· Antigenic shift, which involves a major change in antigenicity, so that previously infected individuals
possess little or no immunity to the shifted agent.
Antigenic shifts are of
particular significance when the control of a disease is being attempted by
vaccination, since in effect they represent the introduction of a new agent
against which the existing vaccine is likely to confer little or no immunity.
The capacity of parasites to
evolve rapidly has important implications in other areas of disease control.
The very act of introducing a control measure or disease treatment may, in
itself, create conditions whereby a strong pressure is exerted on the agent
population to select strains which are resistant to the measures or treatments
imposed. The evolution of such resistant strains will, in turn, jeopardise the
effectiveness of the control measure or treatment. Resistant strains of agents
are most likely to develop when the measures or treatments are carried out on a
wide scale but improperly - as, for example, in the case of antibiotic
resistance arising through the widespread, unsupervised use of antibiotics by
livestock producers.
Other terms used to further
define host/agent relationships include:
· Incubation
period, which is the period of time
that elapses from the infection of the host by the agent to the appearance of
clinical symptoms.
· Prepatent period, which is the period between the infection of the
host by the agent and the detection of the agent in the tissues or secretions
of the host.
· Period of communicability, which is the period of time during which an
infected host remains capable of transmitting the infective agent.
Methods
of transmitting infectious agents
Ascertaining the means by
which disease agents are transmitted is a major objective in epidemiological
studies, since once the mechanisms by which a particular disease is transmitted
are understood, it may become possible to introduce measures to prevent
transmission from taking place.
There are three main ways by
which disease agents are transmitted from infected to susceptible hosts. An
agent may be transmitted through contact between infected and susceptible
individuals, or it may be conveyed between these individuals by means of an
inanimate object or via another animal serving as a vector or intermediate
host. These methods of transmission are not mutually exclusive; the same
disease agent may be transmitted by more than one of the following ways.
Contact transmission.
In contact transmissions the agent is conveyed between
hosts through direct physical contact, as in the case of venereally
transmitted diseases such as vibriosis or trichomoniasis, or through indirect contact.
In cases of indirect contact
the agent is normally contained in the excretions, secretions or exhalations of
the infected host i.e. in the faeces, urine, milk, saliva, placenta and
placental fluids, or as aerosols or droplets in the breath. Susceptible hosts
contract the infection either by direct exposure to these or through exposure
to substances contaminated by them. Diseases spread in this fashion include rinderpest, foot-and-mouth disease,
Contact transmissions can be
further distinguished according to whether they occur horizontally between individuals
of the same generation or vertically between individuals of different
generations. In vertical transmissions the infectious agent is usually passed
from dam to offspring either in the uterus or through the colostrum.
The main factors determining
whether or not transmission takes place in contact-transmitted diseases are:
·
The ability of the agent to survive in the environment. Rinderpest
virus, for example, is easily destroyed in the environment, so contact between
infected and susceptible individuals must be close and immediate for
transmission to take place, whereas, under certain circumstances,
foot-and-mouth disease can spread between widely separated stock.
·
The extent of the contact that occurs between infected and susceptible
individuals of the host populations and their mobility within these
populations. The control of livestock movements is, therefore, a vital factor
in the control of contact-transmitted diseases which, in
Vehicular
transmission.
In vehicular transmission the agent is transferred
between infected and susceptible hosts by means of an inanimate substance or
object (sometimes called fomite), such as
water, foodstuffs, bedding materials, veterinary equipment and pharmaceuticals,
or on the skin, hair or mouthparts of animals. In contrast to indirect
transmission, the survival time of the agent in or on the vehicle is usually
prolonged. This means, in effect, that vehicular transmission can take place
over greater distances and over longer time periods. Hygiene, disinfection and
control over the distribution of likely vehicles of transmission are important
factors in the control of vehically transmitted
diseases.
Certain agents may take the
opportunity to reproduce themselves during vehicular transmission. This occurs
in the transmission of food-borne bacteria, such as salmonella and coliforms, and underlines the importance of strict hygiene
in the handling of foodstuffs and livestock feeds, since a small initial
contamination may eventually result in the gross contamination of a whole batch
of food or feed.
Vectors and intermediate
hosts.
Confusion frequently arises
between the terms "vector", "intermediate host" and
"definitive host". The latter two terms are essentially
parasitological terms and describe the different types of hosts that are
biologically necessary in the lives of agents with relatively complicated life
cycles.
· A definitive host is a host in which the agent
undergoes a sexual phase of its development.
· An intermediate host is a host in which the agent
undergoes an asexual phase of its development.
The definitive host is usually
a vertebrate, while intermediate hosts can be either vertebrates or invertebrates.
· A vector is an invertebrate animal that actively
transmits an infectious agent between infected and susceptible vertebrates.
Essentially, vectors can
transmit infectious agents in two ways. They can serve as a vehicle whereby the
infectious agent is conveyed from one host to another without undergoing a
stage of development or multiplication. This is known as mechanical transmission.
Alternatively, the infectious agent can undergo some stage of development or
multiplication in the vector - this is known as biological transmission
- and in this case the vector is serving either as an intermediate or
definitive host, depending on which stage of the development cycle of the agent
takes place within it. Vertebrate intermediate hosts play the same role in the
transmission of their disease agents as biological vectors.
In mechanical transmission the
agent is carried on the skin or mouthparts of the vector from an infected to a
susceptible host. The survival time of the agent in or on the vector is usually
short, and as a result the transmission of the agent has to be accomplished
rapidly. The carriers are normally winged haematophagous
insects, and transmission usually takes place when susceptible and infected
hosts are in close proximity and when large numbers of vectors are present.
In biological transmission,
since the agent develops in the vector, a period of time elapses between the
acquisition of the infectious agent by the vector and its becoming infective.
Once it has become infective, the vector may remain so, normally for a
considerable period if not the rest of its life. This provides more than a
single opportunity for disease transmission.
In addition, vectors may be
able to pass the agent on to their own offspring transovarially.
Transovarial transmission enables
an infectious agent to be maintained in a vector population through many
generations without that population having to be reinfected,
and, as such, the vector population remains a continuous source of risk. If transovarial transmission does not occur, at least one
stage in each generation of the vector must become infected before transmission
of the agent can take place.
Arthropod vectors that undergo
metamorphosis have the capacity to pass an agent from one developmental stage
to the next. This is known as transtadial transmission.
Usually in transtadial transmission, one
developmental stage becomes infected with the disease agent and the following
stage transmits it. If different developmental stages feed on different host
species, transtadial transmission can provide a
mechanism for an inter-species transmission of disease agents.
The main intrinsic
determinants in the host which can influence the frequency of occurrence of
infection and disease are species, breed, age and sex.
Species
susceptibilities and natural reservoirs
Most disease agents are
capable of infecting a range of animal species, both vertebrate and
invertebrate. The severity of the disease resulting from such infections may,
however, vary between the species concerned. While certain host species may be
refractory to infection with certain disease agents, e.g. equines to the
foot-and-mouth disease virus, very few disease agents are in fact restricted to
one host species.
The multi-species susceptibility
to disease agents is particularly important if the species concerned are able
to maintain the disease agent within their populations i.e. to function as natural
reservoirs of infection. The failure of programmes aimed at controlling
a certain disease in one species has often been blamed on the presence of
natural reservoir species, because they can reintroduce the infectious agent.
When investigating the
potential of a certain species to act as a natural reservoir of a particular
disease agent, and the implications this would have on disease control policy,
the following considerations need to be borne in mind:
Infection
with the disease agent.
Although it may be possible to
infect a certain host species with a disease agent under laboratory conditions,
this may only be achievable by using a method of transmission that does not
occur naturally (e.g. intracerebral inoculation). If
this is the case, that particular host species is unlikely to play a
significant role in the epidemiology of the disease.
Ability
of a host species to maintain a disease agent.
It may prove possible to demonstrate that a particular
host species can be infected by a certain disease agent and that that infection
can be accomplished by a natural means of transmission. A further question then
needs to be asked, namely, is that species capable of maintaining the agent
within its populations for significant periods of time? If this is not the
case, then although that particular species may be involved in the localised
spread of the disease agent during an outbreak, it will not serve as a
continuous source of infection. As such, the importance of that species in the
overall epidemiology of the disease may be reduced, and it may become possible
to contemplate a disease control programme in which control measures do not
have to be applied to that particular host species. In rinderpest
control, for example, it has proved possible to control and perhaps even
eradicate the disease by concentrating control measures solely on cattle populations,
in spite of the presence of species of wild game which are also susceptible to
the disease.
Transmission
from the natural reservoir.
Even if a species can function as a natural reservoir
for a particular disease agent, transmission from that reservoir to domestic
livestock may only occur rarely and in certain, clearly defined circumstances.
If this is the case, the reservoir species is unlikely to cause a major problem
in the initial control of the disease in question. However, when the frequency
of occurrence of the disease has been reduced to a low level, and eradication
of the disease becomes a possibility, the implications of the presence of
reservoir host species for the success of the proposed eradication programme
may have to be re-assessed.
Breed
susceptibilities
Within a host species, wide
ranges of susceptibility to a particular disease are often observed between
different breeds. In
Within breeds too, differences
in susceptibility to the same disease agent have been noted between strains or
families. This has led, in recent years, to the development of breeding
programmes designed to select for disease resistance. Selective breeding has
been pioneered in the poultry industry where a large number
of different "lines" of poultry have been developed that are
resistant to such diseases as Marek's disease, salmonellosis, and even vitamin D and manganese
deficiencies. Pigs, too, can be selected for their resistance to atrophic
rhinitis and some forms of colibacillosis. There are
breeding programmes in
Breeding for disease
resistance is probably most applicable as a disease control option in instances
where particular disease agents are ubiquitous in the environment, or of
non-infectious diseases caused by multi-causal determinants, or where other
methods of control have proved unsatisfactory.
Differences in species or
breed susceptibility to disease must be taken into account when introducing new
breeds or species into new environments. The new breed or species may be
exposed to disease agents to which the local breeds or species are resistant
but to which the new breed or species is highly susceptible. Conversely, the
imported breed or species may itself introduce a new disease agent to which it
is resistant but to which local breeds or species are susceptible. This factor
has become the cause for much concern in recent years given the rapid
development of international transport facilities whereby livestock and their products
can easily be conveyed from one part of the world to another. Furthermore,
because of improvements in the disease investigation and diagnostic facilities
of many veterinary services, disease agents are being identified that cause
little or no disease in indigenous livestock populations but which have the
potential to cause a severe problem in the more susceptible livestock
populations of other countries should these agents be imported. Bluetongue is
an example of a disease which has attained prominence in this way.
Age susceptibilities
Differences in susceptibility
to disease are often seen between different age groups. For example, young
animals are generally less susceptible to tick-borne diseases than older
animals. There is, however, often a problem in distinguishing between true age
resistance in young animals and passive resistance occasioned by the transfer
of maternal antibodies via the placenta or in the colostrum.
A false impression of age susceptibility may also be created when a highly infectious
disease occurs frequently in a population. It may, for instance, appear that
only young individuals are affected by the disease in question. This may not be
due to a difference in age susceptibility but simply because the older
individuals, who had been infected previously, represent a surviving and immune
population.
Sex
associations in disease
In these associations the
clinical signs of disease are associated with sexual attributes, as in the case
of diseases of the reproductive tract, rather than with the fact that males may
be more susceptible than females or vice versa. Sometimes, too, one particular
sex may be regarded by farmers as being of greater value than the other and
will therefore receive a correspondingly greater amount of care and attention
when sick.
Extrinsic determinants of disease
Extrinsic determinants of
disease are important in epidemiology in that they can have effects on the
host, on the agent, and on the interactions between the host and the agent.
They can also affect any intermediate hosts or vectors involved in the
transmission of a disease, and thus determine the type and extent of the
disease transmission taking place.
There are three major
extrinsic determinants. The first two are climate and soils, which, by interacting
in a variety of ways, affect the environment of the host, the agent, and the
intermediate host or vector, if they are present. The third major factor is
man, who, uniquely among animals, has the ability to modify both the
environment in which he lives and the environment in which he keeps his
livestock.
When considering climate as a determinant of
disease, a distinction is normally made between the macroclimate or weather,
and the microclimate. The term microclimate refers to the actual climatic
conditions prevailing in the specific, restricted environment where the host,
agent, vector or intermediate host actually live.
While man is as yet largely incapable of deliberately manipulating
macroclimates, he can control and manipulate microclimates to some extent.
Macroclimates. A large number of different factors combine to
make up the microclimate. Some of these factors (heat, cold, rainfall, wind,
humidity etc) can act as disease agents in their own right, either individually
or in combinations. As such they can cause disease in young and newborn animals
which are particularly sensitive to heat, cold and dehydration. In older
animals they tend to act more as indirect determinants of disease in that they
can produce either alone or in combinations with other managemental
and nutritional determinants - "stress" conditions in the host, which
may lower its resistance both to infection and, if infection takes place, to
disease.
Macroclimates can also affect
the ability of a disease agent, or its intermediate host or vector, to survive
in the environment. If the effects of weather on disease agents and their
intermediate hosts or vectors are known, it may be possible to predict when
host populations are at a particular risk of contracting disease and thereby to
implement appropriate control measures at strategic times. This approach has
been used with success in the control of such diseases as helminthiasis,
ticks and tick-borne diseases, trypanosomiasis,
foot-and-mouth disease, and in mineral and other nutritional deficiencies.
Microclimates. While macroclimates can have a direct effect on
microclimates, the study of macroclimates alone can frequently be misleading in
achieving an understanding of the epidemiology of a disease. Regions where
existing macroclimatic conditions might be thought unsuitable for the
transmission of a disease may, in fact, contain limited areas where the
microclimatic conditions are suitable for the survival of the disease agent and
its vector or intermediate host. (An example may be a water hole or an
irrigated pasture in an arid environment). Such areas often provide enhanced
conditions for disease transmission, since they may prove attractive to
livestock, particularly at those times of the year when the macroclimate is at
its most severe. If the host and the agent (and the vector or intermediate host, if they exist) are in close contact, the transmission
of disease can be effected rapidly and easily. Thus, in arid areas, the
transmission of such diseases as helminthiasis and trypanosomiasis may in fact take place during the dry season
when the hosts, the agent and the vector are all concentrated around permanent
water sources. High contact rates in these areas also favour the introduction
and transmission of rinderpest, foot-and-mouth
disease and contagious bovine pleuropneumonia.
By interacting with climate,
soils determine vegetation and the environment in which the livestock are kept.
The main effect of vegetation is on nutrition. Soils therefore act indirectly
as determinants of disease by causing starvation, if there is little or no
vegetation, or nutritiorial imbalances such as
protein, energy, vitamin or mineral deficiencies. Malnutrition can be the
direct cause of disease, or it can stress the host and thus increase its
susceptibility to infection and disease from other sources. Soils can also have
an effect on the ability of the agent to survive in the environment, through
such factors as waterlogging, pH etc.
Man is often able to create
favourable, artificial microclimates for livestock rearing by providing such
inputs as housing, water supplies, irrigation etc. Unfortunately, this often
results in the creation of conditions favourable for the survival of disease
agents and their intermediate hosts or vectors. This means that, by altering
the environment, man can alter the determinants of the diseases present in that
environment. The changes in determinants will favour some diseases and be
detrimental to others. Thus changes in systems and methods of production will
result in changes in the relative importance of the diseases present, with
perhaps some new diseases being introduced and others disappearing. The
epidemiologist should be alert to such changes and should attempt to predict
the likely effect that these will have on the overall disease picture, so that
potentially dangerous situations can be averted or controlled.
Man is also able to interfere
directly in the disease process through the use of drugs, vaccines, movement
controls, quarantines etc. Among the main tasks of the epidemiologist is the
investigation of the efficacy such measures, as well as to design ways in which
they can be used most efficiently and to monitor the effects of their
introduction on disease incidence.
Describing disease
events in populations
The first priority in investigating the epidemiology of a disease is to
describe accurately the nature of the problem being investigated. Comprehensive
and accurate description of disease problems often provides valuable insights
into the epidemiology of the disease being investigated and allows hypotheses
about likely determinants to be formulated.
A description of a disease
problem should specify the disease and the population at
risk, give information on the distribution of events in time and space,
and include an attempt to quantify disease events.
Disease
diagnosis. If the
disease is infectious in nature, the disease agent involved should also be
identified. For the disease agent to be infectious it must fulfil Koch's
postulates that:
- The agent should be present
in all cases of the disease;
- It can be isolated and grown in pure culture; and
- It should be capable of producing the disease when innoculated
into healthy animals.
One of the problems associated
with these postulates is that they do not take into account the differences
between different strains of agents, particularly in their virulence, pathogenicity, and infectivity, which may be important in
the epidemiology of the disease. We shall have more to say on the problems of
disease diagnosis in Chapter 4.
Populations
at risk. These can be identified by studying the
distribution of the disease within host populations by species, breed, age and
sex. Descriptions of population densities and movements are also of great
value, particularly when the disease is transmitted by contact.
Distribution
of disease events in time and space. This generally involves looking for the
"clustering" of disease events in time, space or both.
The clustering of disease
events in space can often be demonstrated by the use of conventional mapping
techniques. This type of clustering may indicate the presence of a particular
determinant or determinants (e.g. a vector, a mineral deficiency etc) in an
area. It should be remembered, however, that clustering in space occurs
naturally in the case of contact - transmitted diseases, and that it may also
be a function of host-population density.
The clustering of disease
events in time may indicate that the host population was exposed to a common
source of the disease or its determinant. Outbreaks of
diseases transmitted by such vehicles as water or foodstuffs frequently exhibit
clustering in time, as in the case of food poisonings. Seasonal clustering
of disease events often indicates the influence of climatic determinants in
some form or other.
The distribution of disease
events in populations in time and space can be described by three basic
descriptive terms. These are: endemic, epidemic
and sporadic.
An endemic disease
is a disease that occurs in a population with predictable regularity and with
only minor deviations from its expected frequency of occurrence. In endemic
diseases, disease events are clustered in space but not in time. Note that a
disease may be endemic in a population at any frequency level, provided that it
occurs with predictable regularity. Additional terms can be used to describe
endemic diseases according to their frequency of occurrence. Thus:
· Hyperendemic is an endemic disease that
affects a high proportion of the population at risk.
· Mesoendemic is an endemic disease that affects a moderate
proportion of the population at risk.
· Hypoendemic is an endemic disease that
affects a small proportion of the population at risk.
An epidemic disease
is a disease that occurs in a population in excess of its normally expected
frequency of occurrence. In an epidemic disease, disease events are clustered
in time and space. Note that a disease may be epidemic even at a low frequency
of occurrence, provided that it occurs in excess of its expected frequency.
A pandemic is
a large epidemic affecting several countries or even one or more
continents.
A sporadic disease
is a disease that is normally absent from a population but which can occur in
that population, although rarely and without predictable regularity.
Many epidemics of infectious
disease occur in a regular, cyclical fashion over a prolonged period of time.
This is because with an increasing frequency of occurrence of the disease in a
host population, the number of susceptible hosts
decreases as individuals within that population become infected, and then
either die or recover and become immune to reinfection.
As the number of susceptible hosts decreases, so does the opportunity for
disease transmission. This, in turn, means that the frequency of occurrence of
new cases of the disease declines. A period of time then elapses during which
new susceptible individuals are born into the host population. The number of
susceptible hosts in the population thus increases, and the opportunities for
the disease agent to find a susceptible host are enhanced. As a result the
frequency of occurrence of the disease may increase and a new epidemic may take
place.
When assessing the efficacy of
measures introduced to control epidemics, an attempt should be made to
distinguish between a decline in the frequency of occurrence of the disease due
to a control measure, and a natural decline in the epidemic cycle. Epidemics
can be prevented if the level of immunity in the host population can be
sustained. It is important, therefore, in instances where the control of an
infectious disease is being attempted by vaccination, that coverage be
maintained in the. host population even when the
disease is occurring rarely.
Morbidity and Mortality
Morbidity and Mortality conferences (M&M) are traditional, recurring
conferences held by medical services at academic medical centers and by most
large private medical and surgical practices. They are essentially peer reviews
of mistakes occurring during the care of patients. The objectives of a well-run
M&M conference are to learn from complications and errors, to modify
behavior and judgment based on previous experiences, and to prevent repetition
of errors leading to complications. Conferences are nonpunitive
and focus on the goal of improved patient care. M&M conferences occur with
regular frequency, often weekly, biweekly or monthly, and highlight recent
cases and identify areas of improvement for clinicians involved in the case.
They are also important for identifying systems issues (e.g., outdated
policies, changes in patient identification procedures, arithmetic errors,
etc.) which affect patient care.
Morbidity and Mortality
conferences have a long tradition in the practice of medicine, having
originated in the early 1900s with Dr. Ernest Codman at Massachusetts
General Hospital in Boston. It is almost 100
years since Ernest Codman wrote a monograph on this subject, which caused his
colleagues to banish him from the
How
do I choose a study type?
·
Ensure that it directly addresses your research question. There is no point
performing a study which will not answer the question in hand. Many study types
can address the same question, so choose a design carefully.
·
Make sure the study is ethical. Epidemiology usually involves the active
cooperation of patients. They usually participate for the good of research
rather than for any benefit which they stand to gain. The ideal study must be
ethically sound and ought to minimise the invasiveness to the participants.
·
Work within your budget. Epidemiological studies tend to be much larger
than other scientific experiments and resources are always limited. Patient
recruitment and assessment take time and money. You need to consider the cost
of collection and testing of biological samples, telephone calls and postage,
and of course salaries--personnel resources have high costs attached. The cost
of the research can preclude certain study designs.
·
Make sure the results will be valid. The most frequent flaws in
epidemiology are bias and confounding. Bias produces incorrect results and can
rarely be rectified after data collection. Confounding can be addressed during
statistical analysis (number crunching), provided that sufficient information
was gathered during the study. Ways to avoid these two hazards will be
discussed in the next article
The
six study designs that you need to know
- Case series--what clinicians see
- Ecological--geographical comparisons
- Cross sectional--survey, a snapshot in time
- Case-control--compare people with and without a
disease
- Cohort--follow people over time to see who gets
the disease
- Randomised controlled trial (RCT)--the human
experiment
Hierarchy
of evidence
There are six main types of
epidemiological study to choose from. Each design is ranked according to what
was traditionally thought of as its usefulness in providing accurate results.
This ranking is sometimes referred to as the hierarchy of evidence, with
stronger evidence coming from the studies later rather than earlier on in the
list.
Case series
Lowest in the pecking order is
the case series. This is simply a description of cases. Importantly,
there is no comparison group and so case series are often not considered as
epidemiology. They describe patients' characteristics, and may generate ideas
for future studies. They can also be misleading though. For example, in the
early 1980s, doctors noticed that patients with immune system deficiencies
tended to be young homosexuals. That observation suggested that their symptoms
were caused by the use of "poppers" (amyl nitrates--sexual
stimulants). Experiments of the immunological properties of amyl nitrates were
underway before the HIV virus was identified.1 The use of case
series is clearly limited, although that should not deter clinicians from
observant monitoring of unusual patients.
Ecological studies
Second in our hierarchy comes
the ecological study, when we compare groups of people not individuals.
Assuming that associations seen on a group level also hold on an individual
level leads to ecological bias. Consider a study of suicide and
religion.2 Higher suicide rates occurred in
regions where a higher proportion of protestants lived. To infer that protestants are more likely to commit suicide than people of
other religions may be incorrect. Although the rates are higher in the regions
with more protestants, we do not know the religion of
the people committing suicide. Suicide could be more common among religious
minorities who live in predominantly protestant regions. However, with careful
interpretation of results, ecological studies do have benefits. They are
generally quick, cheap, and can be performed from data which are published
routinely--for example, death rates, per caput income, national food
consumption.
Cross sectional study
A cross sectional study
is a snapshot in time--that is, a survey. Participants are picked from a well
defined population. Exit polls on voting day are cross sectional studies, where
the population is all voters exiting from a particular polling station. We
contact people only once, so these studies are relatively cheap. But that
limits their usefulness, since we can study only current diseases (prevalence),
and cannot identify when people first get a disease (incidence). If we are
interested in whether a certain behaviour may cause a
disease we may infer incorrect results. People may change their behaviour once
they get a disease. This concept of reverse causality will be discussed
in the next article.
Case-control studies
Choosing your participants on
account of their disease is the basis of a case-control study. On face
value, this seems a simple study design, where cases are people with the
condition and controls are those without. Suitable control selection can be tricky,
and unsuitable controls can invalidate your results. Suppose that you want to
know whether smokers are at an increased risk of colon cancer. Comparisons are
made between the smoking habits (probably current and past) of cases and
controls. It is no good choosing controls who have lung cancer or heart
disease, as they will be more likely to be smokers than the population from
which the cases came, and that will distort your results. Another risk of
case-control studies is recall bias, which occurs if cases and controls
recall past events differently. Because we actively choose the cases, a
case-control study ensures that we find enough people when a disease is rare.
These studies are rarely suitable for investigating causes of death, since dead
people cannot provide vital information. Carefully designed case-control
studies can provide useful results, and such studies should not be ignored
without a careful evaluation of the methodology used.
Cohort studies
In a cohort or follow
up study, a healthy group of people (cohort) are identified. They are then
followed over time to see who develops the disease of interest and who does
not. The important point to remember about cohort studies is the time
factor--that at the beginning of the study neither the people themselves nor
the researchers know who is going to get what disease. This effectively avoids
recall bias, although other types of bias can still hinder these studies.
However, the costs of cohort studies are sometimes prohibitive. If you are
studying mobile phone use and cancer development you need to follow up people
for a long time before the cancer becomes evident. The resource implications is often why cohort studies are not chosen in
epidemiology.
Randomised controlled trials
Finally, what is often called
the gold standard of epidemiological studies--the randomised controlled
trial or clinical trial. This is a human experiment, where people are
randomly assigned to receive one treatment or the other. This treatment is
often a drug as clinical trials of drugs are required before being licensed for
prescription. The treatment may also be a health intervention, such as a weight
loss or smoking cessation programme. It is necessary that the individual (and
preferably also the health professional) are "blind" to which
treatment a person receives, although this is not always possible. In clinical
trials, the aim is to replicate the "real life" situation, so that
the results obtained are as close to what would happen if the treatment was
used in a real life situation. Clinical trials tend to be extremely expensive,
and are unsuitable for use in some situations. For example, it is not ethical
to randomise people to heavy drinking to investigate the effect of its use on
breast cancer.
Considerations
when choosing a study type
- Does this design address my question?
- Is this study design ethical?
- What resources do I have (time, money,
personnel)?
- Is there a cheaper or quicker way of answering
the same question?
Example
of study design
As an example of how to choose
a study, I will return to the study of orgasms and mortality in middle aged
men.3 Which of the study types described
above would answer the question of whether sex and death are related?
A case series of people
who have died would not be useful--given the frequency of the exposure
(orgasms) and the outcome (death), there would be nothing that would stand out
in a study of all people who died. Remember, there is no comparison group.
In an ecological study,
we would compare rates of orgasm and death across different geographical areas.
But how would we find out orgasm rates per area? And would these differ
sufficiently across areas to be able to correlate them with death rates?
A cross sectional study
by its nature excludes dead people. We could do a survey of women, asking them
about the frequency of their partner's orgasms, and ask if the partner is still
alive. But how accurate are reports from women regarding their partner's
orgasms? (That approach might be more accurate than asking men directly!) In
addition, it may be too distressing to ask recently widowed women about their
sex life.
Similar problems would be
encountered with a case-control study. Such studies of mortality always
rely on proxy information--for example, from a partner rather than the
individual. The cases would be people who had recently died. But who would be
the controls? Brothers? Neighbours?
The method the authors chose
was the cohort study, when people were asked about their sex life then
followed up for 10 years. This is not without its problems, although these are
more issues of interpretation than design, so will be considered in the next
article.
Finally, could they have done
a randomised controlled trial, allocating men to groups that have
frequent, infrequent, or no sex. In that case
recruitment would have been pretty difficult--would you open yourself to the
option of no sex?
And finally...
As you will have gathered from
the series of questions above, there is no clear cut answer to which study
design to use. Often two or more designs are possible, and then practical
("how much time and money do I have?") and qualitative ("which
study will give better results?") considerations help to make the choice.
The ability to choose a useful study design is an art which improves with
practice
The Role of the Occupational
and Environmental Health Nurse
Occupational and Environmental
Health Nursing is a specialty that provides health and safety programs to
workers and community groups. An Occupational Health Nurse (OHN) focuses on
promotion and restoration of health, prevention of illness and injury, and
protection from work-related and environmental hazards. Occupational and
environmental health nursing began in the
OHNs make independent nursing
judgments and are capable of designing and delivering health care to
employee-based populations. According to a survey conducted by the American
Association of Occupational Health Nurses in 1992, approximately 50% of nurses
are sole health-care providers at the worksite. Their position requires a broad
scope of knowledge and skills in many areas. The nurse provides emergency care
and follow-up case management for job-related injuries and illnesses, providing
the most efficient and effective care for the injured worker. The goal is to
return the injured worker to his or her job as soon as possible. Early
intervention by the nurse reduces workers' compensation costs and also gets the
employee back to work. The nurse acts as a counselor
and also recommends referrals to the company's employee-assistance program and
other community resources.
OHNs develop health promotion
programs for employees and teach them the skills needed to become responsible
for their own health. Most health services offer smoking-cessation programs,
exercise and fitness, nutrition, and weight-control programs. If necessary, the
OHN can educate an employee in the control of chronic illness and can provide
information needed to direct them to effective health-care resources. Health
education and prevention programs are effective in the early detection of
symptoms that can lead to long-term catastrophic illness.
There are numerous regulations
that protect today's worker, and the OHN must work with employees and employers
on compliance with the many regulations and laws affecting the workplace. The
OHN must have knowledge of the following laws and regulations: Occupational
Safety and Health Administration (OSHA), Family Medical Leave Act (FMLA), The
Americans with Disabilities Act (ADA), Workers' Compensation Act, and the
Health Information Portability and Accountability Act (HIPPA).
The role of the nurse will
continue to expand as more nurses are hired by businesses to manage and operate
occupational health services. Employers pay about $1 trillion annually for
employee health, so business executives are looking to OHNs
to maximize employee productivity and to decrease cost through lowered
disability claims, reduction of on-the-job injuries, and improvement in
absentee rates.
OHNs are registered nurses (RNs),
licensed to practice in the states in which they are employed. Typically,
nurses entering the field have a baccalaureate degree in nursing and experience
in community health, ambulatory care, critical care, or emergency nursing.
Certification in Occupational
and Environmental Health Nursing is highly recommended. Criteria for
certification requires 4,000 hours of work experience in the field within 5
years, 50 contact hours of continuing education in the specialty, and
successful completion of a national examination.
The OHN's
role ranges from clinician to case manager, health educator, manager, policy
maker, consultant, and program evaluator. While it's challenging to be all
things to everyone, the occupational health service affords the OHN a great
opportunity for providing excellence in the delivery of health care while it
provides an excellent career opportunity.
As the workplace continues to
change, nurses must be prepared to handle the challenges and opportunities as
employers look to OHNs to be cost-effective providers
of work place health care. The most fundamental goal of any organization is to
earn a profit while providing a safe and healthy working environment for its
employees. The occupational health service exists to support that goal.
Summary
References
Brucker, M. C. (2005). Providing evidence-based care: You can understand
research and use it in practice. AWHONN Lifelines, 9(1), 47–55.
Bradford-Hill,
A. (1971). Principles of medical statistics (9th ed.).
Centers for Disease Control and
Prevention. (1993,
September 10). Public health focus: Physical activity and the prevention of
coronary heart disease. Morbidity
and Mortality Weekly Report, 42, 398–400.
Centers for Disease Control and
Prevention. (1983, August
5). Update: Toxic shock syndrome—
Centers for Disease Control and
Prevention. (1981, June
30). Toxic shock syndrome—
Centers for Disease Control and
Prevention. (1980,
September 19). Follow up on toxic shock syndrome. Morbidity and Mortality Weekly Report,
29(37), 441–445.
McFarlane, J,
MacMahon, B., & Pugh, T. F. (1970). Epidemiology: Principles and
methods.
Sinauer, N., Bowling, J. M., Moracco, K. E., Runyan, C. W., & Butts, J. D. (1999). Comparisons among female homicides occurring in rural,
intermediate, and urban counties in
Snow,
J. (1936). Snow on cholera,
being a reprint of two papers by John Snow, M.D., together with a biographical
memoir by B. W. Richardson, M.D., and an introduction by Wade Hampton Frost,
M.D.
Further
Aschengrau, A. & Seage,
G. R. (2003). Essentials of epidemiology in public
health.
Chernick, K. M. & Friis, R.(2003).
Introductory
biostatistics for the health sciences.
Cravens, G., & Mair,
J. L. (1977). The black death.
Crichton, M. (1969). The Andromeda
strain.
Dunne,
T. L. (1978). The
scourge.
Everitt, B. (2003). Modern medical
statistics: A practical guide.
Friis, R. & Sellers, T. (2004). Epidemiology for
public health practice. (3rd ed.)
Savitz, D. (2003). Interpreting
epidemiologic evidence: Strategies for study design and analysis.
Selvin, S. (2004). Statistical analysis of
epidemiologic data (3rd ed.).
Timmreck, T. (1998). An introduction to epidemiology (2nd ed.).
Valanis, B. (1992). Epidemiology in
nursing and health care (2nd ed.).
Internet Resources
http://www.cdc.gov/mmwr, The
Centers for Disease Control and Prevention has morbidity and mortality weekly
reports by state and select cities along with reportable disease trends. This
is an excellent site for information on measures and determinants of community
health.
http://www.cdc.gov/nchs,
CDC's
http://www.epidemiolog.net,
This site contains epidemiology learning materials,
including a free online evolving textbook.