Concept of sufficient cause and component causes

Editor's Notes

• #3: This definition provides only a component of a complete causal mechanism of the Constellation of components that act in concert to produce a specific effect Every toddler – a scientist – busily fulfilling an earnest mission to develop logical structure for the strange objects and events that makes up his world. He develops and meticulously tests often through exasperating repetitions; an inventory of causal explanation that brings meaning to the perceived events so that he has power to control. Once a child reaches a certain age he will, on entering the new room, search for a wall switch to put light on and does so repeatedly to test the discovery beyond doubt! ….he is usually avoiding extraneous influences by avoiding parental interferences during such experiments….igniting paper by lens!!! The fruit of such scientific labor is a working knowledge of the essential system of causal relations that enables each of us to navigate our complex world General Model of Causation- every one also begin life as a pragmatic philosopher, developing a general causal theory that some events or states of Nature are causes having specific effects or effects with specific causes. All this though rudimentary is suggesting that we are equipped with curiosity to understand, logic, doubt, speculation, and developing methods to prove (experiments) Flick of light switch seems solely responsible for putting light on…but there are less evident causes that also operate to produce effect (unspent bulb, proper wiring, voltage)
• #4: ? Heavy smokers have approx. a 10% lifetime risk of developing lung cancer – some interpret this statement to mean that all men would be subject to a 10% probability of getting lung cancer if they were to become heavy smokers!!!! As if outcome, aside from smoking, were purely a matter of chance??? actually an individual will or will not get the disease….you cannot assign a group risk to an individual… Not all smokers get lung cancer- there are certain individuals primed by certain unknown circumstances/ conditions/ events and just adding smoking causes lung cancer. Eg asbestos exposure
• #7: The condition under which ‘E’ acts as “necessary and sufficient cause” is - “presence of A or B but not both” – One key difference in Pop.1 and 2 is its presence - in Pop. 1 it is 3600 out of total 4000 (90%), while in Pop.2 it is 400/ 4000= 10% presence of ‘A or B but not both’ is the causal complement of factor E which is common in population 1 and rare in Population 2 In Epidemiology, the strength of a factor’s effect is usually measured by the change in disease frequency by introducing or removing the factor This change may be measured in absolute or relative term, in either case, the strength of an effect may have tremendous public health significance, but it may have little biologic significance. Because given a specific causal mechanism, any of the component causes can have strong or weak effects. The actual identities of the components of sufficient cause are part of the biology of causation, whereas the strength of a factor’s effect depends on the time specific distribution of its causal complement in the population. Over a span of time, the strength of the effect of a given factor on the occurrence of a given disease may change because of the prevalence of its causal complement.
• #8: This need not to be ‘simultaneous’ e.g. head injury leading to permanent disturbance of equilibrium. Many years later this faulty equilibrium leads to fall and hip fracture. Here causal mechanism also include walking on slippery surface, lack of support etc The degree of observable interaction depends on how many different ‘sufficient causes’ produce disease and the proportion of cases that occur via ‘sufficient causes’ in which these component causes play role
• #9: What fraction is due to ‘E’ ? E causes disease through two mechanisms – II, III and all disease arising through theses two mechanism is due to E. That is not saying that all disease is due to ‘U’ alone or fraction of disease caused by E is caused by E alone!!!! These factors interact with complementary factors to produce disease….hence total of each factors contribution will not be 100%...it is infinity!!!!! A single cause that is present in every ‘sufficient cause’ will have the attributable fraction of 100% On priory ground 100% 0f any disease is inherited and 100% has environmental factor!! MacMohan (1960) cited an example given by Hogben in 1930 - of yellow shanks (shank is the lower part of leg also called shin), a trait occurring in certain genetic strains of Fowl fed on yellow corn. Both the yellow corn diet and genes are necessary but consider following situations: A farmer whoes Fowl has all the strains of Fowl, feeds them all yellow corn – what will be his interpretation? – he thinks the yelow color of shanks is genetic since he is feeding all same diet !!! Other farmer has Fowl with only liable strain, but he feds some white corn and some yellow corn…so he thinks its environmental (diet)! Phenylketonuria is considered by many a purely genetic disease, nontheless; the mental retardation can be prevented by diet!!!
• #10: Disease occurs only after the sequence is completed, so there will be delay while C,D,And E acts. Only when finally E acts disease occurs. In carcinogenesis, the term initiator and promoter have been used to refer to component cause of cancer that act early and later – hence initiator has long induction time while promtors have short
• #11: Role of Biomarkers (which may reflects the effects of earlier-acting agents on the organism )
• #13: AML also known as acute nonlymphocytic leukemia, tends to occur in later life, with a median age at onset of 65 years, males are at a higher risk than females. Risk factors include – exposure to ionizing radiation, benzene, certain drugs, and perhaps cigarette smoke, more in Down syndrome Presents with variety of symptoms – weakness, fatigue, unexplained weight loss, infection, and bleeding. Physical examination shows pale, have multiple bruises and fever with evidence of localized infection. Laboratory examination shows – anemia, low platelet counts, and markedly elevated leukocyte counts Infection and bleeding in these patients is directly related to chemotherapy induced suppression of bone marrow with consequent reduction in the circulating levels of neutrophils and platelets. In about 50% of these neutropenic patients with fever, an infection cannot be doccumented either clinically or microbiologically but on the basis evidence broad spectrum antibiotics are given
• #14: factor influencing prevalence – longer duration of disease, prolonged life span, increased incidence, in - migration of suceptibles, in - migration of cases, out migration of healthy, improved dx facilities (since so many factors unrelated to the cause of dis. Determine prev.- prev studies do not provide strong evidence of causality, but a good measure for chronic diseases of slow onset) Risk – is the probability that individuals in the population will get the disease in specified time period
• #15: What is the difference between incidence and prevalence? Prevalence can be viewed as a snapshot or a slice through the population at a point in time at which we determine who has the disease and who does not. But in so doing, we are not determining when the disease developed. Some individuals may have developed arthritis yesterday, some last week, some last year, and some 10 or 20 years ago. Thus, when we survey a community to estimate the prevalence of a disease, we generally do not take into account the duration of the disease. Consequently, the numerator of prevalence includes a mix of people with different durations of disease, and as a result we do not have a measure of risk. If we wish to measure risk, we must use incidence, because in contrast to prevalence, it includes only new cases or events and a specified time period during which those events occurred. In the medical and public health literature, the word prevalence is often used in two ways: Point prevalence. Prevalence of the disease at a certain point in time—this is the use of the term prevalence that we have just discussed. Period prevalence. How many people have had the disease at any point during a certain time period? The time period referred to may be arbitrarily selected, such as a month, a single calendar year, or a 5-year period. Some people may have developed the disease during that period, and others may have had the disease before and died or been cured during that period. The important point is that every person represented by the numerator had the disease at some time during the period specified.
• #16: People at Risk Who Are Observed throughout a Defined Time Period In the first type of denominator for incidence rate, we specify a period of time, and we must know that all of the individuals in the group represented by the denominator have been followed up for that entire period. The choice of time period is arbitrary: We could calculate incidence in 1 week, incidence in 1 month, incidence rate in 1 year, incidence rate in 5 years, and so on. The important point is that whatever time period is used in the calculation must be clearly specified, and all individuals included in the calculation must have been observed (at risk) for the entire period. The incidence rate calculated using a period of time during which all of the individuals in the population are considered to be at risk for the outcome is also called cumulative incidence, which is a measure of risk. When All People Are Not Observed for the Full Time Period, Person-Time, or Units of Time When Each Person Is Observed Often, however, every individual in the denominator has not been followed for the full time specified for a variety of reasons, including loss to follow-up or death from a cause other than that being studied. When different individuals are observed for different lengths of time, we calculate an incidence rate (also called an incidence density), in which the denominator consists of the sum of the units of time that each individual was at risk and was observed. This is called person-time and is often expressed in terms of person-months or person-years of observation. Let us consider person-years: One person at risk who is observed for one year = one person-year. One person at risk observed for 5 years = 5 person-years. But 5 people at risk, each of whom is observed for only 1 year, also = 5 person-years.
• #18: HAI = documented by cultures was not incubating on admission occurred at least 48 hrs after admission occurred no more than 48 hrs after discharge
• #20: Prevalence is an important and useful measure of the burden of disease in a community. For example, how many people in the community have arthritis? This information might help us to determine, for example, how many clinics are needed, what types of rehabilitation services are needed, and how many and what types of health professionals are needed. Prevalence is therefore valuable for planning health services. When we use prevalence, we also want to make future projections and anticipate the changes that are likely to take place in the disease burden. However, if we want to look at the cause, or etiology, of disease, we must explore the relationship between an exposure and the risk of disease, and to do this, we need incidence rates. Nevertheless, prevalence data may at times be very useful—they may be suggestive if not confirmatory in studies of the etiology of certain diseases. For example, asthma is a disease of children for which incidence is difficult to measure because the exact time of the beginning of the disease (its inception) is often hard both to define and to ascertain. For this reason, when we are interested in time trends and geographic distribution of asthma, prevalence is the measure most frequently used. Information on prevalence of asthma is often obtained from self-reports such as interviews or questionnaires. Figure 3-15 shows current asthma prevalence in children up to 17 years of age, by state in the United States for 2001–2005. Current asthma prevalence was based on two questions: “Has a doctor or other health professional ever told you that (child's name) had asthma?” and “Does (child's name) still have asthma?” Overall, prevalence was highest in the northeastern states. The explanation for this observation is not entirely clear. Although adverse climate and polluted air may be implicated, other factors may also play a role in the high asthma prevalence in the northeast, such as more complete ascertainment of cases in the medical care system and higher asthma prevalence in Puerto Rican children who are concentrated in this region. Another example of the value of prevalence data is seen in Figure 3-16 . One of the most significant and challenging public health problems today in the United States and in other developed countries is the dramatically increasing prevalence of obesity. Obesity is associated with significant morbidity and mortality and is a risk factor for diseases such as hypertension, type 2 diabetes, coronary disease, and stroke. In this figure, prevalence of obesity by state is shown for each of four years: 1990, 1995, 2000, and 2005. The trend over time is grim: In 1990, all reporting states reported obesity prevalence data below 15%. By 2005, all but four states had prevalence estimates above 20%; 17 states reported a prevalence of obesity equal to or greater than 25% and three of these states (Louisiana, Mississippi, and West Virginia) reported obesity prevalence over 30%.
• #24: average length of stay = 127859/5031=25.41 days
• #25: If we would have taken all patient days i.e. not excluding 596 from 127859 IR would be 0.00466cases / patient day rather than 0.00468 cases / patient day (not much difference) 127859 -596=127263
• #29: We have said that incidence is a measure of risk and that prevalence is not, because it does not take into account the duration of the disease.
• #32: Ignore the bar graph for the moment, and consider the line curve. The pattern is one of continually increasing incidence with age, with a change in the slope of the curve between ages 45 and 50 years. This change is observed in many countries. It has been suggested that something happens near the time of menopause, and that premenopausal and postmenopausal breast cancer may be different diseases. Note that, even in old age, the incidence or risk of breast cancer continues to rise. Now let us look at the histogram—the distribution of breast cancer cases by age. If the incidence is increasing so dramatically with age, why are only fewer than 5% of the cases occurring in the oldest age group of women? The answer is that there are very few women alive in that age group, so that even though they have the highest risk of breast cancer, the group is so small that they contribute only a small proportion of the total number of breast cancer cases seen at all ages. The fact that so few cases of breast cancer are seen in this age group has contributed to a false public impression that the risk of breast cancer is low in this group and that mammography is therefore not important in the elderly. This is a serious misperception. The need to change public thinking on this issue is a major public health challenge. We therefore see the importance of recognizing the distinction between the distribution of disease or the proportion of cases, and the incidence rate or risk of the disease.
• #33: e.g. rabies # Disease duration is reduced and it is becoming acute, or # Disease becoming more fatal
• #34: For example, when insulin first became available, what happened to the prevalence of diabetes? The prevalence increased because diabetes was not cured, but was only controlled. Many patients with diabetes who formerly would have died now survived; therefore, the prevalence increased. This seeming paradox is often the case with public health programs: a new measure is introduced that enhances survival or detects the disease in more people, and the net effect is an apparent increase in prevalence. It may be difficult to convince some people that a program is successful if the prevalence of the disease that is the target of the program actually increases. However, this clearly occurs when death is prevented and the disease is not cured. e.g. diabetes 1.Slow recovery, Fatality reduced (potent drugs available, new drugs effective) or, 3.Immigration of cases from other area (for better facility available).
• #35: Recovery is becoming rapid, (may be a new drug identified is more effective) # Disease turns into a more fatal one (because of treatment failure, change in virulence, drug resistance) or, # Selective emigration of cases (to seek treatment elsewhere)
• #38: Observation of each patient begins at time ‘0’ and continues until one of the following outcomes occur: death, survival for 5 yrs, or follow up ceases (the subject is censored) prior to death or completion of a full period of observation Example: from 1992-1999 only 19% of patients survived for at least 5 yrs from the time of Dx persons under 65 yrs of age at Dx 5-yr survival rate = 31% while for persons above 65 yrs it is 4% So a person of less than 65 yrs, if diagnosed with this disease would be expected to have 1 in 3 chance of surviving 5 yrs from the time of Dx while a person > 65 yrs has only 1 in 25 chance
• #40: propensity = tendency
• #47: Underlying cause of death is defined as – dis. Or injury that initiated the train of morbid events leading directly to death or occurrence of violence or accident that resulted in fatal injury
• #57: Only 10% of patients develop active clinical illness months or years later when mycobacterium begins replicates and cause symptoms
• #59: An effective plan for control of TB requires that infectious persons be identified early, isolated from susceptibles and treated. Screening for asymptomatic infection in the community. Guideline for prophylactic therapy dictate that close contacts who have –ve skin test should receive antibiotic for 12 weeks until repeat test is negative