Berksonian bias where D= disease, S= symptom, and D= no disease. The formula emphasizes what clinical intuition often overlooks--namely, that the probability of disease given this ymptom depends not only on how characteristic of the disease that symptom is but also on how frequent the disease is among the population being served 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 tha Some of the terms in the theorem are named. The probability of the symptom is the POSTERIOR PROBABILITY. It is an estimate of the disease posterior to knowing whether or not the symptom was preser 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 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) BEDSIDE ISoLATIoN See BARRIER NURSING BEHAVIORAL EPIDEMIC An epidemic attributable to the power of suggestion or to culturally determined 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 epidemics"), crowd panic, and waves of fash ion or enthusiasm. The communicable nature of the behavior is dependent not only on person-to-person transmission of the behavioral pattern but also on group reinforce environment by a toxic substance)or may complicate then to o ncs may be difficult ment(as with smoking, alcohol, and drug use). Behavioral epidem to differentiate from outbreaks of organic disease(e. g, d BEHAVIORAL RISK FACToRa characteristic or behavior that is associated with increased probability of a specified outcome; the term does not imply a causal elationship BEHAVIOR SETTING The place where a pattern or sequence of behavior regularly occurs;it includes the ordinary events of daily life. s A forerunner of the concept of BENCHMARK A slang or jargon term, usually meaning a measurement taken at the out- set of a series of measurements of the same variable, sometimes meaning the best or most desirable value of the variable BENEFICENCE Literally, doing good. In bioethics, a principle underlying utilitarian oaches. It implies a certain obligation to good, typically balancing potential or produced goods against risks. In public health, it implies acting in the best interest of the population at stake. 36-37 BENEFIT Advantage or improvement resulting from an intervention. BENEFIT-COST RATIO See CoST-BENEFIT ANALYSIS BERKSONIAN BIAS (Syn: Berkson's bias, Berkson fallacy) A form of SELECTION BIAS arising when both the exposure and the disease under study affect selection. In its clas- sical form, it causes hospital cases and controls in a case-control study to be system- atically different from one another. s This occurs when the combination of exposure and disease under study increases the probability of admission to hospital, leading to a systematically higher exposure rate among hospital cases than among hospital controls the process hence biases the odds ratio
where D = disease, S = symptom, and D– = no disease. The formula emphasizes what clinical intuition often overlooks—namely, that the probability of disease given this symptom depends not only on how characteristic of the disease that symptom is but also on how frequent the disease is among the population being served. The theorem can also be used for estimating exposure-specifi c 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 are named. The probability of disease given the symptom is the posterior probability. It is an estimate of the probability of disease posterior to knowing whether or not the symptom was present. 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 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). BEDSIDE ISOLATION See barrier nursing. BEHAVIORAL EPIDEMIC An epidemic attributable to the power of suggestion or to culturally determined 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 epidemics”), crowd panic, and waves of fashion or enthusiasm. The communicable nature of the behavior is dependent not only on person-to-person transmission of the behavioral pattern but also on group reinforcement (as with smoking, alcohol, and drug use). Behavioral epidemics may be diffi cult to differentiate from outbreaks of organic disease (e.g., due to contamination of the environment by a toxic substance) or may complicate them. BEHAVIORAL RISK FACTOR A characteristic or behavior that is associated with increased probability of a specifi ed outcome; the term does not imply a causal relationship. BEHAVIOR SETTING The place where a pattern or sequence of behavior regularly occurs; it includes the ordinary events of daily life.18 A forerunner of the concept of activity setting. BENCHMARK A slang or jargon term, usually meaning a measurement taken at the outset of a series of measurements of the same variable, sometimes meaning the best or most desirable value of the variable. BENEFICENCE Literally, doing good. In bioethics, a principle underlying utilitarian approaches. It implies a certain obligation to promote benefi ts of things judged to be good, typically balancing potential or produced goods against risks. In public health, it implies acting in the best interest of the population at stake.36,37 BENEFIT Advantage or improvement resulting from an intervention. BENEFIT-COST RATIO See cost-benefi t analysis. BERKSONIAN BIAS (Syn: Berkson’s bias, Berkson fallacy) A form of selection bias arising when both the exposure and the disease under study affect selection. In its classical form, it causes hospital cases and controls in a case-control study to be systematically different from one another.38 This occurs when the combination of exposure and disease under study increases the probability of admission to hospital, leading to a systematically higher exposure rate among hospital cases than among hospital controls; the process hence biases the odds ratio. 17 Berksonian bias
Bernoulli distribution BERNOULLI DISTRIBUTION The probability distribution associated with two mutu ally exclusive and exhaustive outcomes. g, death or survival; a Bernoulli variable is one that has only two possible values.g, death or survival. See also BINOMIAL DISTRIBUTION BERTILLON CLASSIFICATION The first numerically based NOSOLOGY in which disease entities were arranged in chapters, developed by Jacques Bertillon(1851-1922).3It descended from a nosology proposed in 1853 by Marc d'Espigne and william Farr Bertillon,s classification was adopted at the International Statistical Institute(confer- ence)in Chicago in 1893 and was the progenitor of the INTERNATIONAL CLASSI OF DISEASES (ICD). BETA ERROR See ERROR TYPE IL. BIAS Systematic deviation of results or inferences from truth. Processes leading to such deviation. An error in the conception and design of a study--or in the collection, analy sis, interpretation, reporting, publication, or review of data-leading to results or con clusions that are systematically (as opposed to randomly) different from truth -l2- 14 31-34 Ways in which deviation from the truth can occur include 1. Systematic variation of measurements from the true values (syn: systematic 2. Variation of statistical summary measures(means, rates, measures of association. etc. ) from their true values as a result of systematic variation of measurements, other flaws in study conduct and data collection, flaws in study design, or analysis. 3. Deviation of inferences from truth as a result of conceptual or methodological flaws study conception or design, data collection, or the analysis or interpretation of results 4. A tendency of procedures(in study design, data collection, analysis, interpretation, review, or publication) to yield results or conclusions that depart from the truth 5. Prejudice leading to the conscious or unconscious selection of research hypotheses or procedures that depart from the truth in a particular direction or to one-sidedness in the interpretation of resul The term bias does not necessarily carry an imputation of prejudice or any other subjective factor, such as the experimenter's desire for a particular outcome. This differs from onventional usage, in which bias refers to a partisan point of view--to prejudice or unfairness BIAS, ASCERTAINMENT See ASCERTAINMENT BIAS BIAS. BERKSON'S See BERksoN's bias BIAS, CONFOUNDING See CoNFOUNDING BIAS. BIAS, WORKUP See woRKUP BIAS. BIAS DUE TO DIGIT PREFERENCE See DIGIT PREFERENCE. BIAS DUE TO INSTRUMENT ERROR Systematic error due to faulty CALIBRATION, inac curate ing instruments, contaminated reagents, incorrect dilution or mixing of reagents, etc. See also CoNTAMINATION, DATA BIAS DUE TO WITHDRAWALS A difference between the true effect and the association bserved in a study due to characteristics of subjects who choose to withdraw. See also ATTRITION, CENSORING, DROPOUT. BIAS IN ASSUMPTIONS (Syn: conceptual bias) Error arising from faulty logic or premises or mistaken beliefs on the part of the investigator. False conclusions about the explanation for associations between variables. Example: Having correctly deduced the
BERNOULLI DISTRIBUTION The probability distribution associated with two mutually exclusive and exhaustive outcomes—e.g., death or survival; a Bernoulli variable is one that has only two possible values—e.g., death or survival. See also binomial distribution. BERTILLON CLASSIFICATION The fi rst numerically based nosology in which disease entities were arranged in chapters, developed by Jacques Bertillon (1851–1922).39 It descended from a nosology proposed in 1853 by Marc d’Espigne and William Farr. Bertillon’s classifi cation was adopted at the International Statistical Institute (conference) in Chicago in 1893 and was the progenitor of the International Classifi cation of Diseases (ICD). BETA ERROR See error, type ii. BIAS Systematic deviation of results or inferences from truth. Processes leading to such deviation. An error in the conception and design of a study—or in the collection, analysis, interpretation, reporting, publication, or review of data—leading to results or conclusions that are systematically (as opposed to randomly) different from truth.5–12,14,31–34 Ways in which deviation from the truth can occur include: 1. Systematic variation of measurements from the true values (syn: systematic measurement error). 2. Variation of statistical summary measures (means, rates, measures of association, etc.) from their true values as a result of systematic variation of measurements, other fl aws in study conduct and data collection, fl aws in study design, or analysis. 3. Deviation of inferences from truth as a result of conceptual or methodological fl aws in study conception or design, data collection, or the analysis or interpretation of results. 4. A tendency of procedures (in study design, data collection, analysis, interpretation, review, or publication) to yield results or conclusions that depart from the truth. 5. Prejudice leading to the conscious or unconscious selection of research hypotheses or procedures 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 imputation of prejudice or any other 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—to prejudice or unfairness. BIAS, ASCERTAINMENT See ascertainment bias. BIAS, BERKSON’S See Berkson’s bias. BIAS, CONFOUNDING See confounding bias. BIAS, WORKUP See workup bias. BIAS DUE TO DIGIT PREFERENCE See digit preference. BIAS DUE TO INSTRUMENT ERROR Systematic error due to faulty calibration, inaccurate measuring instruments, contaminated reagents, incorrect dilution or mixing of reagents, etc. See also contamination, data. BIAS DUE TO WITHDRAWALS A difference between the true effect and the association observed in a study due to characteristics of subjects who choose to withdraw. See also attrition; censoring; dropout. BIAS IN ASSUMPTIONS (Syn: conceptual bias) Error arising from faulty logic or premises or mistaken beliefs on the part of the investigator. False conclusions about the explanation for associations between variables. Example: Having correctly deduced the Bernoulli distribution 18
Binary variable mode of transmission of cholera, John Snow concluded that yellow fever was transmit ted by similar means. In fact, the"miasma theory would have been a better fit for the acts of yellow fever transmission. See also BIOLOGICAL PLAUSIBILITY, COHERENCE. BIAS IN AUTOPSY SERIES Systematic errors resulting from the fact that autopsies nt a nonrandom sample of all deaths. BIAS IN HANDLING OUTLIERS Error arising from biased discarding of unusual values due to exclusion of unusual values that should be included BIAS IN THE PRESENTATION OF DATA Error due to irregularities produced by DIGIT PREFERENCE, incomplete data, poor techniques of measurement, technically poor laboratory procedures, or intentional attempts to mislead BIAS IN PUBLICATION See PUBLICATION BIAS BIAS OF AN ESTIMATOR The difference between the expected value of an estimator of parameter and the true value of this parameter. See also UNBIASED ESTIMATOR BIAS OF INTERPRETATION See INTERPRETIVE BIAS BIBLIOGRAPHIC IMPACT FACTOR(BIF) In SCIENTOMETRICS, a useful measure of the average"frequency with which articles in a scientific periodical are cited by articles in journals that are chosen by the Thomson Corporation to be indexed in the Science Citation Index(SCI)and related databases. 4n Given the limited properties of the biF, even when properly applied to journals, and the well-known fact that scientific articles may have a wide spectrum of impacts(or none),4I it is clear that the cultural impact of the "impact factor"in the academic community ha less to do with scientific rationality than with the SocIOLOGY OF SCIENTIFIC KNOWLEDGE (and human nature). Attributing bibliometric indicators for journals to articles or to individual authors is a form of the ECOLOGICAL FALLACY The BiF has virtues and limitations. Main reasons why, even for a given journal, BIF is often not the scientometric indicator of choice include the following: BIF is extremely infuenced by the number of"source items"or"citeable articles"chosen as the denominator of the BIF (i.e. by the number of articles chosen by Thomson among articles published in the journal in the previous 2 years); such articles are not disclosed criteria used by Thomson to decide which articles are included and excluded in the denominator of the BIF are unknown, and so is the consistency of their application across journals; citations to articles excluded from the denominator of the bif are nevertheless counted in the numerator If the journal is the unit of analysis, the total number of citations received by all articles published by such journal may be a better indicator. If the bibliographic"impact"of an article is of interest, the total number of citations received by the article may the best place to start. 4 BILLS OF MORTALITY Weekly and annual abstracts of christenings and burials com- piled from parish registers in England, especially London, that date from 1538. Begi ning in 1629, the annual bills were published and included a tabulation of deaths from plague and other causes. These were the basis for the earliest English vital statistics, compiled, analyzed, and discussed by John Graunt(1620-1674)in Natural and political Observations. on the Bills of mortality(London, 1662) BIMODAL DISTRIBUTION A distribution with two regions of high frequency separated frequency of observations. A two-peak distribution. BINARY VARIABLE A variable y two possible values(e.g, on or off, 0 or 1). See also mEAsUrement scale
mode of transmission of cholera, John Snow concluded that yellow fever was transmitted by similar means. In fact, the “miasma” theory would have been a better fi t for the facts of yellow fever transmission. See also biological plausibility; coherence. BIAS IN AUTOPSY SERIES Systematic errors resulting from the fact that autopsies represent a nonrandom sample of all deaths. BIAS IN HANDLING OUTLIERS Error arising from biased discarding of unusual values or due to exclusion of unusual values that should be included. BIAS IN THE PRESENTATION OF DATA Error due to irregularities produced by digit preference, incomplete data, poor techniques of measurement, technically poor laboratory procedures, or intentional attempts to mislead. BIAS IN PUBLICATION See publication bias. 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 unbiased estimator. BIAS OF INTERPRETATION See interpretive bias. BIBLIOGRAPHIC IMPACT FACTOR (BIF) In scientometrics, a useful measure of the “average” frequency with which articles in a scientifi c periodical are cited by articles in journals that are chosen by the Thomson Corporation to be indexed in the Science Citation Index (SCI) and related databases.40,41 Given the limited properties of the BIF, even when properly applied to journals, and the well-known fact that scientifi c articles may have a wide spectrum of impacts (or none),41 it is clear that the cultural impact of the “impact factor” in the academic community has less to do with scientifi c rationality than with the sociology of scientifi c knowledge (and human nature). Attributing bibliometric indicators for journals to articles or to individual authors is a form of the ecological fallacy. The BIF has virtues and limitations. Main reasons why, even for a given journal, BIF is often not the scientometric indicator of choice include the following: BIF is extremely infl uenced by the number of “source items” or “citeable articles” chosen as the denominator of the BIF (i.e., by the number of articles chosen by Thomson among articles published in the journal in the previous 2 years); such articles are not disclosed; criteria used by Thomson to decide which articles are included and excluded in the denominator of the BIF are unknown, and so is the consistency of their application across journals; citations to articles excluded from the denominator of the BIF are nevertheless counted in the numerator. If the journal is the unit of analysis, the total number of citations received by all articles published by such journal may be a better indicator. If the bibliographic “impact” of an article is of interest, the total number of citations received by the article may the best place to start.41 BILLS OF MORTALITY Weekly and annual abstracts of christenings and burials compiled from parish registers in England, especially London, that date from 1538. Beginning in 1629, the annual bills were published and included a tabulation of deaths from plague and other causes. These were the basis for the earliest English vital statistics, compiled, analyzed, and discussed by John Graunt (1620–1674) in Natural and Political Observations … on the Bills of Mortality (London, 1662). BIMODAL DISTRIBUTION A distribution with two regions of high frequency separated by a region of low frequency of observations. A two-peak distribution. BINARY VARIABLE A variable having only two possible values (e.g., on or off, 0 or 1). See also measurement scale. 19 Binary variable
Binomial distribution BINOMIAL DISTRIBUTION A probability distribution associated with two mutually sive outcomes(e.g, presence or absence of a clinical or laboratory sign, death or ival). The probability distribution of the number of occurrences of a binary event in a sample of n independent observations. The binomial distribution may be used to model cumulative incidence rates and prevalence the bernoulli distribution is a ecial case of the binomial distribution with n BIOACCUMULATION Progressive increase in the concentration of a chemical compound in an organism, organ, or tissue when the rate of uptake exceeds the rate of excretion or metabolism In humans, exposure to and bioaccumulation of persistent chemical agent occurs largely through the fatty components of animal foods, including recycled animal ats from slaughterhouses, which are used as components of food products and animal feed ingredients. Bioaccumulation occurs within a trophic( food chain) level. See also BIOMAGNIFICATION BIOASSAY The quantitative evaluation of the potency of a substance by assessing its effects on tissues, cells, live experimental animals, or humans. Bioassay may be a direct method of estimating relative potency: groups of subjects are assigned to each of two (or more)preparations, the dose that is just sufficient to produce a specified response is measured, and the estimate is the ratio of the mean doses for the two(or more) group 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 magni- tude of a dose and the magnitude of a quantitative response produced by it. See also BIODIVERSITY (Syn: biological diversity) The variety of species of plants, animals, and microorganisms in a natural community, of communities within a particular environ- ment,and of genetic variation within a species(GENETIC DIVERSITY). Biodiversity is important for the stability of ecosystems. To many individuals worldwide it is also a cultural value “B|oLoG| CAL AGE” 1. An attribute of body tissue that is relevant in PATHOGENESIS; e.g., " age"of breast tissue, which develops after puberty, in relation to breast cancer risk. 42 See also ARMITAGE-DOLL MODEL 2. People age with different"speed"at equal"calendar age. Some people ar physically older than others, and this is expressed in external appearance, body characteristics, or physical and social functioning. The concept is applied in the form of the calculation of the biological age of the subject by multiple regression. BIOLOGICAL MONITORING(Syn: biomonitoring) Performance, analysis, and interpre- tation of biological measurements aimed at detecting changes(often adverse) in the health status of populations, in an environmental compartment(including water, air or soils), or in other health DETERMINANTS (e.g, food samples, animal feed). Monitoring of concentrations of suspected or known toxic or hazardous substances using biological means in well-defined populations(e.g, analyses of concentrations of environmental chemical agents in samples of urine, blood, or adipose tissue). Examples include the U.s.NationalReportsonHumanExposuretoEnvironmentalChemicals(www.cdc gov/exposurereport)andtheGermanEnvironmentalSurveys(www.umweltbunde samt.de/survey-e) See also MONITORING SURVEILLANCE. BIOLOGICAL PLAUSIBILITY The CAUSAL CRITERION or consideration that an observed presumably causal ASSOCIATION is plausible on the basis of existing biomedical knowledge
BINOMIAL DISTRIBUTION A probability distribution associated with two mutually exclusive 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 binary event in a sample of n independent observations. The binomial distribution may be used to model cumulative incidence rates and prevalence. The Bernoulli distribution is a special case of the binomial distribution with n = 1. BIOACCUMULATION Progressive increase in the concentration of a chemical compound in an organism, organ, or tissue when the rate of uptake exceeds the rate of excretion or metabolism. In humans, exposure to and bioaccumulation of persistent chemical agents occurs largely through the fatty components of animal foods, including recycled animal fats from slaughterhouses, which are used as components of food products and animal feed ingredients. Bioaccumulation occurs within a trophic (food chain) level. See also biomagnifi cation. BIOASSAY The quantitative evaluation of the potency of a substance by assessing its effects on tissues, cells, live experimental animals, or humans. Bioassay may be a direct method of estimating relative potency: groups of subjects are assigned to each of two (or more) preparations, the dose that is just suffi cient to produce a specifi ed 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. See also interaction. BIODIVERSITY (Syn: biological diversity) The variety of species of plants, animals, and microorganisms in a natural community, of communities within a particular environment, and of genetic variation within a species (genetic diversity). Biodiversity is important for the stability of ecosystems. To many individuals worldwide it is also a cultural value. “BIOLOGICAL AGE” 1. An attribute of body tissue that is relevant in pathogenesis; e.g., “age” of breast tissue, which develops after puberty, in relation to breast cancer risk.42 See also Armitage-Doll model. 2. People age with different “speed” at equal “calendar age.” Some people are physically older than others, and this is expressed in external appearance, body characteristics, or physical and social functioning. The concept is applied in the form of the calculation of the biological age of the subject by multiple regression. BIOLOGICAL MONITORING (Syn: biomonitoring) Performance, analysis, and interpretation of biological measurements aimed at detecting changes (often adverse) in the health status of populations, in an environmental compartment (including water, air or soils), or in other health determinants (e.g., food samples, animal feed). Monitoring of concentrations of suspected or known toxic or hazardous substances using biological means in well-defi ned populations (e.g., analyses of concentrations of environmental chemical agents in samples of urine, blood, or adipose tissue). Examples include the U.S. National Reports on Human Exposure to Environmental Chemicals (www.cdc. gov/exposurereport) and the German Environmental Surveys (www.umweltbunde samt.de/survey-e). See also monitoring; surveillance. BIOLOGICAL PLAUSIBILITY The causal criterion or consideration that an observed, presumably causal association is plausible on the basis of existing biomedical knowledge. Binomial distribution 20
Birth cohort On a schematic continuum including possible, plausible, compatible, and coherent, the term plausible is not a demanding or stringent requirement, given the many biological mechanisms that often may underlie clinical and epidemiological observations; hence, in assessing CAUSALITY, it may be logically more appropriate to require CoHERENCE(bio- logical as well as clinical and epidemiological). The criterion of biological plausibility should hence be used cautiously, since it could impede development of new knowl edge that does not fit existing biological evidence or pathophysiological reasoning Innovative, valid, and relevant clinical and epidemiological discoveries may prece he acquisition of knowledge on their biological mechanisms; 1. e, biologically relevant epidemiological evidence may precede biological evidence. In evaluating associations between genetic variants and common complex diseases, we should fully expect bio- logically meaningful associations with small clinical or epidemiological effects. 4 See also CoHERENCE: HILLS CRITERIA OF CAUSATION. BIOLOGICAL TRANSMISSION See VECTOR-BORNE INFECTION BIOMAGNIFICATION(Syn: biological magnification, bioamplification) Sequence of processes in an ecosystem by which higher concentrations (e.g, of a persistent toxic substance)are attained in organisms at higher levels in the food chain. The increase in concentration of an element or compound, such as a pesticide, that occurs in a food chain. Biomagnification occurs across trophic(food chain) levels. See also IOMARKER, BIOLOGICAL MARKER A cellular, biochemical, or molecular indicator of exposure; of biological, subclinical, or clinical effects; or of possible susceptibility (e. g, biomarkers of internal dose, biologically effective dose, early altered structure, altered function). It is occasionally an ambiguous term that sug gests insufficient understanding of the pathophysiological or mechanistic role of the "marker. See alSo MOLECULAR EPIDEMIOLOGY BIOMETRY Literally, measurement of life. The application of statistical methods to the study of numerical data based on observation of biological phenomena. The term made popular by Karl Pearson(1857-1936), who founded the journal Biometrika. The British biologist Francis Galton(1822-1911)has been described as the founder of biometry, but others-e. g, the Frenchman Pierre-Charles-Alexandre Louis(1787 187 ceded him BIOMONITORING See BIOLOGICAL MONITORING BIOSTATISTICS Application of STATISTICS to biological problems. The term should not be restricted to mean the application of statistics to medical problems(MEDICAL STATIS- TIcs), since its real meaning is broader, subsuming agricultural statistics, forestry, and ecology, among other applications. BIRTH CERTIFICATE Official, legal document recording details of a live birth, usually prising name, date, place, identity of parents, and sometimes additional information 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 rates BIRTH COHORT The location of a person in historical time as indexed by his or her year of birth. Birth cohorts are often differentially affected by social events. Numerous CoHORT variations in factors that have long-term effects on health(e.g, childbearing, smok ng, physical activity) have been documented. Cohort effects are easiest to distinguish when disease trends have accelerated, decelerated, or changed direction; where they
On a schematic continuum including possible, plausible, compatible, and coherent, the term plausible is not a demanding or stringent requirement, given the many biological mechanisms that often may underlie clinical and epidemiological observations; hence, in assessing causality, it may be logically more appropriate to require coherence (biological as well as clinical and epidemiological). The criterion of biological plausibility should hence be used cautiously, since it could impede development of new knowledge that does not fi t existing biological evidence or pathophysiological reasoning. Innovative, valid, and relevant clinical and epidemiological discoveries may precede the acquisition of knowledge on their biological mechanisms; i.e., biologically relevant epidemiological evidence may precede biological evidence. In evaluating associations between genetic variants and common complex diseases, we should fully expect biologically meaningful associations with small clinical or epidemiological effects.43 See also coherence; Hill’s criteria of causation. BIOLOGICAL TRANSMISSION See vector-borne infection. BIOMAGNIFICATION (Syn: biological magnifi cation, bioamplifi cation) Sequence of processes in an ecosystem by which higher concentrations (e.g., of a persistent toxic substance) are attained in organisms at higher levels in the food chain. The increase in concentration of an element or compound, such as a pesticide, that occurs in a food chain. Biomagnifi cation occurs across trophic (food chain) levels. See also bioaccumulation. BIOMARKER, BIOLOGICAL MARKER A cellular, biochemical, or molecular indicator of exposure; of biological, subclinical, or clinical effects; or of possible susceptibility (e.g., biomarkers of internal dose, biologically effective dose, early biological response, altered structure, altered function). It is occasionally an ambiguous term that suggests insuffi cient understanding of the pathophysiological or mechanistic role of the “marker.” See also molecular epidemiology. BIOMETRY Literally, measurement of life. The application of statistical methods to the study of numerical data based on observation of biological phenomena. The term was made popular by Karl Pearson (1857–1936), who founded the journal Biometrika. The British biologist Francis Galton (1822–1911) has been described as the founder of biometry, but others—e.g., the Frenchman Pierre-Charles-Alexandre Louis (1787– 1872)—preceded him. BIOMONITORING See biological monitoring. BIOSTATISTICS Application of statistics to biological problems. The term should not be restricted to mean the application of statistics to medical problems (medical statistics), since its real meaning is broader, subsuming agricultural statistics, forestry, and ecology, among other applications. BIRTH CERTIFICATE Offi cial, legal document recording details of a live birth, usually comprising name, date, place, identity of parents, and sometimes additional information 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 rates. BIRTH COHORT The location of a person in historical time as indexed by his or her year of birth. Birth cohorts are often differentially affected by social events. Numerous cohort variations in factors that have long-term effects on health (e.g., childbearing, smoking, physical activity) have been documented. Cohort effects are easiest to distinguish when disease trends have accelerated, decelerated, or changed direction; where they 21 Birth cohort