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Modular Learning Objectives
By the end of this module, the student shall be able to satisfy the following outcomes expectations:
Case
Use and interpret statistical information to evaluate problems in minority health groups
Distinguish between major causes of mortality between minority and ethnic groups
SLP
Formulate and answer specific questions related to selected countries fertility, disability, morbidity, and mortality
TD
Interpret the components and general concept of demographic transition model
This module will focus on the analysis, interpretation, and application of statistical data among minority health groups and among different countries.
As we get into some formulas used in demography, here is some refresher information: A ratio expresses the relationship between two numbers x : y. A proportion is a type of ratio which is expressed as a percentage. A rate is a proportion that includes a time specification. Rates may be expressed as a percentage (i.e., per 100) or per 1,000, or per 100,000, depending on convention, the number of digits, and convenience. For example, some numbers are expressed per 100,000 to avoid fractions–it is easier to interpret 6 per 100,000 than .06 per 1,000.
Health Statistics
Heath statistics are concerned with the presence or occurrence of disease, accidents, incapacities in a population.
The type of data gathered varies with the jurisdiction. For our purposes, we will consider selected morbidity measures.
Morbidity
The incidence of a given illness or abnormal condition is called morbidity in statistics parlance. In studying diseases and tracking their incidence we need a strict case definition. For example, rubeola (measles) may be defined as (1) generalized rash of three or more days duration and (2) fever to 101°F (38.3°C) or more and (3) cough, coryza, or conjunctivitis. The preciseness of this definition should distinguish measles from similar febrile illnesses. For a study of diarrhea, a broader definition is warranted. If we only want to track diarrhea caused by rotavirus such as Shigella, Salmonella, or E. coli, then a precise definition is necessary. And then, the definition must be strictly applied to the individual: case ascertainment. Sometimes this is simple, other times it requires costly and complex laboratory studies. Accurate case definition and ascertainment, tied to appropriate statistical methods, are needed to evaluate community-based interventions such as disease control problems.
Sometimes another method is acceptable. For example, you want to determine whether malnutrition in under-fives exceeds 5% of the population at risk (because that is the level where funding kicks in). A relatively simple clinical survey with some laboratory backup, may be sufficient to make a yes or no decision. Such a procedure is called a rapid epidemiologic assessment.
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