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Chapter 5 Descriptive Epidemiology According to Person, Place, and Time

© 2010 Jones and Bartlett Publishers, LLC Descriptive epidemiology allows us to:  Describe the extent of a public health problem according to person, place, and time.  Communicate a public health problem with the use of tables and graphs.  Identify who is at greatest risk for selected health-related states or events.  Use surveillance methods to monitor whether unusual health related states or events exist and evaluate public health intervention programs.  Understand how descriptive epidemiology can provide clues as to the causes of disease.

© 2010 Jones and Bartlett Publishers, LLC Person  Descriptive data on person answers to WHO question.  Descriptors often include: Age Sex Race/ethnicity Marital and family status Occupation Education

© 2010 Jones and Bartlett Publishers, LLC Place  Descriptive data by place addresses WHERE question  These data often involve comparisons between or among geographic regions, in groups before and after migration, and between twins raised in different settings

© 2010 Jones and Bartlett Publishers, LLC Time  Epidemiologic investigations range from hours to weeks, years to decades  Short-term disease incubation periods of a few hours can be as important to the epidemiologist as long-term latency periods for chronic diseases spanning decades  Another term used occasionally to describe time factors in epidemiology is temporal, which means time or refers to time-related elements or issues

© 2010 Jones and Bartlett Publishers, LLC Communicating health data and identifying who is at greatest risk  Tables and graphs summarize and describe data in a way that can be easily interpreted  Some examples follow

© 2010 Jones and Bartlett Publishers, LLC In accordance with the 2000 standard population. MalesFemalesRatio All causes Diseases of the heart Cerebrovascular diseases Malignant neoplasms Chronic lower respiratory diseases HIV/AIDS Motor vehicle-related injuries Homicide Suicide Firearm-related injuries Occupational injury Age-Adjusted Cause-Specific Death Rates Per 100,000 for Males and Females in 2005 in the United States

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Death rates for motor vehicle-related injuries in the United States according to age in 1960 and 2005.

© 2010 Jones and Bartlett Publishers, LLC Fatal occupational injury rates by state, 2002

© 2010 Jones and Bartlett Publishers, LLC Remaining life expectancy at selected ages by race and sex: United States, 2005

© 2010 Jones and Bartlett Publishers, LLC Dependency Ratio  Population <15 and 65+ divided by the population  Multiply by 100 to express as %  Interpretation. There are ___ dependents for every 100 people of working age.

© 2010 Jones and Bartlett Publishers, LLC Dependency ratio in the US  2000 – 51% There are 51 dependent for every 100 people of working age  2025 – 61%  There are 61 dependent for every 100 people of working age  2050 – 67%  There are 67 dependent for every 100 people of working age

© 2010 Jones and Bartlett Publishers, LLC Types of trends  Secular trends – represent long-term changes in health-related states or events  Short-term trends – usually brief, unexpected increases in health-related states or events  Cyclic trends – represent periodic increases and decreases in the occurrence of health-related states or events

© 2010 Jones and Bartlett Publishers, LLC Cyclic trend: Example #2

© 2010 Jones and Bartlett Publishers, LLC Surveillance  Medical  Public health

© 2010 Jones and Bartlett Publishers, LLC Public Health Surveillance  Implicit in descriptive epidemiology is the notion of public health surveillance.  What is Public Health Surveillance?  The systematic ongoing collection, analysis, interpretation, and dissemination of health data.

© 2010 Jones and Bartlett Publishers, LLC Why surveillance data?  Monitor To identify sudden changes in occurrence To follow long-term trends and patterns To identify changes in risk factors  As a result, we identify whether Does a health problem exist? Is the problem getting worse?

© 2010 Jones and Bartlett Publishers, LLC Some explanations for observed changes in the frequency and pattern of cases in a surveillance system, which are not due to changes in risk exposures, include Inconsistent interpretation and application of the case definition Change in the case definition Change in surveillance system/policy of reporting Improved diagnosis (e.g., new laboratory test, increased physician awareness, a new physician in town) Change in diagnostic criteria Change in reporting requirements Change in the population Change in the level and emphasis on active case detection Random events Increased public awareness

© 2010 Jones and Bartlett Publishers, LLC Some explanations for observed changes in the frequency and pattern of cases in a surveillance system, which are not due to changes in risk exposures, include Inconsistent interpretation and application of the case definition Change in the case definition Change in surveillance system/policy of reporting Improved diagnosis (e.g., new laboratory test, increased physician awareness, a new physician in town) Change in diagnostic criteria Change in reporting requirements Change in the population Change in the level and emphasis on active case detection Random events Increased public awareness

© 2010 Jones and Bartlett Publishers, LLC Surveillance for evaluation  Health programs may be aimed at Increasing vaccination levels Reducing smoking Increasing fruit and vegetable consumption Increasing physical activity Decreasing obesity Increasing screening

© 2010 Jones and Bartlett Publishers, LLC Vaccine preventable disease  State public health officials monitor vaccine preventable disease rates  May signal that the vaccination program is not reaching specific at-risk populations  Monitoring rates by racial/ethnic groups, for example, may show that the increasing rate only exists among a given minority group  Do barriers exist related to culture, language, and access to care.  The vaccination program should then be altered to address these barriers

© 2010 Jones and Bartlett Publishers, LLC Value of a surveillance program determined by  Whether appropriate actions have been taken to date as a result of information from the surveillance system  Whether the information has been used to make decisions and take action  Whether monitored prevalence of the outcome variable relates to the level and distribution of services available  Whether the information may be used in the future

© 2010 Jones and Bartlett Publishers, LLC Causal insights from descriptive epidemiology  Plotting health-related states or events over time can give the epidemiologist insights into probable determinants of disease  If a disease occurs only in the summer, then that is when the epidemiologist searches for causal factors

© 2010 Jones and Bartlett Publishers, LLC Causal insights from descriptive epidemiology  Studies involving geographic comparisons of disease frequency between groups, states, countries, migration studies, and twin studies have further yielded important insights into the respective roles genetic and environmental forces have on disease.

© 2010 Jones and Bartlett Publishers, LLC Final thoughts  Confounding factors are always a threat in descriptive studies  Analytic epidemiologic studies are better for minimizing the threat of confounding  Nevertheless, descriptive studies are a good first step in the search for causes of health-related states or events