In epidemiology , a risk factor or determinant is a variable associated with an increased risk of disease or infection .
67-662: Epidemiology is the study and analysis of the distribution (who, when, and where), patterns and determinants of health and disease conditions in a defined population . It is a cornerstone of public health , and shapes policy decisions and evidence-based practice by identifying risk factors for disease and targets for preventive healthcare . Epidemiologists help with study design, collection, and statistical analysis of data, amend interpretation and dissemination of results (including peer review and occasional systematic review ). Epidemiology has helped develop methodology used in clinical research , public health studies, and, to
134-437: A causal association does not exist in general. Conversely, it can be (and is in some circumstances) taken by US courts, in an individual case, to justify an inference that a causal association does exist, based upon a balance of probability . The subdiscipline of forensic epidemiology is directed at the investigation of specific causation of disease or injury in individuals or groups of individuals in instances in which causation
201-455: A disease is in an endemic steady state in a population, the relation above allows the basic reproduction number (R 0 ) of a particular infection to be estimated. This in turn can be fed into a mathematical model for the epidemic. Based on the reproduction number, we can define the epidemic waves, such as the first wave, second wave, etc. for COVID-19 in different regions and countries. It has been claimed that endemic COVID-19 implies that
268-494: A health system responds to current population health issues but also how a health system can be managed to better respond to future potential population health issues. Examples of organizations that use population-based health management that leverage the work and results of epidemiological practice include Canadian Strategy for Cancer Control, Health Canada Tobacco Control Programs, Rick Hansen Foundation, Canadian Tobacco Control Research Initiative. Each of these organizations uses
335-413: A higher rate of measles because they are less likely to have developed immunity during a previous epidemic. Statistical methods are frequently used to assess the strength of an association and to provide causal evidence, for example in the study of the link between smoking and lung cancer . Statistical analysis along with the biological sciences can establish that risk factors are causal. Some prefer
402-520: A lesser extent, basic research in the biological sciences. Major areas of epidemiological study include disease causation, transmission , outbreak investigation, disease surveillance , environmental epidemiology , forensic epidemiology , occupational epidemiology , screening , biomonitoring , and comparisons of treatment effects such as in clinical trials . Epidemiologists rely on other scientific disciplines like biology to better understand disease processes, statistics to make efficient use of
469-785: A population (endemic). The term "epidemiology" appears to have first been used to describe the study of epidemics in 1802 by the Spanish physician Joaquín de Villalba [ es ] in Epidemiología Española . Epidemiologists also study the interaction of diseases in a population, a condition known as a syndemic . The term epidemiology is now widely applied to cover the description and causation of not only epidemic, infectious disease, but of disease in general, including related conditions. Some examples of topics examined through epidemiology include as high blood pressure, mental illness and obesity . Therefore, this epidemiology
536-463: A population with some immune individuals, the basic reproduction number multiplied by the proportion of susceptible individuals in the population ( S ) must be one. This takes account of the probability of each individual to whom the disease may be transmitted being susceptible to it, effectively discounting the immune sector of the population. So, for a disease to be in an endemic steady state or endemic equilibrium , it holds that In this way,
603-520: A population-based health management framework called Life at Risk that combines epidemiological quantitative analysis with demographics, health agency operational research and economics to perform: Applied epidemiology is the practice of using epidemiological methods to protect or improve the health of a population. Applied field epidemiology can include investigating communicable and non-communicable disease outbreaks, mortality and morbidity rates, and nutritional status, among other indicators of health, with
670-422: A prospective study, and confounders are more easily controlled for. However, they are more costly, and there is a greater chance of losing subjects to follow-up based on the long time period over which the cohort is followed. Cohort studies also are limited by the same equation for number of cases as for cohort studies, but, if the base incidence rate in the study population is very low, the number of cases required
737-401: A random sample from the original population at risk. This has as a consequence that the control group can contain people with the disease under study when the disease has a high attack rate in a population. A major drawback for case control studies is that, in order to be considered to be statistically significant, the minimum number of cases required at the 95% confidence interval is related to
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#1732780687626804-463: A specific outcome, the other determinants may act as confounding factors, and need to be controlled for, e.g. by stratification . The potentially confounding determinants varies with what outcome is studied, but the following general confounders are common to most epidemiological associations, and are the determinants most commonly controlled for in epidemiological studies: Other less commonly adjusted for possible confounders include: A risk marker
871-443: A unique disease process different from any other individual ("the unique disease principle"), considering uniqueness of the exposome (a totality of endogenous and exogenous / environmental exposures) and its unique influence on molecular pathologic process in each individual. Studies to examine the relationship between an exposure and molecular pathologic signature of disease (particularly cancer ) became increasingly common throughout
938-399: Is a core component, that is unified with management science to provide efficient and effective health care and health guidance to a population. This task requires the forward-looking ability of modern risk management approaches that transform health risk factors, incidence, prevalence and mortality statistics (derived from epidemiological analysis) into management metrics that not only guide how
1005-575: Is a known risk factor for developing scurvy . Specific to public health policy , a determinant is a health risk that is general, abstract, related to inequalities, and difficult for an individual to control. For example, poverty is known to be a determinant of an individual's standard of health . Risk factors may be used to identify high-risk people . Risk factors or determinants are correlational and not necessarily causal , because correlation does not prove causation . For example, being young cannot be said to cause measles , but young people have
1072-457: Is a variable that is quantitatively associated with a disease or other outcome, but direct alteration of the risk marker does not necessarily alter the risk of the outcome. For example, driving-while-intoxicated (DWI) history is a risk marker for pilots as epidemiologic studies indicate that pilots with a DWI history are significantly more likely than their counterparts without a DWI history to be involved in aviation crashes. The term "risk factor"
1139-425: Is based upon how the pattern of the disease causes change in the function of human beings. The Greek physician Hippocrates , taught by Democritus, was known as the father of medicine , sought a logic to sickness; he is the first person known to have examined the relationships between the occurrence of disease and environmental influences. Hippocrates believed sickness of the human body to be caused by an imbalance of
1206-478: Is beyond the domain of the science of epidemiology. Epidemiology has its limits at the point where an inference is made that the relationship between an agent and a disease is causal (general causation) and where the magnitude of excess risk attributed to the agent has been determined; that is, epidemiology addresses whether an agent can cause disease, not whether an agent did cause a specific plaintiff's disease. In United States law, epidemiology alone cannot prove that
1273-483: Is disputed or is unclear, for presentation in legal settings. Epidemiological practice and the results of epidemiological analysis make a significant contribution to emerging population-based health management frameworks. Population-based health management encompasses the ability to: Modern population-based health management is complex, requiring a multiple set of skills (medical, political, technological, mathematical, etc.) of which epidemiological practice and analysis
1340-533: Is endemic in the United Kingdom, but malaria is not. Every year, there are a few cases of malaria reported in the UK, but these do not lead to sustained transmission in the population due to the lack of a suitable vector (mosquitoes of the genus Anopheles ). Consequently, the number of people infected by malaria in the UK is too variable to be called endemic. However, the number of people who get chickenpox in
1407-535: Is famous for his investigations into the causes of the 19th-century cholera epidemics, and is also known as the father of (modern) Epidemiology. He began with noticing the significantly higher death rates in two areas supplied by Southwark Company. His identification of the Broad Street pump as the cause of the Soho epidemic is considered the classic example of epidemiology. Snow used chlorine in an attempt to clean
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#17327806876261474-499: Is in the term inference . Correlation, or at least association between two variables, is a necessary but not sufficient criterion for the inference that one variable causes the other. Epidemiologists use gathered data and a broad range of biomedical and psychosocial theories in an iterative way to generate or expand theory, to test hypotheses, and to make educated, informed assertions about which relationships are causal, and about exactly how they are causal. Epidemiologists emphasize that
1541-417: Is increasing recognition that a wide range of modern data sources, many not originating from healthcare or epidemiology, can be used for epidemiological study. Such digital epidemiology can include data from internet searching, mobile phone records and retail sales of drugs. Epidemiologists employ a range of study designs from the observational to experimental and generally categorized as descriptive (involving
1608-404: Is reduced by 1 ⁄ 2 . Although epidemiology is sometimes viewed as a collection of statistical tools used to elucidate the associations of exposures to health outcomes, a deeper understanding of this science is that of discovering causal relationships. " Correlation does not imply causation " is a common theme for much of the epidemiological literature. For epidemiologists, the key
1675-519: Is typically determined using DNA from peripheral blood leukocytes. Since the 2000s, genome-wide association studies (GWAS) have been commonly performed to identify genetic risk factors for many diseases and health conditions. While most molecular epidemiology studies are still using conventional disease diagnosis and classification systems, it is increasingly recognized that disease progression represents inherently heterogeneous processes differing from person to person. Conceptually, each individual has
1742-437: Is used to describe the intersection of Host , Agent , and Environment in analyzing an outbreak. Case-series may refer to the qualitative study of the experience of a single patient, or small group of patients with a similar diagnosis, or to a statistical factor with the potential to produce illness with periods when they are unexposed. The former type of study is purely descriptive and cannot be used to make inferences about
1809-474: The " one cause – one effect " understanding is a simplistic mis-belief. Most outcomes, whether disease or death, are caused by a chain or web consisting of many component causes. Causes can be distinguished as necessary, sufficient or probabilistic conditions. If a necessary condition can be identified and controlled (e.g., antibodies to a disease agent, energy in an injury), the harmful outcome can be avoided (Robertson, 2015). One tool regularly used to conceptualize
1876-457: The "who, what, where and when of health-related state occurrence". However, analytical observations deal more with the 'how' of a health-related event. Experimental epidemiology contains three case types: randomized controlled trials (often used for a new medicine or drug testing), field trials (conducted on those at a high risk of contracting a disease), and community trials (research on social originating diseases). The term 'epidemiologic triad'
1943-514: The 2000s. However, the use of molecular pathology in epidemiology posed unique challenges, including lack of research guidelines and standardized statistical methodologies, and paucity of interdisciplinary experts and training programs. Furthermore, the concept of disease heterogeneity appears to conflict with the long-standing premise in epidemiology that individuals with the same disease name have similar etiologies and disease processes. To resolve these issues and advance population health science in
2010-492: The 2010s. By 2012, it was recognized that many pathogens' evolution is rapid enough to be highly relevant to epidemiology, and that therefore much could be gained from an interdisciplinary approach to infectious disease integrating epidemiology and molecular evolution to "inform control strategies, or even patient treatment." Modern epidemiological studies can use advanced statistics and machine learning to create predictive models as well as to define treatment effects. There
2077-560: The OR, a RR greater than 1 shows association, where the conclusion can be read "those with the exposure were more likely to develop the disease." Prospective studies have many benefits over case control studies. The RR is a more powerful effect measure than the OR, as the OR is just an estimation of the RR, since true incidence cannot be calculated in a case control study where subjects are selected based on disease status. Temporality can be established in
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2144-403: The UK varies little from year to year, so chickenpox is considered endemic in the UK. For an infection that relies on person-to-person transmission, to be endemic, each person who becomes infected with the disease must pass it on to one other person on average. Assuming a completely susceptible population, that means that the basic reproduction number (R 0 ) of the infection must equal one. In
2211-407: The assessment of data covering time, place, and person), analytic (aiming to further examine known associations or hypothesized relationships), and experimental (a term often equated with clinical or community trials of treatments and other interventions). In observational studies, nature is allowed to "take its course", as epidemiologists observe from the sidelines. Conversely, in experimental studies,
2278-414: The case control study. However, the point estimate generated is the relative risk (RR), which is the probability of disease for a person in the exposed group, P e = A / ( A + B ) over the probability of disease for a person in the unexposed group, P u = C / ( C + D ), i.e. RR = P e / P u . As with
2345-429: The causation of the disease. Case-control studies are usually faster and more cost-effective than cohort studies but are sensitive to bias (such as recall bias and selection bias ). The main challenge is to identify the appropriate control group; the distribution of exposure among the control group should be representative of the distribution in the population that gave rise to the cases. This can be achieved by drawing
2412-426: The cause-and-effect hypothesis and none can be required sine qua non ." Epidemiological studies can only go to prove that an agent could have caused, but not that it did cause, an effect in any particular case: Epidemiology is concerned with the incidence of disease in populations and does not address the question of the cause of an individual's disease. This question, sometimes referred to as specific causation,
2479-407: The chicken and 22 of them were ill, while of the 35 people who had the fish or vegetarian meal only 2 were ill. Did the chicken make the people ill? So the chicken eaters' risk = 22/74 = 0.297 And non-chicken eaters' risk = 2/35 = 0.057. Those who ate the chicken had a risk over five times as high as those who did not, that is, a relative risk of more than five. This suggests that eating chicken
2546-445: The data and draw appropriate conclusions, social sciences to better understand proximate and distal causes, and engineering for exposure assessment . Epidemiology , literally meaning "the study of what is upon the people", is derived from Greek epi 'upon, among' demos 'people, district' and logos 'study, word, discourse', suggesting that it applies only to human populations. However,
2613-444: The disease severity would be mild. However, endemicity has no inherent relationship with disease severity. Endemic COVID-19 could be mild if previously acquired immunity reduces the risk of death and disability during future infections, but in itself endemicity only means that there will be a steady, predictable number of sick people. This is a short, incomplete list of some infections that are usually considered endemic: Smallpox
2680-496: The disease to the cases in the series. A prospective study would involve following the case series over time to evaluate the disease's natural history. The latter type, more formally described as self-controlled case-series studies, divide individual patient follow-up time into exposed and unexposed periods and use fixed-effects Poisson regression processes to compare the incidence rate of a given outcome between exposed and unexposed periods. This technique has been extensively used in
2747-605: The epidemiologist is the one in control of all of the factors entering a certain case study. Epidemiological studies are aimed, where possible, at revealing unbiased relationships between exposures such as alcohol or smoking, biological agents , stress , or chemicals to mortality or morbidity . The identification of causal relationships between these exposures and outcomes is an important aspect of epidemiology. Modern epidemiologists use informatics and infodemiology as tools. Observational studies have two components, descriptive and analytical. Descriptive observations pertain to
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2814-768: The era of molecular precision medicine , "molecular pathology" and "epidemiology" was integrated to create a new interdisciplinary field of " molecular pathological epidemiology " (MPE), defined as "epidemiology of molecular pathology and heterogeneity of disease". In MPE, investigators analyze the relationships between (A) environmental, dietary, lifestyle and genetic factors; (B) alterations in cellular or extracellular molecules; and (C) evolution and progression of disease. A better understanding of heterogeneity of disease pathogenesis will further contribute to elucidate etiologies of disease. The MPE approach can be applied to not only neoplastic diseases but also non-neoplastic diseases. The concept and paradigm of MPE have become widespread in
2881-570: The field and advanced methods to study cancer, a disease with patterns and mode of occurrences that could not be suitably studied with the methods developed for epidemics of infectious diseases. Geography pathology eventually combined with infectious disease epidemiology to make the field that is epidemiology today. Another breakthrough was the 1954 publication of the results of a British Doctors Study , led by Richard Doll and Austin Bradford Hill , which lent very strong statistical support to
2948-403: The four humors (black bile, yellow bile, blood, and phlegm). The cure to the sickness was to remove or add the humor in question to balance the body. This belief led to the application of bloodletting and dieting in medicine. He coined the terms endemic (for diseases usually found in some places but not in others) and epidemic (for diseases that are seen at some times but not others). In
3015-458: The general population of patients with that disease. These types of studies, in which an astute clinician identifies an unusual feature of a disease or a patient's history, may lead to a formulation of a new hypothesis. Using the data from the series, analytic studies could be done to investigate possible causal factors. These can include case-control studies or prospective studies. A case-control study would involve matching comparable controls without
3082-450: The group as a result of travel or similar means. The term describes the distribution of an infectious disease among a group of people or within a populated area. An endemic disease always has a steady, predictable number of people getting sick, but that number can be high ( hyperendemic ) or low ( hypoendemic ), and the disease can be severe or mild. Also, a disease that is usually endemic can become epidemic . For example, chickenpox
3149-401: The infection neither dies out, nor does the number of infected people increase exponentially . An infection that starts as an epidemic will eventually either die out (with the possibility of it resurging in a theoretically predictable cyclical manner) or reach the endemic steady state, depending on a number of factors, including the virulence of the disease and its mode of transmission . If
3216-574: The link between tobacco smoking and lung cancer . In the late 20th century, with the advancement of biomedical sciences, a number of molecular markers in blood, other biospecimens and environment were identified as predictors of development or risk of a certain disease. Epidemiology research to examine the relationship between these biomarkers analyzed at the molecular level and disease was broadly named " molecular epidemiology ". Specifically, " genetic epidemiology " has been used for epidemiology of germline genetic variation and disease. Genetic variation
3283-401: The main etiological work that brought forward the concept. His concepts were still being considered in analysing SARS outbreak by WHO in 2004 in the context of traditional Chinese medicine. Another pioneer, Thomas Sydenham (1624–1689), was the first to distinguish the fevers of Londoners in the later 1600s. His theories on cures of fevers met with much resistance from traditional physicians at
3350-448: The middle of the 16th century, a doctor from Verona named Girolamo Fracastoro was the first to propose a theory that the very small, unseeable, particles that cause disease were alive. They were considered to be able to spread by air, multiply by themselves and to be destroyable by fire. In this way he refuted Galen 's miasma theory (poison gas in sick people). In 1543 he wrote a book De contagione et contagiosis morbis , in which he
3417-503: The multicausality associated with disease is the causal pie model . In 1965, Austin Bradford Hill proposed a series of considerations to help assess evidence of causation, which have come to be commonly known as the " Bradford Hill criteria ". In contrast to the explicit intentions of their author, Hill's considerations are now sometimes taught as a checklist to be implemented for assessing causality. Hill himself said "None of my nine viewpoints can bring indisputable evidence for or against
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#17327806876263484-416: The odds of exposure in the cases (A/C) to the odds of exposure in the controls (B/D), i.e. OR = (AD/BC). If the OR is significantly greater than 1, then the conclusion is "those with the disease are more likely to have been exposed", whereas if it is close to 1 then the exposure and disease are not likely associated. If the OR is far less than one, then this suggests that the exposure is a protective factor in
3551-498: The odds ratio by the equation: where N is the ratio of cases to controls. As the odds ratio approaches 1, the number of cases required for statistical significance grows towards infinity; rendering case-control studies all but useless for low odds ratios. For instance, for an odds ratio of 1.5 and cases = controls, the table shown above would look like this: For an odds ratio of 1.1: Cohort studies select subjects based on their exposure status. The study subjects should be at risk of
3618-414: The outcome under investigation at the beginning of the cohort study; this usually means that they should be disease free when the cohort study starts. The cohort is followed through time to assess their later outcome status. An example of a cohort study would be the investigation of a cohort of smokers and non-smokers over time to estimate the incidence of lung cancer. The same 2×2 table is constructed as with
3685-399: The prevailing Miasma Theory of the time, a model of disease in which poor air quality was blamed for illness. This was used to rationalize high rates of infection in impoverished areas instead of addressing the underlying issues of poor nutrition and sanitation, and was proven false by his work. Other pioneers include Danish physician Peter Anton Schleisner , who in 1849 related his work on
3752-638: The prevention of the epidemic of neonatal tetanus on the Vestmanna Islands in Iceland . Another important pioneer was Hungarian physician Ignaz Semmelweis , who in 1847 brought down infant mortality at a Vienna hospital by instituting a disinfection procedure. His findings were published in 1850, but his work was ill-received by his colleagues, who discontinued the procedure. Disinfection did not become widely practiced until British surgeon Joseph Lister 'discovered' antiseptics in 1865 in light of
3819-491: The purpose of communicating the results to those who can implement appropriate policies or disease control measures. Risk factor (epidemiology) Due to a lack of harmonization across disciplines, determinant , in its more widely accepted scientific meaning , is often used as a synonym. The main difference lies in the realm of practice: medicine ( clinical practice ) versus public health . As an example from clinical practice, low ingestion of dietary sources of vitamin C
3886-401: The same population that gave rise to the cases. The case-control study looks back through time at potential exposures that both groups (cases and controls) may have encountered. A 2×2 table is constructed, displaying exposed cases (A), exposed controls (B), unexposed cases (C) and unexposed controls (D). The statistic generated to measure association is the odds ratio (OR), which is the ratio of
3953-455: The study of adverse reactions to vaccination and has been shown in some circumstances to provide statistical power comparable to that available in cohort studies. Case-control studies select subjects based on their disease status. It is a retrospective study. A group of individuals that are disease positive (the "case" group) is compared with a group of disease negative individuals (the "control" group). The control group should ideally come from
4020-437: The term is widely used in studies of zoological populations (veterinary epidemiology), although the term " epizoology " is available, and it has also been applied to studies of plant populations (botanical or plant disease epidemiology ). The distinction between "epidemic" and "endemic" was first drawn by Hippocrates , to distinguish between diseases that are "visited upon" a population (epidemic) from those that "reside within"
4087-414: The term risk factor to mean causal determinants of increased rates of disease, and for unproven links to be called possible risks, associations, etc. When done thoughtfully and based on research, identification of risk factors can be a strategy for medical screening . Mainly taken from risk factors for breast cancer , risk factors can be described in terms of, for example: At a wedding, 74 people ate
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#17327806876264154-714: The time. He was not able to find the initial cause of the smallpox fever he researched and treated. John Graunt , a haberdasher and amateur statistician, published Natural and Political Observations ... upon the Bills of Mortality in 1662. In it, he analysed the mortality rolls in London before the Great Plague , presented one of the first life tables , and reported time trends for many diseases, new and old. He provided statistical evidence for many theories on disease, and also refuted some widespread ideas on them. John Snow
4221-411: The water and removed the handle; this ended the outbreak. This has been perceived as a major event in the history of public health and regarded as the founding event of the science of epidemiology, having helped shape public health policies around the world. However, Snow's research and preventive measures to avoid further outbreaks were not fully accepted or put into practice until after his death due to
4288-632: The work of Louis Pasteur . In the early 20th century, mathematical methods were introduced into epidemiology by Ronald Ross , Janet Lane-Claypon , Anderson Gray McKendrick , and others. In a parallel development during the 1920s, German-Swiss pathologist Max Askanazy and others founded the International Society for Geographical Pathology to systematically investigate the geographical pathology of cancer and other non-infectious diseases across populations in different regions. After World War II, Richard Doll and other non-pathologists joined
4355-450: Was coined by former Framingham Heart Study director, William B. Kannel in a 1961 article in Annals of Internal Medicine . Endemic (epidemiology) In epidemiology , an infection is said to be endemic in a specific population or populated place when that infection is constantly present, or maintained at a baseline level, without extra infections being brought into
4422-438: Was the cause of the illness, but this is not proof. This example of a risk factor is described in terms of the relative risk it confers, which is evaluated by comparing the risk of those exposed to the potential risk factor to those not exposed. The probability of an outcome usually depends on an interplay between multiple associated variables. When performing epidemiological studies to evaluate one or more determinants for
4489-666: Was the first to promote personal and environmental hygiene to prevent disease. The development of a sufficiently powerful microscope by Antonie van Leeuwenhoek in 1675 provided visual evidence of living particles consistent with a germ theory of disease . During the Ming dynasty , Wu Youke (1582–1652) developed the idea that some diseases were caused by transmissible agents, which he called Li Qi (戾气 or pestilential factors) when he observed various epidemics rage around him between 1641 and 1644. His book Wen Yi Lun (瘟疫论, Treatise on Pestilence/Treatise of Epidemic Diseases) can be regarded as
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