descriptive epidemiology

2,000 views

Published on

0 Comments
4 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
2,000
On SlideShare
0
From Embeds
0
Number of Embeds
67
Actions
Shares
0
Downloads
120
Comments
0
Likes
4
Embeds 0
No embeds

No notes for slide
  • excluding births at women's with previous a perinatal death , cross section, all births
  • descriptive epidemiology

    1. 1. DESCRIPTIVE EPIDEMIOLOGY: PERSON , PLACE AND TIME.
    2. 2. Typically, epidemiology is divided into twocomponents: descriptive epidemiology andanalytic epidemilogy.Descriptive epidemiology focuses on identifyingand reporting both the pattern and frequency ofhealth events in a populationanalytic epidemiology focuses on the search forthe determinants of health outcomes.These two components work together toincrease our understanding of the healthpopulation
    3. 3. The figure below shows the usual cycle of epidemiologic analysis
    4. 4. This cyclic process is at work in maternal and childhealth (MCH) when we conduct an analytic studybased on the descriptive information obtained throughsurveillance and monitoring activities or needsassessments.Likewise, when analytic work identifies a new riskfactor, we incorporate this new variable into oursurveillance and monitoring activities.For example, as analytic research showed evidence ofa relationship between smoking and alcoholconsumption during pregnancy and adverse birthoutcomes, these risk factors were added to the birthcertificate in order to include them in routinesurveillance activities. Similarly, the descriptive reporting of unintentional andintentional injuries spurred analytic work that led to theunderstanding of violence as a public health problemand the identification of risk and protective factors forthe development of effective intervention strategies.
    5. 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. 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. 7. TIME Time characteristics include cyclical changes, long term secular trends, and even daily or hourly occurrences during an epidemic.
    8. 8. PERSON While person characteristics are attributes of individuals, place and time characteristics are attributes of the physical and social environment.
    9. 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. 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. 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. 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. 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. 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. 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. 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: CDCs 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. 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.
    18. 18.  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).
    19. 19. 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.
    20. 20. 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.
    21. 21.  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.
    22. 22. 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.
    23. 23. The Relationship Between Age and Time For example, during the 1960s and early 1970s, 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.
    24. 24.  Unopposed estrogen therapy had not been offered to women prior to the 1960s and early 1970s, 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.
    25. 25.  As weve 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.
    26. 26. Test Yourself Question:Think about an outcome of interest in your health agency. Can you describe theoccurrence of this health outcome according to person, place, time? Answer:Example: Ectopic pregnancyEctopic pregnancy is defined as pregnancy occurring outside of the uterus, the mostcommon type of which is tubal pregnancy. Ectopic pregnancy is the leading cause ofmaternal mortality in the first trimester of pregnancy, with case-fatality rates highestamong young African-Americans. The following describes the occurrence of ectopicpregnancy according to person, place and time characteristics. Person: rates are higher in older women, black women, women of low gravidity andparity. Place: for the period 1970-1989, the highest rates of ectopic pregnancy were in thesouthern part of the US. Time: there have been rising rates of ectopic pregnancy since the 1970s; this is aworldwide phenomenon.

    ×