Identify factors that could increase the likelihood

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Measures Used in Epidemiology

One important application of epidemiology is to identify factors that could increase the likelihood of a certain health problem occurring within a specific population. Epidemiologists use measures of effect to examine the association or linkage in the relationship between risk factors and emergence of disease or ill health. For instance, they may use measures of effect to better understand the relationships between poverty and lead poisoning in children, smoking and heart disease, or low birth weight and future motor skills. The following are some common measures used in epidemiology:
Odds ratio: The odds ratio quantifies the association between an independent variable (exposure) and a dependent variable (outcome). It is calculated as the odds that an effect will occur given the presence or exposure to a studied variable, compared to the odds when there is no exposure (e.g., lung cancer and smoking)
Risk ratio (also called relative risk): Also quantifies the association between an independent variable and a dependent variable. The risk of an effect occurring in one population versus another population (e.g., preeclampsia in women <35 versus >35). Risks greater than one suggest that exposure to a given variable is associated with an increase in the risk of the outcome, and a risk ratio of less than one indicates that the exposure is associated with a decrease in the risk of the outcome. Hire best assignment help now!
Mortality: Measure of deaths in a particular population during a specified time interval. If this is attributed to a specific cause, it is referred to as cause-specific mortality.
Morbidity: Measure of instances of illness or disability in a population from a given cause (e.g., heart disease) during a specified time interval
Incidence: The occurrence of new cases of an effect or disease in a population over a defined time period relative to the size of the population at risk (e.g., new cases of COVID-19 in a population over a 7-day period/1000 people)
Prevalence: The number of all cases of an effect or disease, not just new ones, in a population at a given time relative to the size of the population (e.g., number of people with autism/1000)

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