Morbidity

Morbidity refers to the absence of health, including physical and psychological well-being. In medical decision making, one cares about morbidity in the following three constructs: (1) the baseline incidence or prevalence of morbidity in the absence of an intervention; (2) the decrease in morbidity in the presence of an efficacious, effective, and cost-effective prevention or treatment intervention; and, in some cases, (3) the increase in morbidity because of an intervention, in terms of adverse events.

Morbidity is commonly measured by the incidence or prevalence of disease or injury. Incidence is the number of new cases of disease or injury in a population over a period of time. Incidence is a rate and describes the probability that healthy or disease-free people will develop the disease or injury over a specific time period, oftentimes a year. Thus, incidence is frequently used to measure diseases with a rapid onset, such as infectious diseases. If a city with a population of 100,000 persons has 500 new cases of influenza over a period of 3 months, then the incidence rate for this city would be 500 cases per 100,000 per 3 months. By comparing incidence rates of disease or injury among population groups varying in one or more identified factors (such as race/ethnicity or gender), health practitioners can make better informed decisions regarding the use of scarce health resources. For example, if a school finds that children living in a particular zip code are five times more likely to have dental caries than do other students, then public health officials can strategically intervene to prevent further morbidity.

Prevalence is the number of persons in a population who have a disease or injury at a given time, regardless of when the disease first occurred. Prevalence is a proportion and measures the probability of having the disease at a point in time. In decision making, prevalence is important in determining human resource needs, workload constraints, and the utilization of healthcare resources associated with particular diseases and injuries. It is also useful for expressing the burden of some attribute, disease, or condition in a population. An awareness that 25% of Hispanic adults aged 50 years or older have diabetes in a geographic area next to a particular hospital, for example, indicates how pervasive this disease is and can guide decision makers at that hospital to effectively allocate resources. Unlike incidence, prevalence is not a rate and therefore should not be used to measure diseases with rapid onsets or infectious diseases.

The relationship between prevalence and incidence is another important aspect of how these measures describe morbidity in a population: Prevalence = Incidence × Duration. Thus, treatments that prolong life and increase duration of disease, such as insulin for diabetics, have a profound effect on disease prevalence. Furthermore, an increased incidence of diabetes contributes to a rapidly increasing prevalence of diabetes in the United States.

In medical decision making, prevalence can also be used to describe the baseline population in the absence of an intervention and to serve as an outcome variable. Treatment and prevention strategies can affect the prevalence of disease by reducing the length of time an individual might suffer from disease or by affecting the development of new cases or both. The use of Pap smears to identify preinvasive and invasive cervical cancer is an example of an intervention that can reduce cervical cancer prevalence by reducing the length of time a woman would suffer from cervical cancer as well as by preventing the development of new cases.

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