Epidemiological Measurements of health Measures of Morbidity Frequency

Epidemiological Measurements of health Measures of Morbidity

Frequency Distributions Epidemiologic data come in many forms and sizes. One of the most common forms is a rectangular database made up of rows and columns. Each row contains information about one individual Each row is called a “record” or “observation. ” Each column contains information about one characteristic such as race or date of birth Each column is called a “variable. ” The first column of an epidemiologic database usually contains the individual’s name, or identification number which allows us to identify who is who.

Frequency Measures In epidemiology, many nominal variables have only two possible categories: alive or dead; case or control; exposed or unexposed; and so forth. Such variables are called Dichotomous variables. The frequency measures we use with dichotomous variables are ratios, proportions, and rates. All three measures are based on the same formula: Ratio, proportion, rate = X × 10 n Y

Ratios, Proportions, and Rates In a ratio, the values of x and y may be completely independent, or x may be included in y. For example, the sex of children attending an immunization clinic could be compared in either of the following ways: Female Male All In the first option, x (female) is completely independent of y (male). In the second, x (female) is included in y (all). Both examples are ratios. A proportion, the second type of frequency measure used with dichotomous variables, is a ratio in which x is included in y. Of the two ratios shown above: The first is not a proportion, because x is not a part of y. The second is a proportion, because x is part of y.

Rates The third type of frequency measure used with dichotomous variables, is often a proportion, with an added dimension: it measures the occurrence of an event in a population over time. Rate= No. of cases or events occurring during a given time period X 10 n population at risk during the same time period Notice three important aspects of this formula. • The persons in the denominator must reflect the population from which the cases in the numerator arose. • The counts in the numerator and denominator should cover the same time period. • In theory, the persons in the denominator must be “at risk” for the event, that is, it should have been possible for them to experience the event.

Risk : the likelihood to have a disease or any health event

The Rate: measures the risk = x *k y in a unit of time, where: x=number of cases y=population at risk k is a constant unit of time: could be any unit, so:

The rate = No. of cases x 100… Population at risk

• The ratio = x *k y Where x is not involved in or part of y • The proportion = x * k (No units of time) y

Measures of morbidity: Incidence rate: measures the occurrence of new cases of a disease or health event, i. e. it measures the development of diseases (usually acute diseases). Useful for estimating risk, study causation of disease, and evaluate primary prevention programs. I. R. = No. of new cases Population at risk * K ( in a period of time) Population at risk: pop. that is present, susceptible, exposed, & free of the dis. at the time of measurement.

Rates imply a change over time. For disease incidence rates, the change is from a healthy state to disease. The period of time must be specified. For surveillance purposes, the period of time most commonly used is the calendar year, but any interval may be used as long as the limits of the interval are identified. When the denominator is the size of the population at the start of the time period, the measure is called cumulative incidence. This is a proportion, all persons in the numerator are also in the denominator. It is a measure of the probability or risk of disease, i. e. , what proportion of the population will develop illness during the specified time period. In contrast, the incidence rate is like velocity or speed measured in miles per hour. It indicates how quickly people become ill measured in people per year.

• Attack rate: an I. R. used for defined populations in definite periods of time. • Secondary attack rate: I. R. among the contacts. Secondary attack rate= No. of cases among contacts * K No. of contacts

Applications of I. R. : 1 - crude rates: - Crude birth rate: No. of live births/MY population - Fertility rate: live births/ women at childbearing age - Infant mortality rate: infants death (0 -365) / No. of live births during the year *1000 - Fetal death rate: No. of fetal deaths (20 w. or more gestation) / No. of live births + No. of fetal deaths >20 w - Fetal death ratio: No. of fetal deaths (20 w. or more gestation) / No. of live births *1000 -

• Neonatal mortality rate: No. of infant deaths <28 days / No. of live births *1000 • Post neonatal mortality rate: No. of infant deaths (28 -365) / No. of live births-neonatal deaths *1000 • Prenatal mortality rate: late fetal deaths >28 w. gestation infant deaths within 7 days of birth/No. of live births + No. of late fetal deaths *1000 • Prenatal mortality ratio: No. of late fetal deaths >28 w +infant deaths 7 days of birth / No. live births • Maternal mortality rate: No. of deaths due to causes related to childbirth / No. of live birth *1000

2. specific rates: - Cause specific rate: - Proportional mortality ratio:

3. Adjusted rates Category specific rates: • Age • Sex • Race • Occupation • SES • ……….

Prevalence: measures the frequency of all current cases of a disease in a population, at a specified time. Useful for health administrative purposes by assessing the impact of health problems to deliver services as it quantifies the ”burden” of disease, and indicates the target pop. Prev. = No. of all cases (old & new)of a dis. * K Total population

*Point prevalence: measures the frequency of all current cases of a disease at a given instant in time. *Period prevalence: measures the frequency of all current cases of a disease in a specified period of time.

I. R. Prev. Death Cure

Prevalence is based on both incidence (risk) and duration of disease. High prevalence of a disease within a population may reflect high risk, or it may reflect prolonged survival without cure. Conversely, low prevalence may indicate low incidence, a rapidly fatal process, or rapid recovery. P ~ I*D We often use prevalence rather than incidence to measure the occurrence of chronic diseases such as osteoarthritis which have long duration and dates of onset which are difficult to pinpoint.

Person-time Rate A type of incidence rate that directly incorporates time into the denominator. Typically, each person is observed from a set beginning point to an established end point (onset of disease, death, migration out of the study, or end of the study). The numerator is still the # of new cases, but the denominator is a little different. The denominator is then sum of the time each person is observed, totaled for all persons. Person place time= No. of cases during observation period X 10 n Time each person observed totaled for all persons For example, a person enrolled in a study who develops the disease of interest 5 years later contributes 5 person-years to the denominator. A person who is disease-free at one year and who is then lost to follow-up contributes just that 1 person-year to the denominator. Person-time rates are often used in cohort (followup) studies of diseases with long incubation or latency periods, such as some occupational diseases, AIDS, & chronic diseases.