Age-adjustment A summarizing procedure for a statistical measure in which the effects of differences in composition of the populations being compared have been minimized by statistical methods. Examples are adjustment by regression analysis and by standardization. Adjustment often is performed on rates or relative risks, commonly because of differing age distributions in populations that are being compared. The mathematical procedure commonly used to adjust rates for age differences is direct or indirect standardization. Clustering, cancer clusters (Syn: disease cluster, time cluster, time-place cluster) A closely grouped series of events or cases of a disease or other health-related phenomena with well-defined distribution patterns in relation to time or place or both. The term is normally used to describe aggregation of relatively uncommon events or diseases, e.g., leukemia, multiple sclerosis. Cancer register, registry The cancer registry is a resource to the epidemiologist, yielding information on the risks of cancer in different population groups, and on the changes that occur with time, from which etiological hypotheses can be developed. The registry provides an economical mechanism for following up industrial and other cohorts of individuals with specific exposures, and may be a useful source of subjects for case-control studies. Factors in causation of disease The following factors have been differentiated (but they are not mutually exclusive): Predisposing factors are those that prepare, sensitize, condition, or otherwise create a situation such as the level of immunity or state of susceptibility so that the host tends to react in a specific fashion to a disease agent, personal interaction, environmental stimulus, or specific incentive. Examples include age, sex, marital status, family size, educational level, previous illness experience, presence of concurrent illness, dependency, working environment, and attitudes toward the use of health services. These factors may be "necessary" but are rarely "sufficient" to cause the phenomenon under study. Enabling factors are those that facilitate the manifestation of disease, disability, ill-health, or the use of services or conversely those that facilitate recovery from illness, maintenance or enhancement of health status, or more appropriate use of health services. Examples include income, health insurance coverage, nutrition, climate, housing, personal support systems, and availability of medical care. These factors may be "necessary" but are rarely "sufficient" to cause the phenomenon under study. Precipitating factors are those associated with the definitive onset of a disease, illness, accident, behavioral response, or course of action. Usually one factor is more important or more obviously recognizable than others if several are involved and one may often be regarded as "necessary." Examples include exposure to specific disease, amount or level of an infections organism, drug, noxious agent, physical trauma, personal interaction, occupational stimulus, or new awareness or knowledge. Reinforcing factors are those tending to perpetuate or aggravate the presence of a disease, disability, impairment, attitude, pattern of behavior, or course of action. They may tend to be repetitive, recurrent, or persistent and may or may not necessarily be the same or similar to those categorized as predisposing, enabling, or precipitating. Examples include repeated exposure to the same noxious stimulus (in the absence of an appropriate immune response) such as an infectious agent, work, household, or interpersonal environment, presence of financial incentive or disincentive, personal satisfaction or deprivation. Confidence interval (CI) The computed interval with a given probability, e.g., 95%, that the true value of a variable such as a mean, proportion, or rate is contained within the interval. Confidence limits The upper and lower boundaries of the confidence interval. Epidemiology The study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to control of health problems. "Study" includes surveillance, observation, hypothesis testing, analytic research, and experiments. "Distribution" refers to analysis by time, place, and classes of persons affected. "Determinants" are all the physical, biological, social, cultural, and behavioral factors that influence death. "Health-related states and events" include diseases, causes of death, behavior such as use of tobacco, reactions to preventive regimens, and provision and use of health services. "Specified populations" are those with identifiable characteristics such as precisely defined numbers. "Application to control . . ." makes explicit the aim of epidemiology -- to promote, protect, and restore health. There have been many definitions of epidemiology. In the past 50 years or so, the definition has broadened from concern with communicable disease epidemics to take in all phenomena related to health in populations. The Oxford English Dictionary (OED) gives as a definition: "That branch of medical science which treats of epidemics" and cites Parkin (1873) as a source. However, there was a "London Epidemiological Society" in the 1850s. The identity of the scholar who first used the word at that time has been lost. Epidemiologia appears in the title of a Spanish history of epidemics, Epidemiologia espanola, Madrid, 1802. Epidemic is much older. The word appears in Johnson's Dictionary (1775), and OED gives a citation dated 1603. The word was, of course, used by Hippocrates. Histology That department of anatomy which deals with the minute structure, composition, and function of the tissues; called also microscopical anatomy. normal h., the histology of normal tissues. pathologic h., the histology of diseased tissues; histopathology. From Dorland's Illustrated Medical Dictionary. Philadelphia: W. B. Saunders Co. (c) 1994. Reprinted by permission. Histopatholog Pathologic histology. From Dorland's Illustrated Medical Dictionary. Philadelphia: W. B. Saunders Co. (c) 1994. Reprinted by permission. Incidence (Syn: incident number) The number of instances of illness commencing, or of persons falling ill, during a given period in a specified population.1 More generally, the number of new events, e.g., new cases of a disease in a defined population, within a specified period of time. The term incidence is sometimes used to denote INCIDENCE RATE. 1 Prevalence and Incidence, WHO Bull 1966; 35:783-784. Incidence rate The rate at which new events occur in a population. The numerator is the number of new events that occur in a defined period; the denominator is the population at risk of experiencing the event during this period, sometimes expressed as person-time. The incidence rate most often used in public health practice is calculated by the formula Number of new events in a specified period x 10n Number of persons exposed to risk during this period In a dynamic population, the denominator is the average size of the population, often the estimated population at the mid-period. If the period is a year, this is the annual incidence rate. This rate is an estimate of the person-time incidence rate, i.e., the rate per 10n person-years. If the rate is low, as with many chronic diseases, it is also a good estimate of the cumulative incidence rate. In follow-up studies with no censoring, the incidence rate is calculated by dividing the number of new cases in a specified period by the initial size of the cohort of persons being followed; this is equivalent to the cumulative incidence rate during the period. If the number of new cases during a specified period is divided by the sum of the person-time units at risk for all persons during the period, the result is the person-time incidence rate. Infrantentorial Inferior to the cerebellum. From Dorland's Illustrated Medical Dictionary. Philadelphia: W. B. Saunders Co. (c) 1994. Reprinted by permission. Life table A summarizing technique used to describe the pattern of mortality and survival in populations. The survival data are time specific and cumulative probabilities of survival of a group of individuals subject, throughout life, to the age-specific death rates in question. The life table method can be applied to the study not only of death, but also of any defined endpoint such as the onset of disease or the occurrence of specific complication(s) of disease. The survivors to age x are denoted by the symbol lx, the expectation of life at age x is denoted by the symbol ex, and the proportion alive at age x who die between age x and x + 1 years is denoted by the symbol nqx. The life table method is used extensively in epidemiology and in many assessments of treatment regimens in clinical practice. The first rudimentary life tables were published in 1693 by the astronomer Edmund Halley. These made use of records of the funerals in the city of Breslau. In 1815 in England, the first actuarially correct life table was published, based on both population and death data classified by age. Two types of life tables may be distinguished according to the reference year of the table: the current or period life table and the generation or cohort life table. The current life table is a summary of mortality experience over a brief period (one to three years), and the population data relate to the middle of that period (usually close to the date of a census). A current life table therefore represents the combined mortality experience by age of the population in a particular short period of time. The cohort or generation life table describes the actual survival experience of a group, or cohort, of individuals born at about the same time. Theoretically, the mortality experience of the persons in the cohort would be observed from their moment of birth through each consecutive age in successive calendar years until all of them die. The clinical life table describes the outcome experience of a group or cohort of individuals classified according to their exposure or treatment history. Life tables are also classified according to the length of age interval in which the data are presented. A complete life table contains data for every single year of age from birth to last applicable age. An abridged life table contains data by intervals of 5 or 10 years of age. See also SURVIVORSHIP STUDY.