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association, direct 8 "effects." Bradford Hill' and othen'~' have pointed out that the (subjective) likeli- hood of a causal relationship is increased by the presence of the following attri- butes. However, temporality is the only indispensable condition among these. I. Consistency-The association is consistent if the results are replicated when studied in different settings and by different methods. 2. Strength-This is an expression of the disparity between the frequency with which a factor is found in the disease and the frequency with which it occurs in the absence of the disease. Not to be confused with statistical significance. 3. Specificity-This is established with the limitation of the association to a single putative cause and single effect. 4._ Dose-response relationship-This is established when an increased risk or se- verit%in disease occurs with an increased quantity ("dose'') or duration of ex- posure to a factor. 5. Temporality-The exposure to a putative cause always pre_cedes, never fol- lows, the outcome. 6. Biological plausibility-It is desirable that the association agree with current understanding of the response of cells, tissues, organs, and systems to stimuli. This criterion should not be applied rigidly. The association may be new to science or medicine. As Sherlock Holmes advised Dr. Watson, "When you have eliminated the impossible, whatever remains, however improbable, must be the truth." 7. Coherence-The associations should not conflict with the generally known fact_s_ of the natural history and biology of disease. 8. Experiment-It is sometimes possible to appeal to experimental, or quasi- experimental evidence, e.g., an observed association leads to_ some preventive action. Does this action in fact prevent? See also C_ AUSALITY: EVANS'S POSTULATES; KOCH'S POSTULATFS. ' Bndford Hill A: The environment and disease: As+mtiation or ousation. Proc Ror Sa Med 5H:295- J00. 1965. r5usxr MN': Judgment and causal inference. Aw J EPidrwiol 105:1-15, 1977. sRothman t:J (Edl: Conal InJn.ur. Chestnut Hill, MA: Epidemiology Resources Inc., 1988. ASSOCtAT1oN,. DutECT Directly associated, i.e., not via a known third variable: A-+B. Re- fers onl% to causality. AsSOCrATtON, rNDIRECT CAUSAL Two types are distinguished: 1. Association n of a factor C with disease A only because both are related to a common underlying factor 8. AV BN C Alteration of factor C will not produce an alteration in the frequency to dis- ease A unless an alteration in C affects B. It has been suggested that to avoid confusion with the alternative meaning of indirect nuonotion, this type should be called "secondary association." 2. Association of a factor C with disease A by means of an intermediate or inter- vening factor B. 8 Cf ~A Alteration of factor C would produce an alteration in the frequency of dis- ease A. To avoid confusion, this type should be called "indirect causal asso- ciation." s 9 attsibutable fraction AssoctATroN, sruRtovs A term, preferably avoided, used with different meanings by different authors. )t may refer to artifactual, fonuitous, false secondary, or to all kinds of noncausal associations due to chance, bias, failure to control for extraneous variables, etc. ASSOCIATION, lYMMETRlCAL An association is noncausal if it is symmetrical, as in the statement F=MA (force equals mass times acceleration). This is a noncausal, non- directional expression of the mathematical relationship between the physical prop- erties of force, mass, and velocity. If one side of the equation is changcd, then thr other must also change to maintain equilibrium. Although epidemiologists are usually most interested_ in asymmetrical statements that have direction, the symmetrical equation can be useful. For instance, preva- lence can be expressed in terms of incidence and duration in the simple equation, P=I xD. If two of these three elemenu_ are known, the third can be derived. See also SYMMETRICAL RELATIONSN/P. ASSORTAnVE MATING Selection of a mate with preference (or aversion) for a particular genotype, i.e., nonrandom mating. ASYMMETRICAL ASSOCIATION See ASSOCrAT1ON, ASYMMETRtCAL. AsYMrrostC f ertaining to a limiting value, for example, of a dependent variable, when the independent variable approaches zero or infinity. See LARGE sAMPL_E_ METNOO. A6YMPTOTIC METHOD See LARGE SAMPLE METHOD. ATTACK RATE Attack rate, or case rate, is a CUMULATIVE INCIDENCE RATE Often used for particular groups, observed for limited periods and under special circumstances, as in an epidemic. The sccondary attack ratF is the number of cases among contacts occurring within the accepted incubation period following exposure to a primary case. in relation to the total of exposed contacts; the denominator may be restricted to susceptible con- tacts when determinable. Infection ratr is the incidence of manifest plus inapparent infections, which can be identified, e.g., by SEROEPIDEMIOLOGY. ATTR1sUTA.LE iRACTtoN (AF) (Syn: attributable proportion) A term sometimes_ usCd to refer to the attributable fraction in the population, and sometimes to the attrib_ut- able fraction among (he exposed. See also ATTRtRt1TAR_ L_E FRACTION (ExPOSEn); AT- TRISUTAaLE FRACTION (POPULATION). ATTRaRUTARLE F7lACT1ON (Exro_SED) (Syn: attributable proportion (exposed), attribut- able risk, etiologic fraction (exposed)). With a given outcome, exposure factor and population, the attributable fraction among the exposed is the proportion by which the incidence rate of the outcome among those exposed would be reduced if the exposure were eliminated. It may be estimated by the formula AF =1,=1 1Y c- . where l, is the incidence rate among the exposed, l, is the incidence rate among the unexposed; or by the formula AF, - RR- I where RR is the rate ratio. 1 fl,. It is assumed that causes other than the one under investigation have had equal effects on the exposed and unexposed groups. ArrRlarl!ARLE IntwcTaON (rorvunoN) (Syn: attributable proportion (population), eti- ologic fraction (population), attributable risk). With a given outcome, exposure fac- tor, and population, the attributable fraction among the population is the propor- vM(v(~TS(.ZV%

attrsbulable number 10 tion by which the incidence rate of the outcome in the entire population would be reduced if exposure were eliminated. It may be estimated by the formula APP=IP-1 I P where lP is the incidence rate in the total population and /v is the incidence rate among the unexposed; or by the formula P,(RR - 1) I + P,(RR - 1) where RR is the rate ratio. /„/lP. It is assumed that causes other than the one under investigation have had equal effects on the exposed and unexposed groups. AYrRlMtri-ASLE NIMtER The number of new occurrences of a specific outcome attrib- utable to an exposure; it may be estimated using the formula AN=s~ where l, is the incidence rate among the exposed, I„ is the incidence rate among the unexpostd, and N, is the number of persons in the exposed population. It is assumed that causes other than the one under investigation have had equal effects on the exposed and unexposed groups. ATTRIRUTAaLE RIsK The rate of a disease or other outcome in exposed individuals that can be attributed to the exposure. This measure is derived by subtracting the rale of the outcome (usually incidence or mortality) among the_ unexposed from the rate among the exposed individuals; it is assumed that causes other than the one under investigation have had equal effects on the exposed and unexposed groups. Unfor- tunatel), this term has been used to denote a number of different concepts, includ- ing the attributable fraction in the population, the attributable fraction among the exposed, the population excess rate, and the rate difference. Therefore, it should be defined carefully by all who use it. See also ATTRIeUTAeLE FRACTION (ExPOSED); POPULA-T-IONEXCESS RATE; ATTRIBUTABLE FRACTION (POPULATION); POPULATION AT- TRIStIrARtt RISK: RATE DtFEERENCE. A7T1<latITACLE RISK (EXPOSED) This term has been used with different connotations to denote the attributable fraction among the exposed and the excess risk among the exposed. See aISO ATTRIRUTApIE FRACTION (EXPOSED); RATE DIFFERENCE. ArrRr.uTA.LE RISK (troevLATSoN) This term has been used with different connotations to denote the attributable fraction in the population and the population excess risk. See 2150 ATTRIRUTARLE FRACTION (POPUlAT10N); POPULATION EXCESS RATE. A-TTRlatITAaLE RISK PERCENT Attributable fraction expressed as a percentage rather than as a proportion. ATTRIBUTABLE RtSK PERCENT (EXPOSED) This is the attributable fraction among the_ e_x- posed, expressed as a percentage. See also ATTRIRUTAeLE FRACTION (ExPOSED). ATTRIBUTABLE RISK PERCENT (ro.vLAT1oN) This is the attributable fraction in the pop- ulation, expressed as a percenl]g0 See also ATTRIBUTABLE FRACTION (POPULATION). ATTSttmtrrt A qualitative characteristic of an individual or item. AUDIT An examination or review that establishes the extent to which a condition, pro- cess, or performance conforms to predetermined standards or criteria. AUTOPSY DATA Data derived from autopsied deaths, e.g., for study of natural history of disease and trends in frequency of disease. Autopsies are done on nonrandomly selected pcrsons in the population and findings should therefore be generalized only with great caution. K i AVERAGE Kendall and Buckland_'s Diclionary of Skuistical Trrm (4(h Edition, 1982) has this to say: "A familiar but elusive concept. Generally an 'average' value purports to represent or to summarize the relevant features of a set of values; and in this sense the term would include the median and the mode. In a more limited sense an 'average' compounds all the values of the set, e.g., in the case of the arithmetic or geometric means. In ordinary usage, 'the average' is often understood to refer to the arithmetic mean." See alSo MEASURE-S OF CENTRAL TEND_ ENCY. AVERAGE LIFE EXPECTANCY See EXPECTATION OF UFE. AXIS 1. One of the dimensions of a graph. A two,dimensional graph has two axes, the horizontal or x axis, and the vertical or y axis. Mathematically, there may be more than two axes, and graphs are sometimes drawn with a third dimension; the eye cannot comprehend more than three dimensions. 2. In NOSOt.OGV, an axis of classification is the conceptual framework, e.g., etio- logic, topographic, psychologic, sociologic. The International Classification of Disease, for example, is multiaxial; the primary axis is topographic (i.e., body syslems)t secondary axes relate to etiology, manifestations of disease, detail et_ail of sites affected, severity, etc. sIA.MTsMYaz

13 bias ACKCROl1ND LEVEI.. RATE The concentration. often low, at which some subsunce, agent. or event is present or occurs at a particular time and place in the absence of a specific hazard or set of hazards under investigation. An example is the background level of naturally occurring forms of ionizing radiation to which we are all exposed. sAR DtweR" A graphic technique for presenting DISCRErE DATA organized in such a way that each observation can fall into one and only one category of the variable. Frequencies are listed along one axis and categories of the variable along the other axis. The frequencies of each group of obsen•atio_ ns are represented by the lengths of the corresponding bars. See atso HtSTOCRAM. 25 2s.s 23.2 9.e 0 e.? 6.8 6A j IM rA_ffl aondrtqnt Hfdrl ArJhrfln Vntr01 MrOertentlon Dia6tlet Impuirmenlt, - and impovm.nla w,tharl htarl larer et,remiliet rhRwnotitm inrolvemen/ Ond hips Bar diagram. Pronr Susser. Watson. Hopper. 1985. •AYES' THEOREM A theorem in probability theory named for Thomas Bayes (1702- 1761). an English clergyman and mathematician; his Essar Tonards So/ving a Pro6lrrn in lhE Doc(nnr of Chancri (1763, published posthumously), contained this theorem. In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease (the prior probability of disease) and of the likelihoeids of that characteristic in healthy and diseased individuals. The most familiar application is in CLINICAL DECISION ANALYSIS where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result. A simplified version oT the theorem is tk y P(DIS)!. P(SID)P(D) P(SID)P(D) +P(SiD)P(D) where D=disease, S- symptom. and Dsno disease. The formula emphasizes what clinical intuition often overlooks, namely, that the probability of disease given this symptom depends not only on how characteristic that symptom is of the disease but also on how frequent the disease is among the population being served. "If you hear hoof beats in the street, do not look for zebra." The theorem can also be used for estimating exposure-specific rates from case control studies if there is added information about the overall rate of disease in that population. Some of the terms in the theorem have special names. The probability of disease given the symptom is called the "posterior probability." It is an estimate of the probability of disease posterior to knowing whether or not the symptom was pres- ent. The overall probability of disease among the population or our guess of the probability of disease before knowing of the presence or absence of the symptom is called the "prior probability." The theorem is sometimes presented in terms of the odds of disease before knowing the symptom (prior odds) and after knowing the symptom (posterior odds). REHAVIORAL ERIDEJNIC An epidemic originating in behavioral patterns (as opposed to invading microorganisms or physical agents). Examples include the dancing manias of the Middle Ages, episodes of mass fainting or convulsions ("hysterical epidem- ics"), crowd panic, or waves of fashion or enthusiasm. The communicable nature of the behavior is dependent not only on person-to-person transmission of the behav- ioral pattern but also on group reinforcement (as with smoking, alcohol, or drug use). Behavioral epidemics may be difTicult to differentiate from, or may compli- cate, outbreaks of organic disease, for example. due to contamination of the envi- runment by a toxic substance. EHAVIORAL RISK rACTOR A characteristic or behavior that is associated with increased probability of a specified outcome; the term does not imply a causal relationship. E_NCHMARK A slang or jargon term, usually meaning a measurement taken at the out- set of a series of measurements of thc same variable, sometimes meaning the best or most desirable salue of the variable. Because of uncertainty about meaning, the term should not be used. MENEIaT-COST RATIO The ratio of net present value of measurable benefits to costs. Calculation of a benefit-cost ratio is used to determine the economic feasibility or success of a program. BERNOULLI DISTR1SUi70N The probability distribution associated with ewo mutually ex- clusive and exhaustive outcomes, e.g., death or survival; a Bernoulli variable is one that has only two possible values, e.g., death or survival. 5ec also etNOMiAL DIsT-RI- RIrTIUN. •ERKSONrS BIAS See BIAS, SELECTION. ETA ERROR See ERROR. TYPE 11. euS Deviation of results or inferences from the truth, or processes leading to such deviation. Any trend in the collection, analysis, interpretation, publication, or re- view of data that can lead to conclusions that are systematically different from the truth. Among the ways in which deviation from thF truth can occur, are the fo)low- ing: 1. Systematic (one-sided) variation of ine2sttrements from the true values (syn: systematic error). Ji'.PtE,YsV7,o7. 12

bina, ..certaiatoent 14 2. Variation of statistical summary measures (means, rates, measures of assoc-ia- tion, etc.) from their true values as a result of systematic variation of measure- ments, other flaws in data collection, or flaws in study design or analysis. S. Deviation of inferences from the truth as a result of flaws_ in study design, data collection, or the analysis or interpretation of results. 4. A tendency of procedures (in study design, data collection, analysis, in(erpre- tation. review or publication) to yield results or conclusions that depart from the truth. 5. Prejudice leading to the conscious or unconscious selection of study proce- dures that depart from the truth in a particular direction, or to one-sidedness in the interpretation of results. The term 'bias" does not necessarily carry an impuution of prejudice or other e subjective factor, such as the experimenter's desire for a particular outcome. This differs from conventional usage in which bias refers to a partisan point of view. Man), varieties of bias have been described.l 'Sackeu DL: Bias in analyuc research. f CAro" Dis 32:51-63. 1979. IAS, AsctRTAtNMr.N'r Systematic error, arising from the kind of individuals or patients (e.g., slightl} ill, moderately ill, acutely ifl) that the individual observer is seeing. Also systematic error arising from the diagnostic process (which may be determined by the culture, customs, or r individual idiosyncrasy of the_ person providing care for the patient). •tAS, IN AsstntrnoN (Syn: conceptual bias) Error arising Irom laulty logic or premises or mistaken beliefs on the pan of the investigator. False conclusions about the ex- planation for associations between variables. Example: Having correctly deduced the mode of transmission of cholera, John Snow concluded thal yelloN~ fever was transmitted by similar means. In fact, the "miasma" theory would better fit the facts of yellow fever transmission. BIAS tN AUi'OPav tERSts Systematic error resulting from the fact that autopsies repre- sent a nonrandom sample of all deaths. BIAS, RER1tSUN'f See BIAS. S€ILEC_TION. BIAS DUE TO CONFOUNDING See CONFOUNDING. •1.1s, DESIGN The difference between a true value and that actually obuined. occurring as a result of faulty design of a study. Some examples are (I) uncontrolled studies where the effects of two processes cannot be separated (confounding), (2) con- trolled studies where observations are based on a poorly defined population, and (3) nonsimultaneous comparisons, e.g., use of historical controls. BIAS, DETECr/ON Due to systematic error(s) in methods of ascertainment, diagnosis, or verification of cases in an epidemiologic survey, study, or investigation. Example: Verification of diagnosis by laboratory tests in hospital cases, but failure to apply the same tests to cases outside the hospital. BIAS DUE TO DIGIT PREFERENCE See DIGtT PREFERENCE. BIAS IN HANDL.INC OUTLIERS Error arising from a failure to discard an unusual value occurring in a small sample, or due to exclusion of unusual values that should_ be included. BtAS, INFORMA77ON (Syn: observational bias) A flaw in measuring exposure or outcome that results in differential quality (accuracy) of information between compared groups. IIAt DUE TO INSTIUMENTAL CRROR Systematicerror due to faulty calibration, inaccur- ate measuring instruments, contaminated reagents, incorrect dilution tion or mixing of reagenu, etc. Itw3 OF INYERPRETATtoN Error arising from inference and speculation. Sources of the C I 15 bias, .election error include (I) failure of the investigator to consider every interpretation consis- tent with the facts and to assess the credentials of each- and (2) mishandling of cases that constitute exceptions to some general conclusion. BIAS, INTERVItwtR Systematic error due to_ interviewers' subconscious bconscious or even con-_ scious gathering of selective data. BIAS, °ttAD-TIME" A systemauc error arising when follow-up of two groups does not begin at strictly comparable times. Occurs especially when one group has been di- agnosed earlier in the natural history of the disease than the other group. See also LERO TIME SI11rT. nAS, LtNCTH A systematic error due to the selection of a disproportionate number of long-duration cases (cases who survive longest) in one group and not in the other. Can occur when prevalent cases, rather than incident cases, are included in a case control study. RIAR, MEASUREMENT Systematic error arising from inaccurate measure_ment (or caassifi- cation) of subiects on the study variables. RIAS, OtSERVER Svstematic difference between a true value and that actually observed due to observer variation. Observer variation may be due to differences among observers (interobserver variation) or to variation in readings by the same observer on separate occasions (intraobserver variation). See also OBSERVER VARIATION. BIAS IN T1/E PRESENTATION OF DATA Error due to irregularities produced by DIGIT PREF ERENCE, incomplete data, poor techniques of ineasurement, or technically lly poor lab- oratory standards. IAS IN PtnucAT10N An editorial predilection lor publishing particular hndings, e.g., positive results, which leads to the failure of authors to submit negative findings lor publication or failure of journal editors to accept and publish reports with negative findings. This can distort the general belief about what has been demonstrated in a particular situation. BIAS OF AN ESTIMATOR The difference between the expected value of an estimator of a parameter and the true value of this parameter. See also UNBIASSED ESTIMATOR. RtA_s, RceAU. Syste_matic error due to differences in accuracy or completeness of recall to memory of prior events or experiences. Example: Mothers whose children have had or have died of leukemia are more likely than mothers of healthy living chil- dren to remember details of diagnostic x-ray examinations to which thes_e_ children were exposed in utero. IA_s, REPORTalvG Selective suppression or revealing of information such as past history ry of sexually transmitted disease. nAS, RtsroNSt Systematic error due to difference in characteristics between those who choose or volunteer to participate in a study and those who do not. t11A8, LAMPLUVG Unless the sampling method ensures that all members of the "universe" or reference population have a known chance of selection in the sample, bias is possible. The best way to ensure a known chance of selection for all is to use a probability sampling method such as a ubk of random numbers. BIAS, SELECTION Error due 10 systematic differences in characteristics between those who are selected for study and those who are not. Examples include hospital cases or cases under a physician's care, excluding those who die before admission to hos- pital because the course of their disease is so acute, those not sick enough to require hospital care, or those excluded by distance, cost, or other factors. Selection bias also invalidates generalizable conclusions from surveys that would include only vol- unteers from a healthy population. A special example is BERKSON'S BIAS,I which Berkson charac-terizrd as the set of 4=461141sEZ0z

bias due to withdrawals 16 selective factors that lead hospital cases and controls in a case control study to be systematically different from one another. This occurs when the combination of exposure and disease under study increases the risk of hospital admission, thus leading to a svstematically higher exposure rate among the hospital cases than the hospital/ cnntrols. This in turn results in systematic distortion of the oDDS RATIO. ~ Berkson J: Limitations of the application of fourfold table analysis to hospital data. Bionwtnu Bull 2:47-59, 1946. SIAS DUE TO MT-t71DRAWALf A difference between the true value and that actually ob- served in a study due to the characteristics of those subjects who choose to with- draw. BIt.La or MORTALtT'Y Weekly and annual abstracts of chrisienings and burials, distin- guishing deaths from the plague, compiled for London (and some other cities), especially in times of plague, from the English parish registers that started in 1538. From 1629, the annual bill was published regularly and included a breakdown of deaths bv cause. These records were the basis for the earliest vital statistics, com- piled, analv:ed, and discussed by John Graunt in Natural and Political Obsrn atiom on thi Bills of Mortality (1662). t11MODAL DISTIlIaAT10N A distribution with two_ regions of high frequency separated by a region of low frequency of observations. A two-peak distribution. BINARY VARIA/LE A variable having on(y two possible values, e.g. on or off, 0 or I. See_ also sIT. •INOMIAL DISTRI/VTION A probability distribution associated with two mutua)Iv exclu- sive outcomes. e.g., presence or absence of a clinical or laboratory sign, death, or survival. The probability distribution of the number of occurrences of a binan event in a sample of n independent observations. The binomial distribution is used to model CUMUIUTIVE INCIDENCE RATFS and PREVALENCE RATES. The BERNOUt1.1 D15- TRIItuT-loN is a special case of the binomial distribution with n= I. IOASSAY The quantitative evaluation of the potency of a substance by assessing its ef- fects on tissues, cells, live experimental animals, or humans. Bioassay may be a direct method of estimating relative potency: groups of sub- jects are assigned to each of two (or more) preparations; the dose that is just suffi- cient to produce a specified response is measured, and the estimate is the ratio of the mean doses for the two (or more) groups. In this method, the death of the subject may be used as the "response.'' The indirect method (more commonly used) requires study of the relationship between the magnitude of a dose and the magnitude of a quantitative response produced by it. not.oc/CAtL ruuststl.ITV The criterion that an observed, presumably or putatively causal AssocursoN fits previously existing biological or medical knowledge. This judgment should be used cautiously since it could impede development of new knowledge that does not fit existing ideas. IOLOGICAL TtANSMISSION See VE(,TOR-RORNE INFECTION. /IOMETRY [literally, the mraeurrrnenl of (I(rJ The application of statistical methods to the study of numerical data based on biological observations and phenomena. The term was coined by W. F. R. Weldon (1860-_ 1906), a zoologist at University College, London. FRANCIS GALTON has been called "the father of-biometry" for his applica- tion of statistical methods to the analysis of biological variation. However, others preceded him, e.g., QuE-rELET and tnuls. IOSSATtsncs Application of aTAnsTICS to biological problems. The term is considered 17 blind(ed) study by many biomedical scientists to mean the application of statistics specifically to medical problems, but its real meaning is broader. BIRAUD, YvES (1900-1965) French physician and statistician. He served the League of Nations and later WHO as Director of Epidemiological and Statistical Services from 1925 to 1960. In 1960, he founded the first chair of Health Statistics in France, at the Ecoll dr sant; publiqur in Rennes. slRTtt cERTtFtCATE Official, legal document recording details of a live birth, usually comprising name, date, place, identity of parents, and sometimes additional infor- mation such as birth weight. It provides the basis for vital statistics of birth and birthrates in a political or administrative jurisdiction, and for the denominator For infant mortality and certain other vital raies. SIRTH COHORT See COHORT. a1RTH GOHORT ANALYSIS Ste COHORT ANALYSIS. BIRTH INTERVAL Interval between termination of one completed pregnancy and the_ termination of Ihe next. a1RTrt ORDER l"he ranking of siblings according ing to age, starting with the eldest in a family. The ordinal number of a given live birth in relation to all previous live births of the same women. Thus, 4 is the birth order of the fourth live birth occur- ring to the same woman. This strict demographic definition may be loosened to include all births, i.e., still-births as well as live births sIRTH RATE A summary rate based on the number of live births in a population over a given peritN.1, usually one year. Number of live births to residents in an area in a calendar year Binh rate = x 1000 Average or midyear population in the area in that year utTtt wEIC/rT Infant's weight recorded at the time of birth and, in some countries, entered on the birth certificate. Certain variants of binh weight are precisely de- fined. Low birth weight (LBW) is below 2500 g. Very low birth weight (VLBW) is below 1500 g. Ultralow birth weight (ULBW) is below 1000 g. Large for gestational age (LGA) is birth weight above the 90th percentile. Average weight for gestational age (AGA) (Syn: appropriate or adequate): birth weight between 10th and 90th percentiles. Small for gestational age (SGA) (Syn: small for dates): birth weight below 10th percentile. srT Acronym for binary digit; the signal in computing. See also RYTE. "sucR sox" A jargon lerm, meaning a method of reasoning or studying a problem, in which the methods, procedures, etc., as such are not described. explained, or perhaps even understood. Nothing is stated or inferred about the method: discus- sion and conclusions re)ate solely to the empirical relationships observed. An alter- native definition is the following: A method of formally relating an input, e.g., quantity of a drug absorbed over a period or a putative causal factor, to an output, e.g., the amount of the drug eliminated in a given period, or an observed effect, without making detailed assumptions about the mechanisms that have contributed to the transformation of input to output within the organism (the "black box"). BtJND(ED) STUDY (Syn: masked study) A study in which observer(s) and/or subjects are kept ignorant of the group to which the subjects are assigned, as in an experiment, s4 eG YSE~Of,

blocked randomiratioo 18 or of the population from which the subjects come, as in a nonexperimenul study. When both observer and subjects are kept ignorant, we refer to a doub)e-blind study. If the statistical analysis is also done in ignorance of the group to which subjects belong, the study is sometimes described as trip)e-blind. The intent of keeping subjects and/or investigators blinded, i.e., unaware of knowledge that might intro- duce a bias, is to eliminate the effects of such biases. To avoid confusion about the meaning of the word "blind" some authors prefer to describe such studies as ..masked" I/LOCKED RANDOMILATION See STRATIFIED RANDOMIZATION. The analogue in a r-andom- ized experiment of individual matching in an observational study. DODY MASS INDEX (Syn: Quetele_t's index) One of the anthropometric measures of body mass. Defined as (weight) +(height)°. This measure has the highest correlation with skinfold thickness or body density and in this respect is superior to the roN- DERAL INDEX. twoTaTnwr A technique for estimating the variance and the bias of an estimator by repeatedly drawing random samples with replacement from the observations at hand. One applies the estimator to each sample drawn, thus obtaining a set of estimates. The observed variance of this set is the bootstrap estimate of variance. The differ- ence between the average of the set of estimates and the original estimate is the bootstrap estimate of bias. BRCwrerotNT In helminth epidemiology, the critical mean worm)oad in a community, below which the helminth mating frequency is too low to maintain reproduction. A value exceeding the breakpoint of a wormload means that the wormload will in- crease until equilibrium is reached: a value less than or equal to the breakpoint means that the wormload will decrease progressively. sY-rE A group of adjacent bits, commonly 9, 6, or 8, operating as a unit for storage and manipulation of data in a computer. See also BIT. 6!,E2:Tqc ~©7 I c CALIPER MATCBINC S[e MATCHING. CANADIAN MORTAt.r1T DATA f1AlE A large set of computer-stored death statistics; per- sonal identifiers and causes of all deaths in Canada since 1950 have been compwer- stored, and the death certificates have been preserved on microfiche. This data base and record linkage have been used in some important historic_al cohort studies. See also NATIONAL DEATH INDEX. CANCER REGISTRY See REGISTER. CARRIER I. A person or animal that harbors a specific infectious agent in the absence of discernible clinical disease and serves as a potential sourcE of infection. The carrier state mav occur in an individual with an infection that is inapparent throughout its course (known as healthy or asymptomatic carrier), or during the incubation period, convalescence. and postconvalescence of an individual with a clinicalh• recognizable disease (known as incubator-%• carrier or convalcs- cent carrier). The carrier state mav be of short or long duration (temporar) or transient carrier or chronic c_arrier).' ' Adapied from Conrrol of Coin'nunicable Dutav rn Man, 14th ed. N'ashinRtnn. DC: American Public Healdh Association. 1985. CARRYING CArACITY An estimate of f the numbers of people that a nation, region, or the planet can sustain. CASE In epidemiology, a person in the population or study group identified as having the particular disease, health disorder, or condition under investigation. A variety of criteria may be used to identify cases, e.g., individual physicians' diagnoses, re- gistries and notifications, abstracts of clinical records, surveys of the general popu- lation, population screening, and reporting of defects such as in a dental record. The epidemiologic definition of a case is not necessarily the same as the ordinary clinical definition. CASE-RASE STUDY A study that starts with the identification and sampling of persons with the disease of interest, and then samples the entire base population (of cases and noncases) from which the original cases arose. This design is similar to a CASE CONTROL sruDV in most respects, but cases may appear in the comparison (base) sample as well as in the case sample. C_ASE. COt.L1TERAL A case occurring in the immediate vicinity of a case which has been the subject of an epidemiological investigation; a term used mainly in malaria con- trol programs, equivalent to the term contact as used in infectious disease epide- miology. CASE COMrARISON STUDY See CASE CONTROL STUDY. CASE COMPEER STUDY See CASE CONTROL STUDY. 19

case control .tu..y 20 CASE CONTROL 6TUDY (Svn: case comparison study, case compeer study, case history slud), case referent studi, retrospective study) A study that starts with the idencifi- cation of persons with the disease (or other outcome variable) of interest, ano a suitable control (comparison, reference) group of persons without the disease. The relationship of an attribute to the disease is examined by comparing the diseased and nondiseased with regard to how frequentlyy the attribute is present or, if quan- titative, the levels of the attribute, in each of the groups. Such a study can be called "retrospective" because it starts after the onset of disease and looks back to the postulated causal factors. Cases and controls in a case control study may be accumulated "prospectively;" that is, as each new case is di, agnosed it is entered in the study. Nevertheless, such a study may still be called '•retrospective" because it looks back from the outcome tu its causes. The terms 'tases" and "controls" are sometintes used to describe subjects in a RANDOMIZEu cONTROLLED TRtAL_ but, the term "case control stud)" should not be used to describe such a study. The terms "case control study" and "retrospective study" have been used most often to describe this method. Other terms also used are listed above. The concept of the case-control studc is lo be found in the works of I'.C.A. Louis;' the firsl explicit description of the method is contained in a paper by William Augustus Guy, who reported his analvsis of the relationship between prior occupational exposure and the occurrence of pulmonary consumption to the Statistical Society of London in 1843.2 The evolution of the case-control study thereafter has been described br Lilienfeld and Lilienfeld.' The first modern use of the method was a case-control study of breast cancer, reported by hne-Claypon' in 1926: Irom that time onward. casetontrol studies became increasingly popular and widely used. 'Louis I'CA: Researches on PMhisise Anatomical. 1'adhuloRiol and Therapeutical. (Trans. N•.H. N`olshel. London: Svdcnlum Societr. 1844. 'Gui, WA: Contributions to a knowiedRc of the influence ol emplm•mcros on hcaldh.J Rm SWt Sw 6: I St7-21 I. 11443. 'Lilicnfeld AM. Lilienkld D: A cemury of ose-comnd studies-proRrrss. J CArnn !1u 52:5-13. 1979. ' Lane-Clacpon ) E: A further report on cancer of the breast. Rrp Pub llltA Alyd Subj 32. London: HAtSO. 1926. CASE iATALfII' RATL The proportion of cases of a specified condition which are fatal within a specified time. Number of deaths from a disease Case fatality rate (usually (in a given period) x I(10 expressed as a percentage) ~ Number of diagnosed ;es oT that diseas_e (in the same period) This definition can lead to paradox when more persons die of the disease than develop it during a given period. For instance, chemical poisoning that is slowly but inexorably fatal may cause many persons to develop the disease over a relatively short period of time, but the deaths may not occur until sonte years later and may be spread over a period of years during Mhich Ihere are no new cases. Thus, in calculating the case faulity rate, it is necessary to acknowledge that the time dimen- sion varies: it may be brief, e.g., covering only the period of stay in a hospital, of futite duration, e.g., one year, or of longer duration still. The term "case fatality rate" is then better replaced by a term such as "survival rate" or by the use of a SURVIVOR3HIP TARLE. See a130 ATTACK RATE. 21 causation of disea.e CASE HISTORY BTi/DY 1. Synonym for CASE CONTROL STUDY. 2. In clinical medicine, a case report, or a report on a series of nses. CASE REFERENT STUDY See CASE CONTROL STUDY. CATASTROPHE THEORY A branch of mathematics dealing with large changes in the total system that may result front small changes in a critical variable in the system. An example is the sudden change in the physical state of water into steam or ice with rise or fall of temperature beyond a critical level. Certain epidemics, gene frequen- cies. and behavioral phenomena in populations may abide by the same mathernati- cal rule. Herd immunity is an example. CATCHMENT AREA Regitln, which may be well- or ill-defined, from which the clients of a particular health facility are drawn. CAUSALITY The relating of causes to the effects they produce. Most of epidemiology concerns causality and several types of causes can be distinguished. It should be clearlv stated, hoivever, that epidemiologic evidence by itself is insufficient to estab- lish causality. A cause is termed "necessar)" when it must always precede an effect. This effect need not he the sole result of the one cause. A cause is termed "sufficient" when it inevitably initiates or produces an effect. Am given rau_ se may be necessary, suffi- cient, neither, or both. These possibilities are explained below•. Four conditions under which independent variable X may cause Y variable X may cause Y Xis Xis necessary suflicient 1. + + 2. + 3. - + 4. - - I. X is necessary and sufficient to cause 1'. Both X and Y are always present together, and nothing but X is needed to cause )'; X-+1'. 2. X is necessary but not sufTicient to cause Y. X must be present when l' is pres- ent, but F is not always present when X is. Some additional factor(s) must alsu be present: X and Zz+Y. 3. X is not necessary but is sufficient to cause l'. 1' is present when X is• but X may or may not be present when )' is present, because Y has other causes and can occur without X. For example, an enlarged spleen can have many separate causes that are unconnected with each other; X-+Y; Z-)'. 4. X is neither necessary nor sufTicient to cause )'. Again, X may or may not be present when )• is present. Under these conditions, however, if X is present with Y, some additional factor must also be present. Here X is a contributory cause of )' in some causal sequences; X and Z-+)': W and Z-.Y. These relatiorr ships and the logic of causal inference are discussed in Cau+e! Infrrrncr.' 'Rmhman KJ (Ed) Cawof ln/rr.'vr. Chestnut Hill, MA: Epidemiolog}• Resources Inc.. 1988. C_AUSAIION OF DrlEASE. FACTORS IN The following factors have bcen differentiated (but they are not mutually exclusive): PrrdiupoeingJactors are those that prepare, sensitize, condition, or otherwise create a situation such as a level of immunity or state of susceptibility so that the host tends to react in a specific fashion to a disease agent, personal interaction, environ- mental stimu)us, or specific incentive. Examples include age. sex, marital status, t~ez T-sC zo%

causes of death 22 family size, educational level, previous illness experience, presence of concurrent illness, dependency, working environment, and attitudes toward the use of health services. These facton may be "necessary" but_ are rarely "sufficient" to cause se the phenomenon under study. EnabGng jodon art those that facilitate the manifestation of disease, disability, ill- health, or the use of services or conversely those that faciliute 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. Precnpitntiniq Jadon are those associated with the definitive onset of a disease, ill- ness, 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 infectious organism, drug, noxious agent, physical trauma, personal interaction, occupational stimulus, or new awareness or knowl- ed ge. Rnnjorcing jactors are those tending to perpetuate or aggravate the presence of a disease, disabihty, impairment. attitude, pattern of behavior, or course of action. They may tend to be repetitive, recurrent, or persistent and may or may not nec- essarily be the same or similar to those categorized as predisposing, enabling. or precipitating. Examples include repeated exposure to the same noxious stimulus (in (he absence of an appropriate immune response) such as an infectious agent. work, household, or interpersonal environment, presence of financial incentive or disin-_ centive, personal satisfaction, or deprivation._ CAUSES OF DEATH See DEATH CERTIFICATE. CAUS_ E-DELETED uFt TABL[ A life table constructed using death rates lowered by elim- inating the risk of dying from a specified cause: its most common use is to calculate the gain in life expectancy that would result from the elimination of one cause. CAUSE-srECtnC suTE A rate that specifies events, such as deaths, according to their cause. eENSOtuNC This term refers to the loss of subjects from a follow-up study; the occur- rence of the event of interest among such subjects is unceruin after a specified time when it was known that the event of interest had not occurred; it is not known. however, if or when the event of interest occurred subsequently. Such subjects are desc-ribed as censored. For example, in a follow-up study with tnyocardial infarction as the outcome of interest, a subject who has not had an infarct but is killed in a traffic crash in year 6 is described as censored as of year 6, since it cannot be known when, if ever, he might have had an infarct at a later year of follow,up. This is censoring by competing risk; other varieties include loss to follow-up and termina- tion of the study. Examination of data for censoring requires thc use of special analytic methods, such as life table analysis. cENSUS An enumeration of a population, originally intended for purposes of taxation and milita -ry service. Census enumeration of a population usually records identities of all persons in every place of residence, with age, or birth date, sex, occupation, national origin, language, mariul sutus, income, and relationship to head of house- hold, in addition to information on the dwelling place. Many other items of infor- mation may be inclu_ded, e.g., educational level (or literacy), and health-related data such as permanent disability. A de facto census allocates persnns according to their location at the time of enumeration. A de jure census assigns persons according to tbEir usual place of residence at the time of enumeration. 23 class cENSUS 'ntACr An area for which details of population structure are separately tabu- lated at a periodic census; normally it is the smallest unit of analysis of (published) census tabulations. Census tracts are chosen because they have well-defined bound- aries, sometimes the same as local political jurisdictions, sometimes defined by con- spicuous geographical features such as main roads, rivers. In urban areas census tracts may be further subdivided, e.g., into city blocks, but published tables do not contain details to this level. CENTaLE See QUANTILFS. C_E_SSATION EIFERIMENT Controlled study in which an attempt is made to evaluate the termination of an exposure to risk such as a living habit that is considered to be of etiologic importance. CHART The medical dossier Of a patient. See also 1NFORMATION SVSTEM; MEDICAL RE- CORD. ettteR Dtcrt A single digit. derived from a multidigit number such as a case identifi- cation numlxr, that is used as a screening test for transcription errors. CHEMOrROrxvLAXIs The administration of a chemical, including antibiotics. to prevent the development of an infection or the progression of an infection to active mani- fest disease. CHEMOI7IERARY The use of a chemical to_ treat a clinically recognizable disease or to_ limit its further progress. - CHILD DEATH RATE ThFnumber of deaths of children aged 1-4 years in a given year per 1000 children in this age group. This is a usEful measure of the burden of preventable communicable diseases in the child population. CHt-SQUARE (Xr) DIST/UnUTtON A variable is said to have a chi-square distribution with A degrees of freedom if it is distributed like the sum of the squares of K indepen- dent random variables, each of which has a normal distribution with mean z_ero and variance one. cHt-sqUARE (Xr) TFST Any statistical test based on comparison of a test statistic to a chi- square distribution. The oldest and most common chi-square tests are for detecting whether two or more population distributions differ from one another; these tests usually involve counts of data, and may involve comparison of samples from the distributions under study, or the comparison of a sample to a theoretically expected distribution. The Pearson chi-square test is probably the best known; another is the Manlel-Haenszel test. (Statisticians disagree about the terminal letter; a bare ma- jority of those who contributed to the discussion of this entry prefer "chi-square" rather than "chi-squared." Either usage is acceptable.) estRZSOMS This word, which appears in Blt.ts oF MORTAIJTV, means infants who die txfore formal baptism; therefore, the number recorded in Bills of Mortality can be used to estimate (albeit inaccurately) neonatal death rates in studies of historical demography and epidemiology. cHRDNtc I. Referring to a health-related state, (asting a long time. 2. Referring to ex- posure, prolonged or long-term, often with specific reference to low-intensity. 3. The U.S. National Center for Health Statistics defines a "chronic" condition as one of three months' duration or longer. ct.ASS A term used in the theory of frequency distributions. The total number of ob- servations made upon a particular variate may be grouped into classes according to convenient divisions of the variate range in order to make subsequent analyses less laborious, or for other reasons. A group so determined is called a "class." The variate values that determine the upper and lower limits of a class are called "class boundaries," the interval between them is the class interval, and the• tn-oucnrv fall- YS(iC. Y9(.%OC.

classification 24 C(ASSIFICATION (Syn: categorization) Assignment to predesignated classes on the basis of perceived common characteristics. A means of giving ordcr to a group of discon- nected facts. Idealh, a classification should be characterized by (I) naturalness-the classes correspond to the nature of the thing being classified. (2) exhaustiveness- every member of the group will fit into one (and only one) class in the system, (3) usefulness--the classification is practical, (4) simplicity-the subclasses are not ex- cessive, and (5) constructability-the set of csasses can be constructed by a demon- strabl) systematic procedure. CL_ASSIFICATtoN oP DISEASES Arrangement of diseases into groups having common characteristics. Useful in efforts to achieve standardization, and therefore compa- rability, in the methods of presentation of mortality and morbidity data from dif- ferenl sources. May include de a systematic numerical notation fnr each disease entry. Examples InclUde the INTERNATIONAL CLAS-IIFICAT-ION OF DIS€ASFS, IN,IURIES, AND CAUSES OF DEATH (ICD) and the INTERNATIONAL CLASSIFICATION OF HEALTH PROSLEMS IN PRIMARY CARE (ICHPPC). CLASS, SOCIAL A method of socially stratifving populations, e.g., according to education, income, or occupation. See a1S0 SOCIOECONOMIC CLASSIFICATION. CLINICAL DECISION ANALYSIS Application Of DECISION ANALYSIS in a clinical setting wilh the aim of applying epidemiologic and other data on probability of outcomes when alternative decisions can be made, e.g., surgical imervention or drug treatment for mvocardial ischemia. CLtNICAL EPIDEMIOLOCdST A practitioner of clinical epidemiology. CLINICAL EPIDEMIOLOGY While some epidemiologists deplore any adjectival qualifica- .. tion of the discipline, a subspecialty of clinical epidemiology is sufficiently demar- cated to justify definition. There are plenty of suggested definitions. Johu R. Paul' proposed "A marriage between quantitative concepts used by epidemiologists to study disease in populations and decision-making in the individual case which is the daily fare of cliniwl mec(icine." Patient care is central to S•eckett's delinitiont: "The application, by a phvsician who provides direct patient care, of epidemiologic and biometric methods to the study of diagnostic and therapeutic processes in urder to effect an improvement in health." While limiting the discipline to medical graduates in clinical practice, this definition is conceptually close to the definition of clinical decision analysis: the proper distinction between clinical epidemiology and clinical decision analysis may be that the epidemiologist works with a defined pnpulation, even if it is a population of patients rather than a community-based population with numerator and denominator in the conventional epidemiolugic sense; clinical deci- sion analysis can be applied to a single patient. Abramson's definition' is "The use of epidemiological principles, methods and findings in personal health care or community-oriented primary care, with special refcrence to applications in diag- nostic and prognostic appraisal, decisions concerning care and the evaluation of care. The term sometimes refers to anv epidemiological study conducted in a clin- ical setting." Weiss' defines clinical epidemiology as "The study of variation in the outcome of illness and of the reasons for that variation." The existence of the above and other subtly different definitions suggesu_ that this branch of epidemiology remains inchoate. ' f Chn fwtrst 17:519-54 I. 1938. 'Ar, f t(nMruol fl9:125-128. 1969. ' Personal communicatiun. 1986. 'C6nicof Eptdnniolog.. New York: Uxford University Press, 1986. CLINICAL TRIAL (Syn: therapeutic trial) A research activity that involves thr administra- tion of a test regimen to humans to evaluate its efficacy and safety. The term is 25 cohort slopes subject to wide variation in usage, from the first use in humans without any control treatment to a rigorously designed and executed experiment involving test and con- trol treatments and randomization. tion. See alSO COMMIINITI' TRIAL. C_LINIMETRICS Feinstein,' who coined this term, defines it as the domain concerned with indexes, rating scales, and other expressions that are used to describe or measure svnlptoms, physical signs, and other distinctly clinical phenomena in clinical medi- cine. Such measurements, of course, are an essential part of many epidemiologic studies. 'Feinslein AR: C/initn.fnn. New Haven and l.ondon: Yale University Press, 1987. CLOSED CouORT A population in which membership begins at a defined time or with a defined event and ends only through occurrence of the study outcome or the end of eligibility for membership. An example is a population of women in labor being studied to determine the vital status of their offspring (i.e., whether live or still- born). CLUSTER ANALYSIS A set of statistical methods used to group variables or observations into strongly interrelated subgroups. CLl/iTERING (Svn: 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 nor- malle used to describe aggregation of relatively uncommon events or diseases, e.g., leukemia, multiple sclerosis. CLUSTER SAMPLING A sampling method in which each unit selected is a group of per- sons (all persons in a city block, a family, etc.) rather than an individual. CootNG Translation of information, e.g., questionnaire responses. into numbered cate- gories for entry in a data processing system. COEFFICIENT OF VARIAT-lON The ratio of the standard deviation to the mean. This is meaningful onlv if the variable is measured on a ratio scale. See MEASUREMENT SCALE. COHORT )from Latin cohon, warriors, the tenth part of a legionj I. The component of the population born during a particular period and iden- tified by period of birth so that its characteristics (e.g., causes of death and numbers still living) can be ascertained as it enters successive time and age periods. - 2. The term "cohort" has broadened to describe any designated group of per- sons who are followed or traced over a period of time, as in COHORT STUDY (prospective study). COHORT ANALYSIS The tabulation and analysis of morbidity or mortality rates in rda- tionship to the ages of a specific group of people (cohort), identified at a particular period of time and followed as they pass through different ages during part or all of their life span. In certain circumstances, e.g., studies of migrant populations, cohort analysis may be performed according to duration of residence of migrants in a country rather than year of binh, in order to relate health or mortality expe- rience to duration of exposure. COHORT COMPONENT METHOD A method of population projection that takes the popu- lation distributed by age and sex at a base date and carries it forward in time on the basis of sepante allowances for fertility, mortality, and migration. COHORT EFFECT Sef GENERATION EFFECT. COHORT INCIDENCE See INCIDENCE. COHORT SLOPES Arrangement of data so that when ploued graphically, lines connect points representing the age-specific rates for population segments from the same

co6orx etudr 500 Cohort 200 100 50 20 10 5 2 1 0.5 0.2 0.1 26 curves for yeara of birth, 1860-1950* ~ - - 1 - t9 193 1940 0 ~9_50 20 1900 40 60 Age . The tine associated with each year indicates death rates by age-group /or persons born in that year 1870 1880 80 100 Cohort slopes (tuberculosis mortality rates of successive birth generations). Death rates for tuberculosis, by age, United States, 19(N)-19fi0 (per 100,t/W population). ErorA Susser, Watson, Hopper, 1985. generation of birth (see diagram). These slopes represent changes in rates with age during the life experience of each cohort. COHORT STUDY (Syn: concurrent, follow-up. incidence, longitudinal, prospective study) The method of epidemiologic study in which subsets of a defined population can be identified who are, have been, or in the future may be exposed or not exposed, or exposed in different degrees, to a factor or factors hypothesized to influence the probability of occurrence of a given disease or other outcome. The alternative terms for a cohort study, i.e., follow-up, longitudinal, and prospective study, describe an essential feature of the method, which is observation of the population for a sufli- cient number of person-years to genente reliable incidence or mortality rates in the population subsets. This generally implies study of a large population, study for a prolonged period (years), or both. Co1NTERYENT1oN In a RANDOMIZED CONTROLLED TRIAL, the application of additional di- agnostic or therapeutic procedures to members of either or both the experimental and the control groups. COLD CHAIN A system of protection against high environmental temperatures for heat- labile vaccines, sera, and other active biological prepantions. Unless the cold chain is preserved, such preparations are inactivated and immunization procedures, etc. will.be ineffective. f'reservation of the cold chain is an integral part of the WHO expanded program on immunization in tropical countries. CoLLSNEARSTY Very high correlation between variables. COLONIZATION See INrECTION. COMMENSAL Litenlly, eating together (sharing the same table); an organism t_hat lives harmlessly in the gut. See also xENOeloTlc. COMMON SOURCE EPIDEMIC (Syn; common vehicle epidemic) See EPIDEMIC, COMMON SOURCE. so 1890 27 community trial COMMON vEHta,E sPRUD Spread of disease agent from a source that is common to those who acquire the diseast, e.g., water, milk, shellfish, foods, air, or syringe contaminated by infectious or noxious agents. See also TRANSMISSION oF INFEC- TION. - - - COMMUNICASL_E DtSEASE (Svn: infectious disease) An illness due to_ a specific infectious agent or its toxic products that arises through transmission of that agent or its products from an infected person, animal, or reservoir to a susceptible host, either directly or indirectly through an intermediate plant or animal host, vector, or the inanimate environment. See also TRANSMISSION OF INFECTION. COMMUNIGASLE PERIOD The time during which an infectious agent may be transferred directly or indirectly from an infected person to another person, from an infected animal to man, or from an infected person to an animal, including arthropods._ See alSO TRANSMISSION or INFECTION. CoMMUNrtv A group of individuals organized into a unit, or manifesting some unifying trait or common interest; loosely, the locality or catchment area population for which a service is provided, or more broadly, the state, nation, or body politic. COMMUNrTY DIAGNOSIS T'he process of appraising the health status of a community, including assembly of vital statistics and other health-related statistics and of infor- mation pertaining to determinants of health, such as prevalence of tobacco smok- ing. and examination of the relationships of these determinants to health in the specified community. The term may also denote the findings of this diagnostic pro cess. Community diagnosis may attempt to be comprehensive, or may be restricted to specific health conditions. determinants, or subgroups. J.N. Morris' identified community diagnosis as one of the uses of epidemiology. 'Br Mrd J 2:l95-401 • 1955. COMMUNr7Y HEALTH See PUSUC HEAL_TH. COMMUNrrY MEDICINE Since the late 1960s, this term has gained wide currency as the preferred name for important activities concerning health care in the community. There are several different definitions, including the following. I. The field concerned with the study of health and disease in the population of a defined community or group. lu goal is to identify the health problems and needs of defined populations, to identify means by which these needs should be met, and to evaluate the extent to which health services effectively meet these needs. 2. The practice of medicine concerned with groups or populations rather than with individual patients. This includes the elements listed in definition I, to- gether with the organization and provision of health care at a community or group level. 3. The term is also used to describe the practice of medicine in the community, e.g., by a family physician. Some writers equate the terms "family medicine" and "community medicine"; others confine its use to public health practice. 4. Community-oriented primary health care is an integration of community medicine with the primary health care of individuals in the community. In this form of practice the community practitioner or community health learn has responsibility for health care re both at a community and at an individual level. See also PuSLIC HEALTH: SOCIAL MEDICINE. C_OMMUNITY TAIAL Experiment in which the unit of allocation to receive a preventive or therapeutic regimen is an entire community or political subdivision. Examples in- clude the trials of fluoridation of drinking water, and of heart disease prevention in North Karelia (Finland) and California. See also CLINICAL TRIAL.