Descriptive epidemiology focuses on identifying patterns and frequencies of health events in populations. It considers person, place, and time characteristics. Person characteristics describe demographic and behavioral attributes of individuals. Place characteristics describe geographic and environmental attributes. Time characteristics describe cyclical or secular trends. Together, person-place-time variables describe how health outcomes result from interactions between individuals and their environment.

1. DESCRIPTIVE EPIDEMIOLOGY:
PERSON , PLACE AND TIME.

2. Typically, epidemiology is divided into two
components: descriptive epidemiology and
analytic epidemilogy.
Descriptive epidemiology focuses on identifying
and reporting both the pattern and frequency of
health events in a population
analytic epidemiology focuses on the search for
the determinants of health outcomes.
These two components work together to
increase our understanding of the health
population

3. The figure below shows the usual
cycle of epidemiologic analysis

4. This cyclic process is at work in maternal and child
health (MCH) when we conduct an analytic study
based on the descriptive information obtained through
surveillance and monitoring activities or needs
assessments.
Likewise, when analytic work identifies a new risk
factor, we incorporate this new variable into our
surveillance and monitoring activities.
For example, as analytic research showed evidence of
a relationship between smoking and alcohol
consumption during pregnancy and adverse birth
outcomes, these risk factors were added to the birth
certificate in order to include them in routine
surveillance activities.
Similarly, the descriptive reporting of unintentional and
intentional injuries spurred analytic work that led to the
understanding of violence as a public health problem
and the identification of risk and protective factors for
the development of effective intervention strategies.

5. PERSON, PLACE, AND
TIME
Descriptive epidemiology focuses on both the pattern
of health events as well as on their frequency in
populations.
Within the field of epidemiology, there are three types
of data that are necessary for describing the patterns
of health and disease in human populations.
These three pillars of descriptive epidemiologic
analysis are:
 1. Person
 2. Place
 3. Time

6. PERSON
 Person characteristics include sociodemographic
characteristics such as age, race/ethnicity, education,
income, insurance status, occupation, parity, and
marital status as well as behaviors such as substance
abuse, diet, sexual activity or use of health care
services. Place characteristics include geographic
location (e.g., urban versus rural), features of the
geography (e.g., mountainous region, area with wells
as the major water source), population density, as
well geo-political boundaries (e.g., census tracts,
cities, counties, or states), and location of worksites,
schools, and health facilities.

7. TIME
 Time characteristics include cyclical
changes, long term secular trends, and
even daily or hourly occurrences during
an epidemic.

8. PERSON
 While person characteristics are
attributes of individuals, place and time
characteristics are attributes of the
physical and social environment.

9.  These person-place-time variables are person
characteristics expressed in units of geography and
time.
.
 Examples of this type of variable include the annual
crime rate in a city, the extent of neighborhood
segregation during a given time period, and the
percent of low-income individuals living in a county
during a given year
 By jointly considering person, place, and time,
epidemiology advances the idea that health and
disease result from the interaction between
individuals and their environment.
 While we can all list various person, place and time
characteristics without much effort, it is important to
understand what these characteristics actually
represent so that we use them appropriately person,
place and time characteristics without much effort, it
is important to understand what these

10. Person Characteristics
 Person characteristics are fundamental to
describing health events.
 They are used to describe whether a
particular risk factor or outcome is more
prevalent in one population than another, or
to describe whether the relationship between
a risk factor and an outcome is more salient
for one population than another.
 When using person characteristics to
describe health events there are some issues
that need to be considered.

11. Risk Factors vs. Risk
Markers
 Often by virtue of their strong association with
an outcome, some person characteristics are
themselves considered to be demographic
risk factors.
 For example, the Institute of Medicine’s
report, Preventing Low Birth weight lists five
demographic risk factors for low birth weight
(LBW): age, race (black), low socioeconomic
status, being unmarried and having a low
level of education.

12.  A risk factor directly increases the risk of a
health outcome, implying a causal link; a risk
marker is associated with a health outcome
with no assumption of causality.
 Only if a person characteristic is an actual
determinant of a health outcome, is it truly a
risk factor.
 Otherwise, it is merely risk marker, acting as
a proxy for another variable, because this
other variable is either unavailable in the
data-set or is yet to be discovered or
confirmed as a risk factor.

13. Defining and Categorizing
Person Characteristics in
MCH
 While it is important to understand the meaning of person
variables, it is also important to be knowledgeable about the
meaning of the boundaries used to define categories within the
variable. What categories of the variable were used to collect
the data and/or describe the data? For example, does the
category "unmarried women" include women who were divorced
or widowed as well as those who were never married? Does the
category "adolescents" include 18 and 19 year olds along with
youth less than 15years of age? It is important to choose
appropriate definitions and categories for the variables under
consideration so that our efforts are grounded in the current
knowledge base with respect to the variable (s) of interest and
so that our findings can be compared with others who are doing
similar work. Some key person variables used in MCH are
described below.

14. Maternal Age.
 Maternal age is not a straightforward variable. The effect of a
woman’s age may represent operative genetic phenomena. A
classic example of this is the association between Down’s
syndrome and increasing maternal age. On the other hand, the
increased risk of an outcome associated with a particular
maternal age group may represent the effect of the
environment; exposure to a teratogenic agent at certain ages,
for instance, can result in an increased risk of adverse outcome.
Alternatively, an age effect may represent the interaction of
genetics and the environment; for example, maternal age in
conjunction with differential use of diagnostic technology and
induced abortion may contribute to higher prevalence of genetic
or chromosomal abnormalities for certain age groups. An
association with maternal age may also be indirect, reflecting
the impact of other factors such as parity, rather than a direct
effect of maternal age itself.

15. Child Age
 When describing the occurrence of health events
in children, the focus is usually on age groups that
are considered to represent distinct biological, social
and/or developmental periods of grow than behavior,
such as less than one year, or 15-17 years.
Sometimes there is uncertainty as to whether a
child’s age places them at risk for a particular
outcome because of biological or non-biological
processes and sometimes there is interaction
between these two phenomena. Again, while the
tendency may be assume that the age categories for
children represent primarily biological processes, it is
likely that understanding the social and development
processes associated with these distinct age groups
is as, if not more, important.

16. Race/Ethnicity.
 Race and ethnicity are associated with major differences in
exposure to risk factors, in health service utilization, and in
health status. While the way in which race/ethnicity variables
are used often implies direct causal links between skin color or
heritage and health status outcomes, race/ethnicity variables,
except in a very few instances, are representative of social,
economic or community processes or factors. It is usually more
appropriate, therefore, to consider these variables as risk
markers rather than risk factors. As the Centers for Disease
Control and Prevention has stated in its monograph From Data
to Action: CDC's Public Health Surveillance for Women, Infants,
and Children, "The designation of race and ethnicity is often
problematic, and definitions may vary from one data collection
activity to another . Race is frequently a marker for a variety of
cultural, economic, and medical factors, and these factors must
be taken into account when assessing the effects of race on
health outcomes."

17. Parity
The total number of viable pregnancies, including live births and fetal
deaths—and the related variables of prior reproductive outcome and
birth order are all associated with maternal, infant and child health
status. Knowledge of these variables is important because:
 1. the outcome of one pregnancy tends to be repeated in the next;
 2. a prior pregnancy outcome may affect the mother’s current status vis
o vis work or schooling; and,
 3. behaviors or conditions present in one pregnancy may be repeated
in the next.
 Of note, the association of higher parity with adverse pregnancy
outcomes may not be a reflection of parity itself but rather a reflection of
other maternal factors that influence which women have more births.
Therefore, when we examine typical j-shaped curves, which show the
relationship between parity and pregnancy outcomes in a cross-
sectional fashion (at a given point in time), it is important to consider the
cohort of women contributing to each parity grouping.

19.  In the figure on the preceding page, the cross-
sectional curve (dotted line in the first grid) suggests
that the highest risk of perinatal mortality occurs
among women of both low and high parity. When we
examine the different cohorts of women contributing
to this cross-sectional curve, however, we can see
that the highest risk of perinatal mortality occurs at
each birth among the cohort of women who are high
parity when they complete their childbearing. For
example, even the first infants born to these high
parity women have an elevated mortality risk
compared to the first infants born to women who
remain at low parity. Also of interest is that within the
high parity cohort, although each infant is at higher
risk than infants in lower parity cohorts, the risk of
perinatal death actually decreases with each
subsequent birth. This relationship holds even when
women with previous perinatal deaths are excluded
from the analysis (second grid).

20. Place Characteristics
 Place is central to epidemiology, whether the place demarcation
is characterized using geo-political subdivisions or natural
boundaries. When describing health events by geography, for
example rates by county or proportions in urban versus rural
areas, it is important to ascertain whether geographic
differences represent unique features of the physical, social,
economic, political, or health services environment. Public
health professionals typically use geographic demarcations to
compare how particular geo-political entities are faring with
respect to health outcomes of interest. In addition, it is often
necessary to identify if a health event or health outcome is
clustered in a particular space, or in space and time. Usually,
the objective is to identify whether the cluster reflects a true
difference in exposure or a reflection of variations in population
characteristics, variations in diagnosis and reporting, or
variations in access to, utilization of, or effectiveness of health
care services. When using geographic characteristics to
describe health events there are some issues that need to be
considered.

21. Characteristics to describe health
events there are some issues
that need to be considered.
 Size and Level:When examining
differences across geographic entities
consideration should be given to the size and
level of the political subdivisions to be
compared. It is important to ascertain the
level at which the relationship between a risk
factor and an outcome is most salient as well
as most amenable to intervention and to
understand the different types of interventions
possible at the various geographic levels
such as county, city, or community area.

22.  Availability and Stability of
Data:When examining data in small
geographic entities, either those that
are physically large but have low
population density, or those that are
small by definition such as
neighborhoods, it is essential to
consider issues of data availability and
data stability. In these situations it will
probably be necessary to use
techniques developed for small area
analysis.

23. Time Characteristics
 Examining trends over time is one of the most basic tools of
epidemiology. It is a general assumption of Western culture that
as our knowledge base and our technological skills grow over
time, there should be concomitant improvement in health
outcomes. There is also the recognition that as new hazards
emerge Or as familiar hazards reach new populations, some
health indicators may regress or deteriorate over time. As health
professionals we are interested in exploring whether population
characteristics, access to resources and health services, as well
as health outcomes change over time. Of specific interest are
changes in patterns of health events over long periods of time
known as secular trends. Also of specific interest are patterns of
health events that occur cyclically, such as seasonal
occurrences. The greater incidence of SIDS (Sudden Infant
Death Syndrome) in the late fall/early winter months is an
example of a cyclically occurring health event. When using time
characteristics to describe health events there are some issues
that need to be considered.

24. The Relationship
Between Age and Time
 For example, during the 1960's and early 1970's, the incidence
rate of endometrial cancer rose dramatically, particularly among
women ages 45-64. This was not, however, a function of their
age perse, but was due instead to the common experience of
the cohort of women in this age group at that particular time in
history. Many women in this cohort had been prescribed
unopposed estrogens as treatment for the symptoms of
menopause. In late 1975, however, two papers documented the
association between unopposed estrogens and endometrial
cancer, and subsequently use of this treatment was sharply
curtailed leading to a corresponding decrease in the rates of
endometrial cancer in this age group.

25.  Unopposed estrogen therapy had not been
offered to women prior to the 1960's and
early 1970's, and once estrogen therapy was
identified as conferring cancer risk, it was of
course not offered to women after1975. If we
looked at all women at one point in time, for
example 1970, it might appear that women
ages45-64 were at increased risk for
endometrial cancer; if, however, we looked
separately at the different birth cohorts of
women, we would see that this apparent
increase in risk was an artifact.

26.  As we've just seen, the time variable in
epidemiology often reflects the effects of
history. These effects include changes in
culture, in the economy, in the political
climate, in the use of technology, and
advances in science as well as major
historical events or interventions. For
example, the introduction of surfactant in the
very late 1980’s is associated with the
increased survival of very low birth weight
infants. The forces of history as manifested
by changes over time may have an
independent association with health
outcomes or may affect the manifestation of
many individual risk factors or risk markers
used to describe or explain health outcomes.

27. Test Yourself
 Question:
Think about an outcome of interest in your health agency. Can you describe the
occurrence of this health outcome according to person, place, time?
 Answer:
Example: Ectopic pregnancy
Ectopic pregnancy is defined as pregnancy occurring outside of the uterus, the most
common type of which is tubal pregnancy. Ectopic pregnancy is the leading cause of
maternal mortality in the first trimester of pregnancy, with case-fatality rates highest
among young African-Americans. The following describes the occurrence of ectopic
pregnancy according to person, place and time characteristics.
 Person: rates are higher in older women, black women, women of low gravidity and
parity.
 Place: for the period 1970-1989, the highest rates of ectopic pregnancy were in the
southern part of the US.
 Time: there have been rising rates of ectopic pregnancy since the 1970's; this is a
worldwide phenomenon.