Descriptive Epidemiology Lecture 2, Chapter 4 PDF

Descriptive Epidemiology Dr Muhammad Ahmed Alshyyab Lecture 2 Chapter 4 Lecture objectives To identify and discuss the descriptive epidemiology data sources regarding Surveillance systems. To identify the Epidemiologic variables in terms of, person. Pass...

Descriptive Epidemiology Dr Muhammad Ahmed Alshyyab Lecture 2 Chapter 4 Lecture objectives To identify and discuss the descriptive epidemiology data sources regarding Surveillance systems. To identify the Epidemiologic variables in terms of, person. Passive surveillance Passive surveillance relies on health professionals and the public to identify cases and submit reports to the surveillance system. The routine reporting of health data Notifiable diseases Diseases registries Hospitals data Passive surveillance is a valuable source of health information one of the biggest advantages of this type of surveillance is that it’s generally inexpensive MedWatch as passive example The FDA instituted the MedWatch program in 1993 as a unified system by which consumers and health care professionals can voluntarily report suspected serious adverse events and product quality problems associated with the use of FDA-regulated products. Medwatch is a passive surveillance system; It relies on voluntary reports its listing of cases is often incomplete. ‘‘false positives.’’  Illustrative Example Suprofen-associated flank pain (passive surveillance) Passive collection of Dr. & consumer reports Stimulate reporting system with Dear Doctor letters Drug was ultimately removed from the market  Approximately 30% of infants in the US are breastfed through 3 months of age The percentage drops to about 11% through the age of 6 months. Non-Hispanic black mothers tend to engage in breastfeeding < often than other racial/ethnic groups and < frequencies of breastfeeding occur among women who are younger, have < levels of education and income, and are unmarried. The reader may want to speculate as to the reasons for the results that are displayed and develop hypotheses for interventions to increase breastfeeding. USES OF DESCRIPTIVE EPIDEMIOLOGIC STUDIES 1. Permit evaluation of trends in health and diseases: Monitoring of known diseases as well as the identification of emerging problems. Comparisons among population groups, geographical areas, and time periods. Breastfeeding example, Infants who resided in metropolitan areas were breastfed more frequently than infants who resided outside of metropolitan areas Infants from families with lower income levels were breastfed less frequently than infants from families with higher income levels. These findings highlighted the relationships between the frequency of breastfeeding and both residential locations and income levels as potential emerging problems.  2. Provide a basis for planning , provision, and Evaluation of Health Services Data needed for efficient allocation of resources often come from descriptive studies. The breastfeeding example: Race, age, and marital status (unmarried) were associated with lower frequency of breastfeeding. An implication of this descriptive study is that an intervention program to increase the frequency of breastfeeding might target pregnant, unmarried, younger African American women. 3. Identifying problems to be studied by analytic methods and suggest areas that may be fruitful for investigation A reduction in breastfeeding after infants reached 3 months of age. This observation raises the question: "What caused the drop-off in breastfeeding?” You might hypothesize that when mothers return to work or other activities, breastfeeding becomes inconvenient. The next step would be to design a more complex study—an analytic study to explore the hypotheses that have been raised. Epidemiological inferences from descriptive data The process of inferences in descriptive epidemiology refers to drawing conclusions about the nature of exposures and health outcomes and formulating hypotheses to be tested in analytic research. As discussed previously, descriptive epidemiology aims to characterize health phenomena according to person, place, and time (who, where, and when). This process involves quantifying the findings (how many cases) and providing insights into what happened. After conducting a descriptive study, the epidemiologist must evaluate the findings carefully in order to rule out chance factors, biases, and confounding. The "analytic epidemiology," which is concerned with testing hypotheses in order to answer the questions "why?" and "how?" Epidemiologic variables Person variables Place variables Time variables Person variables Person variables: address characteristics and attributes of population and population subgroups. Variations in disease rates by person variables provide insights into exposures to agents and differences in host susceptibility. Two of the more common person variables are age and sex (gender). Two other common person variables are race and ethnicity. Age Age is perhaps the most important factor to consider when one is describing the occurrence of virtually any diseases or illness because age specific disease rates usually show greater variation than rates defined by almost any other personal attribute. use age specific rates to compare the disease burden among populations. As age increase, overall mortality increases as do incidence of and mortality from many chronic diseases. For example, USA in 2005, age specific death rates for malignant neoplasms (cancers) demonstrated substantial age related increases, from 2.5/100000 population at age 5 to 14 years to 1,637.7 cases per 10,000 age 85 years and older Sex Numerous epidemiological studies have shown sex differences in a wide scope of health phenomena including mortality and morbidity. Example presents data on sex differences in mortality. The population age adjusted death rate has declined in the US since 1980. Males generally have higher all cause age specific mortality rates than females from birth to age 85 and older than ratio of male to female age adjusted death rates in 2005 was 1.4 to 1 Illustrative Example Sports-related injuries per 1000 population.